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10.1101/19003004 | The Paradox of Female Obesity in Low and Lower-Middle Income Countries | SettingObesity, once considered an epidemic of the developed world, is now becoming an even more prominent problem than underweight in low and lower middle income countries (LLMICs). Ample literature has shown that as a countrys income increases, the burden of obesity shifts from the rich to the poor. This is known as the "Reversal Hypothesis." Many studies have explored the effects of various social determinants of health on obesity, but few have studied education as an independent variable on female obesity across LLMICs.
ObjectiveGlobally, adult females have a higher prevalence of obesity and the obesity shift occurs more quickly for women than for men. We aim to address this disparity and contribute towards the reversal hypothesis by exploring the association of education and obesity in women in LLMICs.
DesignIn this cross-sectional study, we used a multi-national and multi-year database from the publicly available Demographic and Health Surveys program with data from 34 LLMICs. Education levels are standardized across countries during survey collection.
ResultsOur age-adjusted prevalence ratio (AA-PR) analysis shows that women in LLMICs with higher education have a significantly greater prevalence of obesity than women with no education. We analyzed this phenomenon by individual nations, continents, and income classifications. Educated women living in low income countries are 5.12 times more obese than uneducated women (AA-PR, 95% CI=4.75, 5.53) and 3.42 times more obese in lower middle income countries (AA-PR, 95% CI=3.31, 3.54).
ConclusionThese findings highlight a need for more studies and policy attention focusing on female education levels, among other factors, to understand, predict, and prevent obesity in LLMICs.
ARTICLE SUMMARY
Strengths and limitations of this studyO_LIA rigorous sample size of 943,947 adult females in 34 LLMIC countries was utilized to study the association between adult female obesity and education level.
C_LIO_LIAge-adjusted and age-and-wealth-adjusted prevalence ratios of obesity were analyzed based on 34 individual nations, three continents, and two major income categories.
C_LIO_LIThis study includes the most recent data available through the Demographic and Health Surveys program, which standardizes education levels during data collection, allowing for comparison between all surveyed countries.
C_LIO_LIThis study is limited by the relatively small number of countries for which data is available through the DHS dataset, and thus, further research will be needed to show whether these results are generalizable to other LLMICs.
C_LI | epidemiology |
10.1101/19003301 | Real-time Hearing Threshold Determination of Auditory Brainstem Responses by Cross-correlation Analysis | Auditory brainstem response (ABR) serves as an objective indication of auditory perception at given sound level and is nowadays widely used in hearing function assessment. Despite efforts for automation over decades, hearing threshold determination by machine algorithm remains unreliable and thereby still rely on visual identification by trained personnel. Here, we described a procedure for automatic threshold determination that can be used in both animal and human ABR tests. The method terminates level averaging of ABR recordings upon detection of time-locked waveform through cross-correlation analysis. The threshold level was then indicated by a dramatic increase in the sweep numbers required to produce "qualified" level averaging. A good match was obtained between the algorithm outcome and the human readouts. Moreover, the method varies the level averaging based on the cross-correlation, thereby adapting to the signal-to-noise ratio of single sweep recordings. These features empower a robust and fully automated ABR test. | otolaryngology |
10.1101/19006858 | Secrets of the hospital underbelly: patterns of abundance of antimicrobial resistance genes in hospital wastewater vary by specific antimicrobial and bacterial family | BackgroundHospital wastewater is a major source of antimicrobial resistance (AMR) outflow into the environment. This study uses metagenomics to study how hospital clinical activity impacts antimicrobial resistance genes (ARGs) abundances in hospital wastewater.
MethodsSewage was collected over a 24-hour period from multiple wastewater collection points representing different specialties within a tertiary hospital site and simultaneously from community sewage works. High throughput shotgun sequencing was performed using Illumina HiSeq4000. ARG abundances were correlated to hospital antimicrobial usage (AMU), data on clinical activity and resistance prevalence in clinical isolates.
ResultsMicrobiota and ARG composition varied between collection points and overall ARG abundance was higher in hospital wastewater than in community influent. ARG and microbiota compositions were correlated (Procrustes analysis, P=0.014). Total antimicrobial usage was not associated with higher ARG abundance in wastewater. However, there was a small positive association between resistance genes and antimicrobial usage matched to ARG phenotype (IRR 1.11, CI 1.06 - 1.16, P<0.001). Furthermore, analysing carbapenem and vancomycin resistance separately indicated that counts of ARGs to these antimicrobials were positively associated with their increased usage (carbapenem rate ratio (RR) 1.91, 95% confidence intervals (CI) 1.01 - 3.72, P=0.07, and vancomycin RR 10.25, CI 2.32 - 49.10, P<0.01). Overall, ARG abundance within hospital wastewater did not reflect resistance patterns in clinical isolates from concurrent hospital inpatients. However, for clinical isolates of the family Enterococcaceae and Staphylococcaceae, there was a positive relationship with wastewater ARG abundance (odds ratio (OR) 1.62, CI 1.33 - 2.00, P<0.001, and OR 1.65, CI 1.21 - 2.30, P=0.006 respectively).
ConclusionsWe found that the relationship between hospital wastewater ARGs and antimicrobial usage or clinical isolate resistance varies by specific antimicrobial and bacterial family studied. One explanation we consider is that relationships observed from multiple departments within a single hospital site will be detectable only for ARGs against parenteral antimicrobials uniquely used in the hospital setting. Our work highlights that using metagenomics to identify the full range of ARGs in hospital wastewater is a useful surveillance tool to monitor hospital ARG carriage and outflow and guide environmental policy on AMR. | infectious diseases |
10.1101/19008581 | Memory recovery is related to default mode network impairment and neurite density during brain tumours treatment | ObjectiveThe aim of this study is to test brain tumour interactions with brain networks thereby identifying protective features and risk factors for memory recovery after surgical resection.
MethodsSeventeen patients with diffuse non-enhancing glioma (aged 22-56 years) were longitudinally MRI-scanned before and after surgery, and during a 12-months recovery period (47 MRI in total after exclusion). After each scanning session, a battery of memory tests was performed using a tablet-based screening tool, including free verbal memory, overall verbal memory, episodic memory, orientation, forward digit span and backwards digit span. Using structural MRI and Neurite Orientation Dispersion and Density Imaging (NODDI) derived from diffusion-weighted images, we respectively estimated lesion overlap and Neurite Density with brain networks derived from normative data in healthy participants (somato-motor, dorsal attention, ventral attention, fronto-parietal and Default Mode Network -DMN-). Linear Mixed Models (LMMs) that regressed out the effect of age, gender, tumour grade, type of treatment, total lesion volume and total neurite density were used to test the potential longitudinal associations between imaging markers and memory recovery.
ResultsMemory recovery was not significantly associated with tumour location based on traditional lobe classification nor with the type of treatment received by patients (i.e. surgery alone or surgery with adjuvant chemoradiotherapy). Non-local effects of tumours were evident on Neurite Density, which was reduced not only within the tumour, but also beyond the tumour boundary. In contrast, high preoperative Neurite Density outside the tumour, but within the DMN, was associated with better memory recovery (LMM, Pfdr<10-3). Furthermore, postoperative and follow-up Neurite Density within the DMN and fronto-parietal network were also associated with memory recovery (LMM, Pfdr=0.014 and Pfdr=0.001, respectively). Preoperative tumour, and post-operative lesion, overlap with the DMN showed a significant negative association with memory recovery (LMM, Pfdr=0.002 and Pfdr<10-4, respectively).
ConclusionImaging biomarkers of cognitive recovery and decline can be identified using NODDI and resting-state networks. Brain tumours and their corresponding treatment affecting brain networks that are fundamental for memory functioning such as the DMN can have a major impact on patients memory recovery. | radiology and imaging |
10.1101/19010082 | DeepProg: an ensemble of deep-learning and machine-learning models for prognosis prediction using multi-omics data | Multi-omics data are good resources for prognosis and survival prediction, however, these are difficult to integrate computationally. We introduce DeepProg, a novel ensemble framework of deep-learning and machine-learning approaches that robustly predicts patient survival subtypes using multi-omics data. It identifies two optimal survival subtypes in most cancers and yields significantly better risk-stratification than other multi-omics integration methods. DeepProg is highly predictive, exemplified by two liver cancer (C-index 0.73-0.80) and five breast cancer datasets (C-index 0.68-0.73). Pan-cancer analysis associates common genomic signatures in poor survival subtypes with extracellular matrix modeling, immune deregulation, and mitosis processes. DeepProg is freely available at https://github.com/lanagarmire/DeepProg | genetic and genomic medicine |
10.1101/19011312 | Long-Term Effects of Chronic Hemiparetic Stroke and Botulinum Neurotoxin on Wrist and Finger Passive Mechanical Properties | BackgroundNeural impairments that follow hemiparetic stroke may negatively affect passive muscle properties, further limiting recovery. However, factors such as hypertonia, spasticity, and botulinum neurotoxin (BoNT), a common clinical intervention, confound our understanding of muscle properties in chronic stroke.
ObjectiveTo determine if muscle passive biomechanical properties are different following prolonged, stroke-induced, altered muscle activation and disuse.
MethodsTorques about the metacarpophalangeal and wrist joints were measured in different joint postures in both limbs of participants with hemiparetic stroke. First, we evaluated 27 participants with no history of BoNT; hand impairments ranged from mild to severe.
Subsequently, seven participants with a history of BoNT injections were evaluated. To mitigate muscle hypertonia, torques were quantified after an extensive stretching protocol and under conditions that encouraged participants to sleep. EMGs were monitored throughout data collection.
ResultsAmong participants who never received BoNT, no significant differences in passive torques between limbs were observed. Among participants who previously received BoNT injections, passive flexion torques about their paretic wrist and finger joints were larger than their nonparetic limb (average interlimb differences = +42.0{+/-}7.6SEM Ncm, +26.9{+/-}3.9SEM Ncm, respectively), and the range of motion for passive finger extension was significantly smaller (average interlimb difference = -36.3{degrees}{+/-}4.5{degrees}SEM; degrees).
ConclusionOur results suggest that neural impairments that follow chronic, hemiparetic stroke do not lead to passive mechanical changes within the wrist and finger muscles. Rather, consistent with animal studies, the data points to potential adverse effects of BoNT on passive muscle properties post-stroke, which warrant further consideration. | rehabilitation medicine and physical therapy |
10.1101/19011221 | Influence of sexual risk behaviour and STI co-infection dynamics on the evolution of HIV set point viral load in MSM. | HIV viral load (VL) is an important predictor of HIV progression and transmission. Anti-retroviral therapy (ART) has been reported to reduce HIV transmission by lowering VL. However, apart from this beneficial effect, increased levels of population mean set-point viral load (SPVL), an estimator for HIV virulence, have been observed in men who have sex with men (MSM) in the decade following the introduction of ART in the Netherlands. Several studies have been devoted to explain these counter-intuitive trends in SPVL. However, to our knowledge, none of these studies has investigated an explanation in which it arises as the result of a sexually transmitted infection (STI) co-factor in detail.
In this study, we adapted an event-based, individual-based model to investigate how STI co-infection and sexual risk behaviour affect the evolution of HIV SPVL in MSM before and after the introduction of ART.
The results suggest that sexual risk behaviour has an effect on SPVL and indicate that more data are needed to test the effect of STI co-factors on SPVL. Furthermore, the observed trends in SPVL cannot be explained by sexual risk behaviour and STI co-factors only.
We recommend to develop mathematical models including also factors related to viral evolution as reported earlier in the literature. However, this requires more complex models, and the collection of more data for parameter estimation than what is currently available. | hiv aids |
10.1101/19013136 | Metagenomic analysis of common intestinal diseases reveals relationships among microbial signatures and powers multi-disease diagnostic models | Common intestinal diseases such as Crohns disease (CD), ulcerative colitis (UC) and colorectal cancer (CRC), share clinical symptoms and altered gut microbes, necessitating cross-disease comparisons and the use of multi-disease models. Here, we performed meta-analyses on thirteen fecal metagenome datasets of the three diseases. We identified 87 species and 65 pathway markers that were consistently changed in multiple datasets of the same diseases. According to their overall trends, we grouped the disease-enriched marker species into disease-specific and -common clusters, and revealed their distinct phylogenetic relationships: species in CD-specific cluster are phylogenetically related, while those in CRC-specific cluster are more distant; strikingly, UC-specific species are phylogenetically closer to CRC, likely because UC-patients have higher risk of CRC. Consistent to their phylogenetic relationships, marker species had similar within-cluster and different between-cluster metabolic preferences. There were part of marker species and pathways correlated with an indicator of leaky gut, suggesting a link between gut dysbiosis and human derived contents. Marker species showed more coordinated changes and tighter inner-connections in cases than the controls, suggesting that the diseased gut may represent a stressed environment and pose stronger selection to gut microbes. With the marker species and pathways, we constructed four high-performance (including multi-disease) models with AUROC of 0.87 and true positive rates up to 90%, and explained their putative clinical applications. We identified consistent microbial alterations in common intestinal diseases, revealed metabolic capacities and the relationships among marker bacteria in distinct states, and supported the feasibility of metagenome-derived multi-disease diagnosis.
ImportanceGut microbes have been identified as potential markers in distinguishing patients from controls in colorectal cancer, ulcerative colitis and Crohns disease individually, whereas there lacks a systematic analysis to investigate the exclusive microbial shifts of these enteropathies with similar clinical symptoms. Our meta-analysis and cross-disease comparisons identified consistent microbial alterations in each enteropathy, revealed microbial ecosystems among marker bacteria in distinct states, and demonstrated the necessity and feasibility of metagenome-based multi-disease classifications. To the best of our knowledge, this is the first study that constructed multi-class models in these common intestinal diseases. | gastroenterology |
10.1101/2019.12.10.19014266 | What is the best evidence for graft choice in ACL reconstruction? Protocol for a systematic review and network meta-analysis. | IntroductionAnterior cruciate ligament (ACL) reconstruction is one of the most commonly performed sports medicine procedures. A variety of grafts are currently used for reconstruction, including both allograft and autograft. Despite numerous meta-analyses, there exists no high-quality quantitative synthesis of all randomized controlled trial (RCT) data on graft choice.
ObjectiveTo identify the optimal graft choice for ACL reconstruction by performing the first systematic review and network meta-analysis (NMA) to include both functional outcomes and complications.
MethodsMultiple digital databases including MEDLINE, Embase, and CENTRAL will be searched independently and in duplicate for RCTs randomizing graft choice in ACL reconstruction in skeletally mature patients. A Bayesian framework with a random-effects model will be used for NMA. Surface under the cumulative ranking curve (SUCRA) values will be used to generate a rank list for each outcome. Results will be reported as mean differences (MD) (or standardized mean difference, if necessary) or relative risk (RR) with 95% credible intervals (CI). Comparisons will be inferred to be statistically significant if the 95% CI of MD does not cross zero or if the 95% CI of relative risk does not cross one. Studies will be assessed for quality using the Cochrane risk of bias assessment tool. Quality of evidence for each network comparison will be determined as per the Grades of Recommendation, Assessment, Development and Evaluation (GRADE) approach for network meta-analyses. This NMA will be reported according to the PRISMA extension statement for network meta-analyses
Outcomes of interestFunctional outcomes of interest including range of motion, return to activity/sport, and IKDC, Lysholm, Tegner, ACL-QOL, and KOOS scores. Persistent laxity as measured by Lachman, Pivot-shift, side-to-side, and measured laxity (e.g. KT-1000) will also be analyzed. Complications (e.g. infection, graft failure, donor site pain), tunnel osteolysis, and failure (including but not limited to graft rupture and/or persistent laxity) will be compared between grafts.
Relevance/ImpactThis NMA will be the first high-quality syntheses of all randomized evidence regarding graft choice in ACL reconstruction. As the first analysis to compare all major graft choices independently, it will be used to inform surgeon-patient decision making. It has the reasonable possibility of changing clinical practice. | orthopedics |
10.1101/2019.12.19.19015255 | Alterations in Brain Morphology by MRI in Adults with Neurofibromatosis 1 | ObjectiveTo characterize alterations in brain morphology by MRI in adults with neurofibromatosis 1 (NF1).
MethodsPlanar (2D) MRI measurements of 29 intracranial structures were compared in 389 adults with NF1 and 112 age- and sex-matched unaffected control subjects. The 2D measurements were correlated to volumetric (3D) brain measurements for 99 of the adults with NF1.
A subset of adults with NF1 (n = 70) was also assessed for clinical severity of NF1 features and neurological problems and received psychometric testing for attention deficits and IQ. Correlation analyses were performed between principal components of the intracranial measurements and clinical and psychometric features of these patients.
ResultsFour of nine corpus callosum measurements were significantly greater in adults with NF1 than in sex- and age-matched controls. All seven brainstem measurements were significantly greater in adults with NF1 than in controls. Increased corpus callosum and brainstem 2D morphology were correlated with increased total white matter volume among the NF1 patients. No robust correlations were observed between the 2D size of these structures and clinical or neuropsychometric assessments.
InterpretationOur findings are consistent with the hypothesis that dysregulation of brain myelin production is an important manifestation of NF1 in adults. | neurology |
10.1101/2019.12.26.19015909 | Accurate and reproducible prediction of ICU readmissions | Readmission in the intensive care unit (ICU) is associated with poor clinical outcomes and high costs. Traditional scoring methods to help clinicians deciding whether a patient is ready for discharge have failed to meet expectations, paving the way for machine learning based approaches. Freely available datasets such as MIMIC-III have served as benchmarking media to compare such tools. We used the OMOP-CDM version of MIMIC-III (MIMIC-OMOP) to train and evaluate a lightweight tree boosting method to predict readmission in ICU at different time points after discharge (3, 7 and 30 days), outperforming existing solutions with an AUROC of 0.805 for 3-days readmission. | intensive care and critical care medicine |
10.1101/2019.12.27.19016006 | Comparison of first trimester dating methods for gestational age estimation and their implication on preterm birth classification in a North Indian cohort | BackgroundDifferent formulae have been developed globally to estimate gestational age (GA) by ultrasonography in the first trimester of pregnancy. In this study, we develop an Indian population-specific dating formula and compare its performance with published formulae. Finally, we evaluate the implications of the choice of dating method on preterm birth (PTB) rate. This studys data was from GARBH-Ini, an ongoing pregnancy cohort of North Indian women to study PTB.
MethodsComparisons between ultrasonography-Hadlock and last menstrual period (LMP) based dating methods were made by studying the distribution of their differences by Bland-Altman analysis. Using data-driven approaches, we removed data outliers more efficiently than by applying clinical parameters. We applied advanced machine learning algorithms to identify relevant features for GA estimation and developed an Indian population-specific formula (Garbhini-GA1) for the first trimester. PTB rates of Garbhini-GA1 and other formulae were compared by estimating sensitivity and accuracy.
ResultsPerformance of Garbhini-GA1 formula, a non-linear function of crown-rump length (CRL), was equivalent to published formulae for estimation of first trimester GA (LoA, - 0.46,0.96 weeks). We found that CRL was the most crucial parameter in estimating GA and no other clinical or socioeconomic covariates contributed to GA estimation. The estimated PTB rate across all the formulae including LMP ranged 11.27 - 16.50% with Garbhini-GA1 estimating the least rate with highest sensitivity and accuracy. While the LMP-based method overestimated GA by three days compared to USG-Hadlock formula; at an individual level, these methods had less than 50% agreement in the classification of PTB.
ConclusionsAn accurate estimation of GA is crucial for the management of PTB. Garbhini-GA1, the first such formula developed in an Indian setting, estimates PTB rates with higher accuracy, especially when compared to commonly used Hadlock formula. Our results reinforce the need to develop population-specific gestational age formulae. | obstetrics and gynecology |
10.1101/2019.12.27.19016006 | Comparison of first trimester dating methods for gestational age estimation and their implication on preterm birth classification in a North Indian cohort | BackgroundDifferent formulae have been developed globally to estimate gestational age (GA) by ultrasonography in the first trimester of pregnancy. In this study, we develop an Indian population-specific dating formula and compare its performance with published formulae. Finally, we evaluate the implications of the choice of dating method on preterm birth (PTB) rate. This studys data was from GARBH-Ini, an ongoing pregnancy cohort of North Indian women to study PTB.
MethodsComparisons between ultrasonography-Hadlock and last menstrual period (LMP) based dating methods were made by studying the distribution of their differences by Bland-Altman analysis. Using data-driven approaches, we removed data outliers more efficiently than by applying clinical parameters. We applied advanced machine learning algorithms to identify relevant features for GA estimation and developed an Indian population-specific formula (Garbhini-GA1) for the first trimester. PTB rates of Garbhini-GA1 and other formulae were compared by estimating sensitivity and accuracy.
ResultsPerformance of Garbhini-GA1 formula, a non-linear function of crown-rump length (CRL), was equivalent to published formulae for estimation of first trimester GA (LoA, - 0.46,0.96 weeks). We found that CRL was the most crucial parameter in estimating GA and no other clinical or socioeconomic covariates contributed to GA estimation. The estimated PTB rate across all the formulae including LMP ranged 11.27 - 16.50% with Garbhini-GA1 estimating the least rate with highest sensitivity and accuracy. While the LMP-based method overestimated GA by three days compared to USG-Hadlock formula; at an individual level, these methods had less than 50% agreement in the classification of PTB.
ConclusionsAn accurate estimation of GA is crucial for the management of PTB. Garbhini-GA1, the first such formula developed in an Indian setting, estimates PTB rates with higher accuracy, especially when compared to commonly used Hadlock formula. Our results reinforce the need to develop population-specific gestational age formulae. | obstetrics and gynecology |
10.1101/2020.01.17.20017939 | Assessing Knowledge, Attitudes, and Practices towards Causal Directed Acyclic Graphs among Epidemiologists and Medical Researchers: a qualitative research project | BackgroundCausal graphs provide a key tool for optimizing the validity of causal effect estimates. Although a large literature exists on the mathematical theory underlying the use of causal graphs, less literature exists to aid applied researchers in understanding how best to develop and use causal graphs in their research projects.
MethodsWe sought to understand why researchers do or do not regularly use DAGs by surveying practicing epidemiologists and medical researchers on their knowledge, level of interest, attitudes, and practices towards the use of causal graphs in applied epidemiology and health research. We used Twitter and the Society for Epidemiologic Research to disseminate the survey.
ResultsOverall, a majority of participants reported being comfortable with using causal graphs and reported using them sometimes, often, or always in their research. Having received training appeared to improve comprehension of the assumptions displayed in causal graphs. Many of the respondents who did not use causal graphs reported lack of knowledge as a barrier to using DAGs in their research.
ConclusionCausal graphs are of interest to epidemiologists and medical researchers, but there are several barriers to their uptake. Additional training and clearer guidance are needed. In addition, methodological developments regarding visualization of effect measure modification and interaction on causal graphs is needed. | epidemiology |
10.1101/2020.01.17.20017897 | Implicit and explicit motor learning interventions for gait in people after stroke: a process evaluation of a randomized controlled trial | BackgroundGait training within stroke rehabilitation can be applied using implicit or explicit motor learning approaches. Explicit learning is a more conscious approach to learning, in which many detailed instructions about the movement are provided to the learner. Implicit learning strives to take place in a more automatic manner, without much knowledge of the underlying facts and rules of the movement.
ObjectiveTo evaluate whether the implicit and explicit motor learning walking interventions for people after stroke delivered in a randomized controlled trial were performed as intended (fidelity) and to report the therapist and participant experiences with regard to feasibility.
MethodsFidelity was assessed by evaluating the dose delivered (number of therapy sessions) and content of instructions (explicit rules) that were collected through the therapist logs and audio recordings of the training sessions. The therapist and participant experiences were assessed by means of self-developed questionnaires.
Results79 people were included of which seven people (9%) dropped out. The remaining participants all received the required minimum of seven sessions. Overall therapists adhered to the intervention guideline. On average 5.2 and 0.4 explicit rules were used within the explicit and implicit group respectively. Therapists and participants were generally positive about the feasibility but frequent comments were made by the therapists regarding "therapy time restrictions" and "tendency of the participants to develop explicit rules".
ConclusionDelivery of the implicit and explicit motor learning walking interventions were successful in terms of fidelity. Therapists and participants were generally positive about the feasibility of the intervention. | rehabilitation medicine and physical therapy |
10.1101/2020.01.22.20018408 | miRNA biomarkers for diagnosis of ALS and FTD, developed by a nonlinear machine learning approach | The neurodegenerative disorders amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) reside on a clinical and pathological continuum. Heterogeneity in clinical presentation too often delays clinical diagnosis and calls for molecular biomarkers to assist diagnosis, including cell free microRNAs (miRNA). However, nonlinearity in the relationship of miRNAs to clinical states and underpowered cohorts has limited research in this domain. Here, we prospectively enrolled a large cohort of 495 subjects with ALS (n=202) and FTD (n=168), or non-neurodegenerative controls (n=125). Based on cell-free plasma miRNA profiling by next generation sequencing and machine learning approaches, we develop nonlinear prediction models that accurately distinguish ALS and FTD from non-neurodegenerative controls in [~]90% of cases. Among the miRNAs that contribute to classifying disease, we identified miRNAs shared between conditions as well as disease-specific miRNAs. The fascinating potential of diagnostic miRNA biomarkers might enable early-stage detection and a cost-effective screening approach for clinical trials that can facilitate drug development. | neurology |
10.1101/2020.01.22.20018408 | miRNA biomarkers for diagnosis of ALS and FTD, developed by a nonlinear machine learning approach | The neurodegenerative disorders amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) reside on a clinical and pathological continuum. Heterogeneity in clinical presentation too often delays clinical diagnosis and calls for molecular biomarkers to assist diagnosis, including cell free microRNAs (miRNA). However, nonlinearity in the relationship of miRNAs to clinical states and underpowered cohorts has limited research in this domain. Here, we prospectively enrolled a large cohort of 495 subjects with ALS (n=202) and FTD (n=168), or non-neurodegenerative controls (n=125). Based on cell-free plasma miRNA profiling by next generation sequencing and machine learning approaches, we develop nonlinear prediction models that accurately distinguish ALS and FTD from non-neurodegenerative controls in [~]90% of cases. Among the miRNAs that contribute to classifying disease, we identified miRNAs shared between conditions as well as disease-specific miRNAs. The fascinating potential of diagnostic miRNA biomarkers might enable early-stage detection and a cost-effective screening approach for clinical trials that can facilitate drug development. | neurology |
10.1101/2020.01.23.20018523 | Integrated genomics identify novel immunotherapy targets for malignant mesothelioma | BackgroundMalignant pleural mesothelioma (MPM) is an aggressive malignancy with limited effective therapies.
MethodsIn order to identify therapeutic targets, we integrated SNP genotyping, sequencing and transcriptomics from tumours and low-passage patient-derived cells.
ResultsPreviously unrecognised losses of SUFU locus (10q24.32), observed in 21% of 118 tumours, resulted in disordered expression of transcripts from Hedgehog pathways and the T-cell synapse including VISTA. Co-deletion of Interferon Type I genes and CDKN2A was present in half of tumours and was a predictor of poor survival. We also found previously unrecognised deletions in RB1 in 26% of cases and show sub-micromolar responses to downstream PLK1, CHEK1 and Aurora Kinase inhibitors in primary MPM cells. Defects in Hippo pathways that included RASSF7 amplification and NF2 or LATS1/2 mutations were present in 50% of tumours and were accompanied by micromolar responses to the YAP1 inhibitor Verteporfin.
ConclusionsOur results suggest new therapeutic avenues in MPM and provide targets and biomarkers for immunotherapy. | oncology |
10.1101/2020.01.25.20016832 | Two-stage biologically interpretable neural-network models for liver cancer prognosis prediction using histopathology and transcriptomic data | PurposePathological images are easily accessible data with the potential as prognostic biomarkers. Moreover, integration of heterogeneous data types from multi-modality, such as pathological image and gene expression data, is invaluable to help predicting cancer patient survival. However, the analytical challenges are significant.
Experimental DesignHere we take the hepatocellular carcinoma (HCC) pathological image features extracted by CellProfiler, and apply them as the input for Cox-nnet, a neural network-based prognosis. We compare this model with conventional Cox-PH model, CoxBoost, Random Survival Forests and DeepSurv, using C-index and log ranked p-values on HCC testing samples. Further, to integrate pathological image and gene expression data of the same patients, we innovatively construct a two-stage Cox-nnet model, and compare it with another complex neural network model PAGE-Net.
Resultspathological image based prognosis prediction using Cox-nnet is significantly more accurate than Cox-PH and random survival forests models, and comparable with CoxBoost and DeepSurv methods. Additionally, the two-stage Cox-nnet complex model combining histopathology image and transcriptomics RNA-Seq data achieves better prognosis prediction, with a median C-index of 0.75 and log-rank p-value of 6e-7 in the testing datasets. The results are much more accurate than PAGE-Net, a CNN based complex model (median C-index of 0.68 and log-rank p-value of 0.03). Imaging features present additional predictive information to gene expression features, as the combined model is much more accurate than the model with gene expression alone (median C-index 0.70). Pathological image features are modestly correlated with gene expression. Genes having correlations to top imaging features have known associations with HCC patient survival and morphogenesis of liver tissue.
ConclusionThis work provides two-stage Cox-nnet, a new class of biologically relevant and relatively interpretable models, to integrate multi-modal and multiple types of data for survival prediction. | genetic and genomic medicine |
10.1101/2020.01.27.20018929 | Simultaneous estimation of bi-directional causal effects and heritable confounding from GWAS summary statistics | Mendelian Randomisation (MR), an increasingly popular method that estimates the causal effects of risk factors on complex human traits, has seen several extensions that relax its basic assumptions. However, most of these extensions suffer from two major limitations; their under-exploitation of genome-wide markers, and sensitivity to the presence of a heritable confounder of the exposure-outcome relationship. To overcome these limitations, we propose a Latent Heritable Confounder MR (LHC-MR) method applicable to association summary statistics, which estimates bi-directional causal effects, direct heritabilities, and confounder effects while accounting for sample overlap. We demonstrate that LHC-MR out-performs several existing MR methods in a wide range of simulation settings and apply it to summary statistics of 13 complex traits. Besides several concordant results, LHC-MR unravelled new mechanisms (how being diagnosed for certain diseases might lead to improved lifestyle) and revealed new causal effects (e.g. HDL cholesterol being protective against high systolic blood pressure), hidden from standard MR methods due to a heritable confounder of opposite direction. Phenome-wide MR search suggested that the confounders indicated by LHC-MR for the birth weight-diabetes pair are likely to be obesity traits. Finally, LHC-MR results indicated that genetic correlations are predominantly driven by bi-directional causal effects and much less so by heritable confounders. | genetic and genomic medicine |
10.1101/2020.01.27.20019091 | Artificial Intelligence Assisted Early Warning System for Acute Kidney Injury Driven by Multi-Center ICU Database | BackgroundTo improve the performance of early acute kidney injury (AKI) prediction in intensive care unit (ICU), we developed and externally validated machine learning algorithms in two large ICU databases.
MethodsUsing eICU(R) Collaborative Research Database (eICU) and MIMIC-III databases, we selected all adult patients (age [≥] 18). The detection of AKI was based on both the oliguric and serum creatinine criteria of the KDIGO (Kidney Disease Improving Global Outcomes). We developed an early warning system for forecasting the onset of AKI within the first week of ICU stay, by using 6- or 12-hours as the data extraction window and make a prediction within a 1-hour window after a gap window of 6- or 12-hours. We used 52 features which are routinely available ICU data as predictors. eICU was used for model development, and MIMIC-III was used for externally validation. We applied and experimented on eight machine learning algorithms for the prediction task.
Results3,816 unique admissions in multi-center eICU database were selected for model development, and 5,975 unique admissions in single-center MIMIC-III database were selected for external validation. The incidence of AKI within the first week of ICU stay in eICU and MIMIC-III cohorts was 52.1% (n=1,988) and 31.3% (n=1,870), respectively. In eICU cohort, the performance of AKI prediction is better with shorter extraction window and gap window. We found that the AdaBoost algorithm yielded the highest AUC (0.8859) on the model with 6-hours data extraction window and 6-hours gap window (model 6-6) rather than other prediction models. In MIMIC-III cohort, AdaBoost also performed well.
ConclusionsWe developed the machine learning-based early AKI prediction model, which considered clinical important features and has been validated in two datasets. | intensive care and critical care medicine |
10.1101/2020.02.04.20019380 | Differential vulnerability of the cerebellum in healthy ageing and Alzheimer's disease | Recent findings challenge the prior notion that the cerebellum remains unaffected by Alzheimers disease (AD). Yet, it is unclear whether AD exacerbates age-related cerebellar grey matter decline or engages distinct structural and functional territories. We performed a meta-analysis of cerebellar grey matter loss in normal ageing and AD. We mapped voxels with structural decline onto established brain networks, functional parcellations, and along gradients that govern the functional organisation of the cerebellum. Importantly, these gradients track continuous changes in cerebellar specialisation providing a more nuanced measure of the functional profile of regions vulnerable to ageing and AD. Gradient 1 progresses from motor to cognitive territories; Gradient 2 isolates attentional processing; Gradient 3 captures lateralisation differences in cognitive functions. We identified bilateral and right-lateralised posterior cerebellar atrophy in ageing and AD, respectively. Age- and AD- related structural decline only showed partial spatial overlap in right lobule VI/Crus I. Despite the seemingly distinct patterns of AD- and age-related atrophy, the functional profiles of these regions were similar. Both participate in the same macroscale networks (default mode, frontoparietal, attention), support executive functions and language processing, and did not exhibit a difference in relative positions along Gradients 1 or 2. However, Gradient 3 values were significantly different in ageing vs. AD, suggesting that the roles of left and right atrophied cerebellar regions exhibit subtle functional differences despite their membership in similar macroscale networks. These findings provide an unprecedented characterisation of structural and functional differences and similarities in cerebellar grey matter loss between normal ageing and AD. | neurology |
10.1101/2020.02.04.20020404 | Distinguishing Viruses Responsible for Influenza-Like Illness | The many respiratory viruses that cause influenza-like illness (ILI) are reported and tracked as one entity, defined by the CDC as a group of symptoms that include a fever of 100 degrees Fahrenheit and a cough and/or a sore throat. In the United States alone, ILI impacts 9-49 million people every year. While tracking ILI as a single clinical syndrome is informative in many respects, the underlying viruses differ in their parameters and outbreak properties. Most existing models treat either a single respiratory virus or ILI as a whole. However, there is a need for models capable of comparing several individual ILI viruses. To address this need, here we present a flexible model and simulations of epidemics for influenza, RSV, rhinovirus, seasonal coronavirus, adenovirus, and SARS/MERS, parameterized by a systematic literature review and accompanied by a global sensitivity analysis. We find that for these biological causes of ILI, their parameter values, timing, prevalence, and proportional contributions differ substantially. These results demonstrate that distinguishing the viruses that cause influenza-like illness will be an important aspect of future work on ILI diagnostics, mitigation, modeling, and preparation for future unknown pandemics. | epidemiology |
10.1101/2020.02.08.20021311 | Assessing the plausibility of supercritical transmission for an emerging or re-emerging pathogen | Rapid assessment of the transmission potential of an emerging or reemerging pathogen is a cornerstone of public health response. A simple approach is shown for using the number of disease introductions and secondary cases to determine whether the upper bound of the reproduction number exceeds the critical value of one. | epidemiology |
10.1101/2020.02.13.20022475 | Evaluating quality improvement at scale: routine reporting for executive board governance in a UK National Health Service organisation | PurposeQuality improvement (QI) in healthcare is a cultural transformation process that requires long-term commitment from the executive board. As such, an overview of QI applications and their impact needs to be made routinely visible. We explored how routine reporting could be developed for QI governance.
DesignWe developed a retrospective evaluation of QI projects in an NHS healthcare organisation. The evaluation was conducted as an online survey so that the data accrual process resembled routine reporting to help identify implementation challenges. A purposive sample of QI projects was identified to maximise contrast between projects that were or were not successful as determined by the resident QI team. To hone strategic focus in what should be reported, we also compared factors that might affect project outcomes.
FindingsOut of 52 QI projects, 10 led to a change in routine practice ( adoption). Details of project outcomes were limited. Project team outcomes, indicative of capacity building, were not systematically documented. Service user involvement, quality of measurement plan, fidelity of plan-do-study-act (PDSA) cycles had a major impact on adoption. We discussed how routine visibility of these factors may aid QI governance.
OriginalityDesigning a routine reporting framework is an iterative process involving continual dialogue with frontline staff and improvement specialists to navigate data accrual demands. We demonstrated how a retrospective evaluation, as in this study, can yield empirical insights to support dialogue around QI governance, thereby honing the implementation science of QI in a healthcare organisation. | health systems and quality improvement |
10.1101/2020.02.17.20021949 | Auditory tests for characterizing hearing deficits in listeners with various hearing abilities: The BEAR test battery | The Better hEAring Rehabilitation (BEAR) project aims to provide a new clinical profiling tool - a test battery - for hearing loss characterization. Whereas the loss of sensitivity can be efficiently measured using pure-tone audiometry, the assessment of supra-threshold hearing deficits remains a challenge. In contrast to the classical attenuation-distortion model, the proposed BEAR approach is based on the hypothesis that the hearing abilities of a given listener can be characterized along two dimensions, reflecting independent types of perceptual deficits (distortions). A data-driven approach provided evidence for the existence of different auditory profiles with different degrees of distortions. Ten tests were included in a test battery, based on their clinical feasibility, time efficiency and related evidence from the literature. The tests were divided into six categories: audibility, speech perception, binaural processing abilities, loudness perception, spectro-temporal modulation sensitivity and spectro-temporal resolution. Seventy-five listeners with symmetric, mild-to-severe sensorineural hearing loss were selected from a clinical population. The analysis of the results showed interrelations among outcomes related to high-frequency processing and outcome measures related to low-frequency processing abilities. The results showed the ability of the tests to reveal differences among individuals and their potential use in clinical settings. | otolaryngology |
10.1101/2020.02.18.20024653 | Return to play after treating acute muscle injuries in elite football players with a multimodal therapy approach that includes a specific protocol of (almost) daily radial extracorporeal shock wave therapy | AimTo compare lay-off times achieved by treating acute muscle injuries in elite football players with a multimodal therapy approach that includes a specific protocol of almost daily radial extracorporeal shock wave therapy (rESWT)) with corresponding data reported in the literature.
MethodsWe performed a retrospective analysis of treatments and recovery times of muscle injuries suffered by the players of an elite football team competing in the first/second German Bundesliga during a previous season.
ResultsA total of 20 acute muscle injuries were investigated in the aforementioned season, of which eight (40%) were diagnosed as type 1a/muscular tightness injuries, five (25%) as type 2b/muscle strain injuries, four (20%) as type 3a/partial muscle tear injuries and three (15%) as contusions. All injuries were treated with the previously mentioned multimodal therapy approach. Compared with data reported by Ekstrand et al. (Br J Sports Med 2013;47:769-774), lay-off times (median / mean) were shortened by 54% and 58% respectively in the case of type 1a injuries, by 50% and 55% respectively in the case of type 2b injuries as well as by 8% and 21% respectively in the case of type 3a injuries. No adverse reactions were observed.
ConclusionsOverall, the multimodal therapy approach investigated in this study is a safe and effective treatment approach for treating type 1a and 2b acute muscle injuries amongst elite football players and may help to prevent more severe, structural muscle injuries.
What are the findings?[tpltrtarr] By treating acute muscle injuries suffered by the players of an elite football team competing in the first/second German Bundesliga during a previous season with a multimodal therapy approach (comprising cryotherapy, compression, manual therapy, resistance/weight-training, a progressive physiotherapy exercise programme and a specific protocol of (almost) daily radial extracorporeal shock wave therapy (rESWT)) we achieved median and mean lay-off times after type 1a (muscular tightness/hypertonicity) and 2b (muscular strain injury) muscle injuries that were 50% shorter than corresponding data reported in the literature (Ekstrand et al., Brit J Sports Med 2013;47:769-774).
[tpltrtarr]The percentage of structural muscle injuries, specifically type 3 (partial muscle tear according to the Muller-Wohlfahrt/Munich muscle injury classification) and type 4 (complete muscle tear and/or avulsion injury involving the tendon) amongst this sample group of players (including injury types 1-4 as classified by Muller-Wohlfahrt et al; and excluding contusions) that occurred during the entire season comprised 23.5% of all the muscle injuries suffered. In comparison, the percentage of structural muscle injuries amongst similar sample groups of elite football players has been found to be considerably higher - in the data set reported by Ekstrand et al. (2013) higher grade structural muscle injuries amongst elite European football teams typically make up 66.9% of all muscle injuries suffered during the course of one season.
How might it impact on clinical practice in the future?Our findings emphasise the effective use of a multimodal therapy approach (comprising cryotherapy, compression, manual therapy, resistance/weight-training, a progressive physiotherapy exercise programme and a specific protocol of (almost) daily rESWT for substantially shortening lay-off times associated with functional/ultrastructural muscle injuries and possibly for preventing more severe structural muscle injuries amongst sportspeople. | sports medicine |
10.1101/2020.02.18.20024554 | Is migraine associated to brain anatomical alterations? New data and coordinate-based meta-analysis. | A growing number of studies investigate brain anatomy in migraine using voxel-(VBM) and surface-based morphometry (SBM), as well as diffusion tensor imaging (DTI). The purpose of this article is to identify consistent patterns of anatomical alterations associated with migraine. First, 19 migraineurs without aura and 19 healthy participants were included in a brain imaging study. T1-weighted MRIs and DTI sequences were acquired and analyzed using VBM, SBM and tract-based spatial statistics. No significant alterations of gray matter (GM) volume, cortical thickness, cortical gyrification, sulcus depth and white-matter tract integrity could be observed. However, migraineurs displayed decreased white matter (WM) volume in the left superior longitudinal fasciculus. Second, a systematic review of the literature employing VBM, SBM and DTI was conducted to investigate brain anatomy in migraine. Meta-analysis was performed using Seed-based d Mapping via permutation of subject images (SDM-PSI) on GM volume, WM volume and cortical thickness data. Alterations of GM volume, WM volume, cortical thickness or white-matter tract integrity were reported in 72%, 50%, 56% and 33% of published studies respectively. Spatial distribution and direction of the disclosed effects were highly inconsistent across studies. The SDM-PSI analysis revealed neither significant decrease nor significant increase of GM volume, WM volume or cortical thickness in migraine. Overall there is to this day no strong evidence of specific brain anatomical alterations reliably associated to migraine. Possible explanations of this conflicting literature are discussed.
Trial registration numberNCT02791997, registrated February 6th, 2015. | neurology |
10.1101/2020.02.20.20025528 | Estimating population level disease prevalence using genetic risk scores | Clinical classification is essential for estimating disease prevalence but is difficult, often requiring complex investigations. The widespread availability of population level genetic data makes novel genetic stratification techniques a highly attractive alternative. We propose a generalizable mathematical framework for determining disease prevalence within a cohort using genetic risk scores. We compare and evaluate methods based on the means of genetic risk scores distributions; the Earth Movers Distance between distributions; a linear combination of kernel density estimates of distributions; and an Excess method. We demonstrate the performance of genetic stratification to produce robust prevalence estimates. Specifically, we show that robust estimates of prevalence are still possible even with rarer diseases, smaller cohort sizes and less discriminative genetic risk scores, highlighting the general utility of these approaches. Genetic stratification techniques offer exciting new research tools, enabling unbiased insights into disease prevalence and clinical characteristics unhampered by clinical classification criteria. | genetic and genomic medicine |
10.1101/2020.02.20.20025528 | Estimating population level disease prevalence using genetic risk scores | Clinical classification is essential for estimating disease prevalence but is difficult, often requiring complex investigations. The widespread availability of population level genetic data makes novel genetic stratification techniques a highly attractive alternative. We propose a generalizable mathematical framework for determining disease prevalence within a cohort using genetic risk scores. We compare and evaluate methods based on the means of genetic risk scores distributions; the Earth Movers Distance between distributions; a linear combination of kernel density estimates of distributions; and an Excess method. We demonstrate the performance of genetic stratification to produce robust prevalence estimates. Specifically, we show that robust estimates of prevalence are still possible even with rarer diseases, smaller cohort sizes and less discriminative genetic risk scores, highlighting the general utility of these approaches. Genetic stratification techniques offer exciting new research tools, enabling unbiased insights into disease prevalence and clinical characteristics unhampered by clinical classification criteria. | genetic and genomic medicine |
10.1101/2020.02.20.20025528 | Estimating population level disease prevalence using genetic risk scores | Clinical classification is essential for estimating disease prevalence but is difficult, often requiring complex investigations. The widespread availability of population level genetic data makes novel genetic stratification techniques a highly attractive alternative. We propose a generalizable mathematical framework for determining disease prevalence within a cohort using genetic risk scores. We compare and evaluate methods based on the means of genetic risk scores distributions; the Earth Movers Distance between distributions; a linear combination of kernel density estimates of distributions; and an Excess method. We demonstrate the performance of genetic stratification to produce robust prevalence estimates. Specifically, we show that robust estimates of prevalence are still possible even with rarer diseases, smaller cohort sizes and less discriminative genetic risk scores, highlighting the general utility of these approaches. Genetic stratification techniques offer exciting new research tools, enabling unbiased insights into disease prevalence and clinical characteristics unhampered by clinical classification criteria. | genetic and genomic medicine |
10.1101/2020.02.26.20028274 | Testing the association between tobacco and cannabis use and cognitive functioning: Findings from an observational and Mendelian randomization study | BackgroundAlthough studies have examined the association between tobacco and cannabis use in adolescence with subsequent cognitive functioning, study designs are usually not able to distinguish correlation from causation.
MethodsSeparate patterns of tobacco and cannabis use were derived using longitudinal latent class analysis based on measures assessed on five occasions from age 13 to 18 in a large UK population cohort (ALSPAC). Cognitive functioning measures comprised of working memory, response inhibition, and emotion recognition assessed at 24 years of age. Mendelian randomization was used to examine the possible causal relationship.
ResultsWe found evidence of a relationship between tobacco and cannabis use and diminished cognitive functioning for each of the outcomes in the observational analyses. There was evidence to suggest that late-onset regular tobacco smokers (b=-0.29, 95%CI=-0.45 to -0.13), early-onset regular tobacco smokers (b=-0.45, 95%CI=-0.84 to -0.05), and early-onset regular cannabis users (b=-0.62, 95%CI=-0.93 to -0.31) showed poorer working memory. Early-onset regular tobacco smokers (b=0.18, 95%CI=0.07 to 0.28), and early-onset regular cannabis users (b=0.30, 95%CI=0.08 to 0.52) displayed poorer ability to inhibit responses. Late-onset regular (b=-0.02, 95%CI=-0.03 to -0.00), and early-onset regular tobacco smokers (b=-0.04, 95%CI=-0.08 to -0.01) showed poorer ability to recognise emotions. Mendelian randomization analyses were imprecise and did not provide additional support for the observational results.
ConclusionThere was some evidence to suggest that adolescent tobacco and cannabis use were associated with deficits in working memory, response inhibition and emotion recognition. Better powered genetic studies are required to determine whether these associations are causal. | epidemiology |
10.1101/2020.03.01.20029660 | The long-term impact on health status from lower limb apophysitis: Protocol of a cross-sectional study | Lower limb apophysitis cause long-term pain, decrease in function, and can reduce or completely hinder participation in sports and physical activity. Yet, there is little knowledge on the long-term consequences for health. Our objective with this investigation is to capture self-reported health-status for all adults diagnosed with lower limb apophysitis in the period of 1977 to 2020 in Danish secondary care and compare these data with normative values for the background population. We are therefore conducting a national cross-sectional study based on data from the Danish National Patient Registry. In this protocol we describe the planned methods. | orthopedics |
10.1101/2020.03.06.20032235 | Have associations between mental health and health related behaviours changed between 2005 and 2015? A population based cross-cohort study | Background Adolescent mental ill-health is a growing concern. There is little understanding of changes over time in the associations between mental health and health-related behaviours and outcomes such as substance use, anti-social behaviour and obesity. We investigate whether the associations between different health-related outcomes in adolescence are changing over time in two recent cohorts of adolescents born ten years apart. Methods Data from two UK birth cohort studies, the Avon Longitudinal Study of Parents and Children (ALSPAC, born 1991-92, N=5627, 50.7% female) and Millennium Cohort Study (MCS, born 2000-2, N=11318, 50.6% female) at age 14 sweeps are used. The health outcomes of focus are depressive symptom score, substance use (alcohol, smoking, cannabis and other drugs), antisocial behaviours (assault, graffiti, vandalism, shoplifting and rowdy behaviour), weight (BMI), weight perception (perceive self as overweight) and sexual activity (had sexual intercourse). Regression analyses are conducted to examine associations between these variables with cohort as a moderator to examine cohort differences. Results The directions of associations between mental-health and health-related behaviours (eg smoking) are similar over time, however, their strength across the distribution has changed. While smoking and alcohol use behaviours are decreasing in adolescents, those that endorse these behaviours in 2015 are more likely to have co-occurring mental-health than those born in 2005. Similarly, higher BMI is more strongly associated with depressive symptoms in 2015 compared to 2005. Conclusions Adverse health-related outcomes such as greater substance use, mental health difficulties and higher BMI appear to be more likely to cluster together in the more recent cohort, with implications for public health planning, service provision and lifelong disease burden. | epidemiology |
10.1101/2020.03.05.20031617 | Which assessments are used to analyze neuromuscular control after an anterior cruciate ligament injury to determine readiness to return to sports?A systematic review. | BackgroundAdequate neuromuscular control of the knee could be one element to prevent secondary injuries after an anterior cruciate ligament (ACL) injury. To assess neuromuscular control in terms of time, amplitude and activity, electromyography (EMG) is used. However, it is unclear which assessments using EMG could be used for a safe return to sports (RTS). Therefore, we aimed to summarize EMG-related assessments for neuromuscular control of the knee in adult patients after an ACL injury to decide upon readiness for RTS.
MethodsThis systematic review followed guidelines of Preferred Reporting of Items for Systematic Reviews and Meta-Analyses (PRISMA) and Cochrane recommendations. MEDLINE/PubMed, EMBASE, CINAHL, Cochrane Library, Physiotherapy Evidence Database (PEDro), SPORTDiscus and the Web of Science were searched from inception to March 2019 and updated in November 2020. Studies identifying electromyographic assessments for neuromuscular control during dynamic tasks in adult, physically active patients with an anterior cruciate ligament injury were eligible and qualitatively synthesized. Two independent reviewers used a modified Downs and Black checklist to assess risk of bias of included studies.
ResultsFrom initially 1388 hits, 38 mainly cross-sectional, case-controlled studies were included for qualitative analysis. Most studies provided EMG outcomes of thigh muscles during jumping, running or squatting. Outcomes measures described neuromuscular control of the knee in domains of time, amplitude or activity. Risk of bias was medium to high due to an unclear description of participants and prior interventions, confounding factors and incompletely reported results.
ConclusionsDespite a wide range of EMG outcome measures for neuromuscular control, none was used to decide upon return to sports in these patients. Additional studies are needed to define readiness towards RTS by assessing neuromuscular control in adult ACL patients with EMG. Further research should aim at finding reliable and valid, EMG-related variables to be used as diagnostic tool for neuromuscular control. Moreover, future studies should aim at more homogenous groups including adequately matched healthy subjects, evaluate gender separately and use sport-specific tasks.
RegistrationThe protocol for this systematic review was indexed beforehand in the International Prospective Register of Systematic Reviews (PROSPERO) and registered as CRD42019122188. | rehabilitation medicine and physical therapy |
10.1101/2020.03.06.20032425 | Prevalence and Risk Factors for Acute Posttraumatic Stress Disorder during the COVID-19 Outbreak | BackgroundTo exam the prevalence of and risk factors for acute posttraumatic stress disorder (PTSD) in Chinese people shortly after the COVID-19 outbreak.
MethodsAn online questionnaire survey was conducted between 30 January and 3 February, 2020. The survey included two self-administered questionnaires: one was designed to require participants personal information (gender, age, education background), current location, recent epidemic area contact history, the classification of population, and subjective sleep quality; the other was the PTSD Checklist for DSM-5 (PCL-5).
ResultsA total of 2091 Chinese participated in this study. The prevalence of PTSD among the Chinese public one month after the COVID-19 outbreak was 4.6%. Multiple linear regression analysis revealed that gender (p < 0.001), epidemic area contact history (p = 0.047), classification of population (p < 0.001), and subjective sleep quality (p < 0.001) could be regarded as predictor factors for PTSD.
LimitationsFirst, the majority of participants in this study were the general public, and confirmed or suspected patients being a small part. Second, the measurement of PTSD might be vulnerable to selection bias because of an online self-report study, such as participants recruitment. Third, the prevalence of PTSD in this study was estimated by an online questionnaire rather than a clinical interview.
ConclusionsThe results revealed that some Chinese showed acute PTSD during the COVID-19 outbreak. Therefore, comprehensive psychological intervention needs further implementation. Furthermore, females, people who having recent epidemic area contact history, those at high risk of infection or with poor sleep quality deserve special attention. | psychiatry and clinical psychology |
10.1101/2020.03.13.20035436 | Clinical Characteristics and Durations of Hospitalized Patients With COVID-19 in Beijing: A Retrospective Cohort Study | ObjectiveTo give the information on clinical characteristics and different durations of COVID-19 and to identify the potential risk factors for longer hospitalization duration.
MethodsIn this retrospective study, we enrolled 77 patients (mean age: 52{+/-}20 years; 44.2% males) with laboratory-confirmed COVID-19 admitted to Beijing YouAn Hospital during 21st Jan and 8th February 2020. Epidemiological, clinical, and radiological data on admission were collected; complications and outcomes were followed up until 26th February 2020. The studys endpoint was the discharge within two weeks. Cox proportional-hazards regression was performed to identify risk factors for longer hospitalization duration.
ResultsOf 77 patients, there were 34 (44.2%) males, 24 (31.2%) with comorbidities, 22 (28.6%) lymphopenia, 20 (26.0%) categorized as severe patients, and 28 (36.4%) occurred complications. By the end of follow-up, 64 (83.1%) patients were discharged home, 8 remained in hospital and 5 died. 36 (46.8%) patients were discharged within 14 days and thus reached the study endpoint, including 34 (59.6%) of 57 non-severe patients and 2 (10%) of 20 severe patients. The overall cumulative probability of the endpoint was 48.3%. Hospital length of stay and duration of exposure to discharge for 64 discharged patients were 13 (10-16.5) and 23 (18-24.5) days, respectively. Multivariable stepwise Cox regression model showed that bilateral pneumonia on CT scan, shorter time from the illness onset to admission, severity of disease and lymphopenia were independently associated with longer duration of hospitalization.
ConclusionsCOVID-19 has significantly shorter duration of disease and hospital length of stay than SARS. Bilateral pneumonia on CT scan, shorter period of illness onset to admission, lymphopenia, severity of disease are the risk factors for longer hospitalization duration of COVID-19.
Significance StatementIn this study, we reported that the average hospital length of stay for discharged patients with COVID-19 is 13 days and the average time of clinical course of COVID-19 is 23 days, both of which are significantly shorter than that of SARS. The risk factors for longer hospitalization duration of COVID-19 include bilateral pneumonia on CT scan, shorter period of illness onset to admission, lymphopenia, and severity of disease. There findings might be helpful for the countries or territories facing the threat of COVID-19 to well prepare and rebalance their medical resources. | infectious diseases |
10.1101/2020.03.16.20036913 | Assessment of menstrual hygiene practice and associated factor among High school female students in Harar Eastern Ethiopia 2019 | BackgroundMenstruation is a visible manifestation of cyclic uterine bleeding as a result of the interaction of different hormones. During menstruation, girls face gender problems. These are, early marriage, premature childbirth, higher infant mortality and potential vaginal infections resulting in infertility.
ObjectiveTo assess the level of menstrual hygiene practice and associated factors among high school female students in Harari Region Eastern, Ethiopia, 2019.
Study Design and MethodA cross-sectional quantitative study was employed from April 02-05/2019. A minimum sample size of 301 Data was collected using a self-administered structured questionnaire. Descriptive and analytical facts were applied. Bivariate analysis and multivariate regression model were used. P-value <= 0.05 was declared as statistical significance
ResultAccording to study 168(55.8%) had good practiced the rest had no. students who have no pocket money from family(AOR 0.36:95% CI,0.309,0.989) was 64% less likely poor practiced than students who have permanent pocket money, students who have no educated father(AOR 0.39:95% CI, 0.180,0.872) was 61% less likely poor practiced than who have educated father and students who had not Freely discuss with parents(AOR 0.45:95% CI,0.22,0.903) was 55% less likely poor practiced than who had Freely discuss with parents.
ConclusionMajority of female students in Harar region had good knowledge about menstrual hygiene practice. good menstrual hygiene practice was more among students who live in the urban than students who live in the rural area; students who have permanent pocket money from family than students who have no permanent pocket money from family. | sexual and reproductive health |
10.1101/2020.03.19.20039099 | A Novel Triage Tool of Artificial Intelligence Assisted Diagnosis Aid System for Suspected COVID-19 pneumonia In Fever Clinics | BackgroundCurrently, the prevention and control of the novel coronavirus disease (COVID-19) outside Hubei province in China, and other countries have become more and more critically serious. We developed and validated a diagnosis aid model without computed tomography (CT) images for early identification of suspected COVID-19 pneumonia (S-COVID-19-P) on admission in adult fever patients and made the validated model available via an online triage calculator.
MethodsPatients admitted from Jan 14 to February 26, 2020 with the epidemiological history of exposure to COVID-19 were included [Model development (n = 132) and validation (n = 32)]. Candidate features included clinical symptoms, routine laboratory tests, and other clinical information on admission. Features selection and model development were based on the least absolute shrinkage and selection operator (LASSO) regression. The primary outcome was the development and validation of a diagnostic aid model for S-COVID-19-P early identification on admission.
ResultsThe development cohort contained 26 S-COVID-19-P and 7 confirmed COVID-19 pneumonia cases. The final selected features included 1 variable of demographic information, 4 variables of vital signs, 5 variables of blood routine values, 7 variables of clinical signs and symptoms, and 1 infection-related biomarker. The model performance in the testing set and the validation cohort resulted in the area under the receiver operating characteristic (ROC) curves (AUCs) of 0.841 and 0.938, the F-1 score of 0.571 and 0.667, the recall of 1.000 and 1.000, the specificity of 0.727 and 0.778, and the precision of 0.400 and 0.500. The top 5 most important features were Age, IL-6, SYS_BP, MONO%, and Fever classification. Based on this model, an optimized strategy for S-COVID-19-P early identification in fever clinics has also been designed.
ConclusionsS-COVID-19-P could be identified early by a machine-learning model only used collected clinical information without CT images on admission in fever clinics with a 100% recall score. The well-performed and validated model has been deployed as an online triage tool, which is available at https://intensivecare.shinyapps.io/COVID19/. | emergency medicine |
10.1101/2020.03.20.20039537 | The Population Attributable Fraction (PAF) of cases due to gatherings and groups with relevance to COVID-19 mitigation strategies | BackgroundMany countries have banned groups and gatherings as part of their response to the pandemic caused by the coronavirus, SARS-CoV-2. Although there are outbreak reports involving mass gatherings, the contribution to overall transmission is unknown.
MethodsWe used data from a survey of social contact behaviour that specifically asked about contact with groups to estimate the Population Attributable Fraction (PAF) due to groups as the relative change in the Basic Reproduction Number when groups are prevented.
FindingsGroups of 50+ individuals accounted for 0.5% of reported contact events, and we estimate that the PAF due to groups of 50+ people is 5.4% (95%CI 1.4%, 11.5%). The PAF due to groups of 20+ people is 18.9% (12.7%, 25.7%) and the PAF due to groups of 10+ is 25.2% (19.4%, 31.4%)
InterpretationLarge groups of individuals have a relatively small epidemiological impact; small and medium sized groups between 10 and 50 people have a larger impact on an epidemic. | epidemiology |
10.1101/2020.03.24.20042648 | One size does not fit all. Genomics differentiates among binge-eating disorder, bulimia nervosa, and anorexia nervosa | ObjectiveGenome-wide association studies have identified multiple genomic regions associated with anorexia nervosa. Relatively few or no genome-wide studies of other eating disorders, such as bulimia nervosa and binge-eating disorder, have been performed, despite their substantial heritability. Exploratively, we aimed to identify traits that are genetically associated with binge-type eating disorders.
MethodWe calculated genome-wide polygenic scores for 269 trait and disease outcomes using PRSice v2.2 and their association with anorexia nervosa, bulimia nervosa, and binge-eating disorder in up to 640 cases and 17,050 controls from the UK Biobank. Significant associations were tested for replication in the Avon Longitudinal Study of Parents and Children (up to 217 cases and 3018 controls).
ResultsIndividuals with binge-type eating disorders had higher polygenic scores than controls for other psychiatric disorders, including depression, schizophrenia, and attention deficit hyperactivity disorder, and higher polygenic scores for body mass index.
DiscussionOur findings replicate some of the known comorbidities of eating disorders on a genomic level and motivate a deeper investigation of shared and unique genomic factors across the three primary eating disorders. | psychiatry and clinical psychology |
10.1101/2020.03.22.20040964 | A Review of Dosages of Chloroquine and Hydroxychloroquine for COVID-19 in registered Clinical Trials during First Quarter of 2020 | BackgroundThe novel corona virus disease 2019 (COVID-19) pandemic has been causing a massive global public health havoc. Use of quinolones for treatment of COVID-19 was a matter of huge discussion in scientific community. Falsified data about efficacy of the drug against COVID-19 disseminated. This review was designed to study the dosages of chloroquine and hydroxychloroquine planned to be administered in clinical trials registered up to March 2020.
SummaryInclusion of chloroquine and hydroxychloroquine for COVID-19 treatment in Chinese national treatment guideline in the early days of the pandemic prompted numerous clinical trials in many countries to authenticate the efficacy of the drugs. Trials were designed to include chloroquine or hydroxychloroquine singly or in combination with other drugs. Almost all of the trials planned oral administration except few which used aerosol inhalation. In the later half of 2020, systematic reviews and results of those clinical trials point out the inefficacies and inadvertent adverse events due to the use of these quinolone drugs for COVID-19.
ConclusionThis study reviews the various dosages of chloroquine and hydroxychloroquine utilized in published and under-study clinical trials as assessed during the end of March 2020. Specifically, clinical trials registered in Chinese and US trial registries were examined. | pharmacology and therapeutics |
10.1101/2020.03.30.20045591 | Phenotypically independent profiles relevant to mental health are genetically correlated | Genome-wide association studies (GWAS) and family-based studies have revealed partly overlapping genetic architectures between various psychiatric disorders. Given clinical overlap between disorders, our knowledge of the genetic architectures underlying specific symptom profiles and risk factors is limited. Here, we aimed to derive distinct profiles relevant to mental health in healthy individuals and to study how these genetically relate to each other and to common psychiatric disorders. Using independent component analysis, we decomposed self-report mental health questionnaires from 136,678 healthy individuals of the UK Biobank, excluding data from individuals with a diagnosed neurological or psychiatric disorder, into thirteen distinct profiles relevant to mental health, capturing different symptoms as well as social and risk factors underlying reduced mental health. Utilizing genotypes from 117,611 of those individuals with White English ancestry, we performed GWAS for each mental health profile and assessed genetic correlations between these profiles, and between the profiles and common psychiatric disorders and cognitive traits. We found that mental health profiles were genetically correlated with a wide range of psychiatric disorders and cognitive traits, with strongest effects typically observed between a given mental health profile and a disorder for which the profile is common (e.g. depression symptoms and major depressive disorder, psychosis and schizophrenia). Strikingly, although the profiles were phenotypically uncorrelated, many of them were genetically correlated with each other. This study provides evidence that statistically independent mental health profiles partly share genetic underpinnings and show genetic overlaps with psychiatric disorders, suggesting that shared genetics across psychiatric disorders cannot be exclusively attributed to the known overlapping symptomatology between the disorders. | psychiatry and clinical psychology |
10.1101/2020.03.25.20043166 | Risk assessment of progression to severe conditions for patients with COVID-19 pneumonia: a single-center retrospective study | BackgroundManagement of high mortality risk due to significant progression requires prior assessment of time-to-progression. However, few related methods are available for COVID-19 pneumonia.
MethodsWe retrospectively enrolled 338 adult patients admitted to one hospital between Jan 11, 2020 to Feb 29, 2020. The final follow-up date was March 8, 2020. We compared characteristics between patients with severe and non-severe outcome, and used multivariate survival analyses to assess the risk of progression to severe conditions.
ResultsA total of 76 (31.9%) patients progressed to severe conditions and 3 (0.9%) died. The mean time from hospital admission to severity onset is 3.7 days. Age, body mass index (BMI), fever symptom on admission, co-existing hypertension or diabetes are associated with severe progression. Compared to non-severe group, the severe group already demonstrated, at an early stage, abnormalities in biomarkers indicating organ function, inflammatory responses, blood oxygen and coagulation function. The cohort is characterized with increasing cumulative incidences of severe progression up to 10 days after admission. Competing risks survival model incorporating CT imaging and baseline information showed an improved performance for predicting severity onset (mean time-dependent AUC = 0.880).
ConclusionsMultiple predisposition factors can be utilized to assess the risk of progression to severe conditions at an early stage. Multivariate survival models can reasonably analyze the progression risk based on early-stage CT images that would otherwise be misjudged by artificial analysis. | infectious diseases |
10.1101/2020.03.28.20046235 | Current State and Predicting Future Scenario of Highly Infected Nations for COVID-19 Pandemic | Since the first report of COVID-19 from Wuhan China, the virus has rapidly spread across the globe now presently reported in 177 countries with positive cases crossing 400 thousand and rising. In the current study, prediction is made for highly infected countries by a simple and novel method using only cumulative positive cases reported. The rate of infection per week (Rw) coefficient delineated three phases for the current COVID-19 pandemic. All the countries under study have passed Phase 1 and are currently in Phase 2 except for South Korea which is in Phase 3. Early detection with rapid and large-scale testing helps in controlling the COVID-19 pandemic. Staying in Phase 2 for longer period would lead to increase in COVID-19 positive cases. | epidemiology |
10.1101/2020.03.30.20044438 | Congenital disorder of glycosylation caused by starting site-specific variant in syntaxin-5 | The SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) protein syntaxin-5 (Stx5) is essential for Golgi transport. In humans, the STX5 mRNA encodes two protein isoforms, Stx5 Long (Stx5L) from the first starting methionine and Stx5 Short (Stx5S) from an alternative starting methionine at position 55. In this study, we identify a human disorder caused by a single missense substitution in the second starting methionine (p.M55V), resulting in complete loss of the short isoform. Patients suffer from an early fatal multisystem disease, including severe liver disease, skeletal abnormalities and abnormal glycosylation. Primary human dermal fibroblasts isolated from these patients show defective glycosylation, altered Golgi morphology as measured by electron microscopy, mislocalization of glycosyltransferases, and compromised ER-Golgi trafficking. Measurements of cognate binding SNAREs, based on biotin-synchronizable forms of Stx5 (the RUSH system) and Forster resonance energy transfer (FRET), revealed that the short isoform of Stx5 is essential for intra-Golgi transport. Alternative starting codons of Stx5 are thus linked to human disease, demonstrating that the site of translation initiation is an important new layer of regulating protein trafficking. | genetic and genomic medicine |
10.1101/2020.03.30.20044438 | Congenital disorder of glycosylation caused by starting site-specific variant in syntaxin-5 | The SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) protein syntaxin-5 (Stx5) is essential for Golgi transport. In humans, the STX5 mRNA encodes two protein isoforms, Stx5 Long (Stx5L) from the first starting methionine and Stx5 Short (Stx5S) from an alternative starting methionine at position 55. In this study, we identify a human disorder caused by a single missense substitution in the second starting methionine (p.M55V), resulting in complete loss of the short isoform. Patients suffer from an early fatal multisystem disease, including severe liver disease, skeletal abnormalities and abnormal glycosylation. Primary human dermal fibroblasts isolated from these patients show defective glycosylation, altered Golgi morphology as measured by electron microscopy, mislocalization of glycosyltransferases, and compromised ER-Golgi trafficking. Measurements of cognate binding SNAREs, based on biotin-synchronizable forms of Stx5 (the RUSH system) and Forster resonance energy transfer (FRET), revealed that the short isoform of Stx5 is essential for intra-Golgi transport. Alternative starting codons of Stx5 are thus linked to human disease, demonstrating that the site of translation initiation is an important new layer of regulating protein trafficking. | genetic and genomic medicine |
10.1101/2020.03.30.20047993 | Double trouble? When a pandemic and seasonal virus collide | As healthcare capacities in the US and Europe reach their limits due to a surge in the COVID-19 pandemic, both regions enter the 2020-2021 influenza season. Southern hemisphere countries that had suppressed influenza seasons provide a hopeful example, but the lack of reduction in influenza in the 2019-2020 influenza season and heterogeneity in nonpharmaceutical and pharmaceutical interventions show that we cannot assume the same effect will occur globally. The US and Europe must promote the implementation and continuation of these measures in order to prevent additional burden to healthcare systems due to influenza. | epidemiology |
10.1101/2020.03.30.20048223 | Wave Reflection: More Than A Round Trip | Reflected pressure waves are key to the understanding of vascular ageing, a prominent factor in major cardiovascular events. Several different metrics have been proposed to index the effect of wave reflection on the pressure waveform and thereby serve as an indicator of vascular ageing. The extent to which these indices are influenced by factors other than vascular health remains a matter of concern. In this paper, we use transmission-line theory to derive a mathematical model for the reflection time (Trefl), and the augmentation index (AI), assuming a general extended model of the arterial system. Then, we test the proposed model against values reported in the literature. Finally, we discuss insights from the model to common observations in the literature such as age-related "shift" in the reflection site, the variation of AI with heart rate, and the flattening of Trefl in older participants. | cardiovascular medicine |
10.1101/2020.03.29.20046755 | Highly tweeted endodontic articles: a network analysis | IntroductionTo identify active journals, authors, institutions and hot topics in the field of Endodontics within the Twittersphere.
MethodsOn December 23, 2019, the Altmetric database was searched using the titles of 11 endodontic journals. The bibliometric data of the top 5% of endodontic articles with the highest tweets number were extracted from the Web of Science and analyzed.
ResultsOverall, 3,918 tweets (from 3,881 individual posts) related to endodontic articles from seven journals were identified, which were mostly from the U.S. The Journal of Endodontics received the most tweets. Systematic review and apical periodontitis were the most popular keywords. At the author level, Dummer PMH and Patel S and at institution level Kings College London and Cardiff University, had the largest number of popular articles in the Twittersphere. The number of tweets was not correlated with citations (r=0.007, P=0.929). No statistically significant differences were found between open access (n=41, Mean=11.19) and non-open access (n=136, Mean=9.38) articles regarding the number of tweets (P=0.648).
ConclusionsIn the Twittersphere, the overall activity of endodontic journals and associations were low. They could be more active and increase their visibility and social impact by immediately sharing research outcomes and communicating with peers, practitioners, and patients. | dentistry and oral medicine |
10.1101/2020.03.31.20049510 | Mindfulness related changes in grey matter: A Systematic Review and Meta-analysis. | Knowing target regions undergoing structural changes caused by behavioural interventions is paramount in evaluating the effectiveness of such practices. Here, using a systematic review approach, we identified 25 peer-reviewed magnetic resonance imaging (MRI) studies demonstrating grey matter changes related to mindfulness meditation. An activation likelihood estimation (ALE) analysis (n=16) revealed the right anterior ventral insula as the only significant region with consistent effect across studies, whilst an additional functional connectivity analysis indicates that both left and right insulae, and the anterior cingulate gyrus with adjacent paracingulate gyri should also be considered in future studies. Statistical meta-analyses suggest medium to strong effect sizes from Cohens d [~]0.8 in the right insula to [~]1 using maxima across the whole brain. The systematic review revealed design issues with selection, information, attrition and confirmation biases, in addition to weak statistical power. In conclusion, our analyses show that mindfulness meditation practice does induce grey matter changes but also that improvements in methodology are needed to establish mindfulness as a therapeutic intervention. | psychiatry and clinical psychology |
10.1101/2020.04.01.20048686 | The effect of including the Nordic Hamstring exercise on sprint and jump performance in athletes: protocol of a systematic review and meta-analyses | The Nordic Hamstring exercise reduces hamstring strain injuries in football and other sports, but the exercise is not well adopted in practice. Barriers from practitioners include fear of performance decrements, due to lack of specificity of the exercise with high speed running. However, in theory, increased eccentric hamstring strength could transfer to faster sprinting due to higher horizontal force production. Studies on the effect of the Nordic Hamstring exercise on performance have been conflicting and no synthesis of the evidence exists. We therefore pose the following question: does including the Nordic Hamstring exercise hamper sprint or jump performance in athletes? We will answer this question by performing a systematic review of the literature, critically appraise relevant studies, and GRADE the evidence across key outcomes and perform meta-analyses, meta-regression and subgroup analyses. In this protocol we outline the planned methods and procedures.
Progress reportBesides this protocol, our data extraction form and the process of data extraction has been piloted on 3 relevant studies, along with familiarization with the Risk of Bias 2.0 tool. We have also comprised a preliminary search strategy for PubMed.
Supplementary filesO_LIData Extraction Form (.pdf)
C_LIO_LIPopulated PRISMA-P checklist (.pdf)
C_LI | sports medicine |
10.1101/2020.04.05.20054304 | Comparing Metapopulation Dynamics of Infectious Diseases under Different Models of Human Movement | Newly available data sets present exciting opportunities to investigate how human population movement contributes to the spread of infectious diseases across large geographical distances. It is now possible to construct realistic models of infectious disease dynamics for the purposes of understanding global-scale epidemics. Nevertheless, a remaining unanswered question is how best to leverage the new data to parameterize models of movement, and whether ones choice of movement model impacts modeled disease outcomes. We adapt three well-studied models of infectious disease dynamics, the SIR model; the SIS model; and the Ross-Macdonald model, to incorporate either of two candidate movement models. We describe the effect that the choice of movement model has on each disease models results, finding that in all cases there are parameter regimes where choosing one movement model instead of another has a profound impact on epidemiological outcomes. We further demonstrate the importance of choosing an appropriate movement model using the applied case of malaria transmission and importation on Bioko Island, Equatorial Guinea, finding that one model produces intelligible predictions of R0 while the other produces nonsensical results.
Significance StatementNewly available large-scale datasets of human population movement represent an opportunity to model how diseases spread between different locations. Combining infectious disease models with mechanistic models of host movement enables studies of how movement drives disease transmission and importation. Here we explore in what ways modeled epidemiological outcomes may be sensitive to the modelers choice of movement model structure. We use three different mathematical models of disease transmission to show how a models epidemiological predictions can change dramatically depending on the chosen host movement model. We find these different outcomes are robust to using the same data sources to parameterize each candidate model, which we illustrate using an example of real-world malaria transmission and importation in Bioko Island, Equatorial Guinea. | epidemiology |
10.1101/2020.04.06.20055574 | A systematic framework for assessing the clinical impact of polygenic risk scores | Risk prediction models provide empirical recommendations that ultimately aim to deliver optimal patient outcomes. Genetic information, in the form of a polygenic risk score (PRS), may be included in these models to significantly increase their accuracy. Several analyses of PRS accuracy have been completed, nearly all focus on only a few diseases and report limited statistics. This narrow approach has limited our ability to assess as a whole whether PRSs can provide actionable disease predictions. This investigation aims to address this uncertainty by comprehensively analyzing 23 diseases within the UK Biobank. Our results show that including the PRS to a base model containing age, sex and the top ten genetic principal components significantly improves prediction accuracy, as measured by ROC curves, in a majority 21 of 23 diseases and reclassifies on average 68% of the individuals in the top 5% risk group. For heart failure, breast cancer, prostate cancer and gout, decision curve analyses using the 5% risk threshold determined that including the PRS in the base model would correctly identity at least 60 more individuals who develop the disease for every 1000 individuals screened, without making any incorrect predictions. Analyses that included disease-specific risk factors, such as Body-Mass Index, and consider time of disease onset found similar PRS benefits. The improved prediction accuracy was translated to 10 instances in which medications/supplements and 94 instances in which lifestyle modifications lead to significantly greater reduction in disease risk for individuals in the top PRS quintile compared to the bottom PRS quintile. Finally we provide guidance for tailored, future PRS generation by comprehensively ranking methods that generate PRS weights and identifying genome wide association study characteristics that influence PRS predictions. The unification of significantly enhanced disease predictions, novel risk mitigation opportunities and improved methodological clarity indicate that PRSs carry far greater clinical impact than previously known. | genetic and genomic medicine |
10.1101/2020.04.07.20057265 | Polygenic associations and causal inferences between serum immunoglobulins and amyotrophic lateral sclerosis | Chronic inflammation might contribute to the development of amyotrophic lateral sclerosis (ALS), the relationship between serum immunoglobulins and risk of ALS remains however unclear. In order to overcome limitations like reverse causation and residual confounding commonly seen in the observational studies, we applied molecular epidemiological analyses to examine the polygenic and causal associations between serum immunoglobulins and ALS. Summary statistics from the large-scale genome-wide association studies (GWAS) among European ancestry populations ([~]15000 individuals for serum immunoglobulins, and more than 36000 individuals for ALS) were accessed from different consortia. The relationships between three types of serum immunoglobulins (IgA, IgM, and IgG) and ALS were investigated in a discovery phase and then in a replication phase. Polygenic risk score (PRS) analysis was performed with PRSice package to test the polygenic association, and Mendelian randomization (MR) analysis was performed with TwoSampleMR package to infer the causality. An inverse polygenic association was discovered between IgA and ALS as well as between IgM and ALS. Such associations were however not replicated using a larger GWAS of ALS, and no causal association was observed for either IgA-ALS or IgM-ALS. A positive polygenic association was both discovered [odds ratio (OR) = 1.18, 95% confidence interval (CI): 1.12-1.25, P=5.9x10-7] and replicated (OR=1.13, 95% CI: 1.06-1.20, P=0.001) between IgG and ALS. A causal association between IgG and ALS was also suggested in both the discovery (OR=1.06, 95%CI: 1.02-1.10, P=0.009) and replication (OR=1.07, 95%CI: 0.90-1.24, P=0.420) analyses, although the latter was not statistically significant. This study suggests a shared polygenic risk between serum IgG (as a biomarker for chronic inflammation) and ALS. | neurology |
10.1101/2020.04.07.20055756 | Polar Vantage and Oura physical activity and sleep trackers: A validation and comparison study | BackgroundConsumer-based activity trackers are increasingly used in research as they have potential to increase activity participation and can be used for estimating physical activity. However, the accuracy of newer consumer-based devices is mostly unknown, and validation studies are needed.
ObjectiveThe objective of this study was to test the accuracy of the Polar Vantage watch and Oura ring activity trackers for measuring physical activity, total energy expenditure, resting heart rate, and sleep duration, in free-living adults.
MethodsTwenty-one participants wore two consumer-based activity trackers (Polar, Oura), an ActiGraph accelerometer, an Actiheart accelerometer and heart rate monitor, and completed a sleep diary for up to seven days. We assessed Polar and Oura validity and comparability for physical activity, total energy expenditure, resting heart rate (Oura), and sleep duration. We analysed repeated measures correlation, Bland-Altman plots, and mean absolute percentage error.
ResultsPolar and Oura were both strongly correlated (p<0.001) with ActiGraph for steps (Polar r 0.75, 95% CI 0.54-0.92. Oura r 0.77, 95% CI 0.62-0.87), moderate-to-vigorous physical activity (Polar r 0.76, 95% CI 0.62-0.88. Oura r 0.70, 95% CI 0.49-0.82), and total energy expenditure (Polar r 0.69, 95% CI 0.48-0.88. Oura r 0.70, 95% CI 0.51-0.83) and strongly or very strongly correlated (p<0.001) with the sleep diary for sleep duration (Polar r 0.74, 95% CI 0.56-0.88. Oura r 0.82, 95% CI 0.68-0.91). Oura had a very strong correlation (p<0.001) with Actiheart for resting heart rate (r 0.9, 95% CI 0.85-0.96). However, all confidence interval ranges were wide and mean absolute percentage error was high for all variables, except Oura sleep duration (10%) and resting heart rate (3%) where Oura under-reported on average one beat per minute.
ConclusionsOura can potentially be used as an alternative to Actiheart to measure resting heart rate. For sleep duration, Polar and Oura can potentially be used as a replacement for a manual sleep diary, depending on acceptable error. Neither Polar nor Oura can replace ActiGraph for measuring steps, moderate-to-vigorous physical activity, and total energy expenditure, but may be used as an additional source of physical activity in some settings. | epidemiology |
10.1101/2020.04.09.20060103 | Acceptance of and preference for COVID-19 vaccination in healthcare workers: a comparative analysis and discrete choice experiment | BackgroundA major obstacle to successful coronavirus disease (COVID-19) vaccine rollout is vaccine hesitancy. Acceptance of and preferences for COVID-19 vaccination among healthcare workers (HCWs) is critical, because they are a key target group for vaccination programs, and they are also highly influential to vaccine uptake in the wider population. This study sought to comparatively determine the acceptance of and preference for COVID-19 vaccination among HCWs and the general population.
MethodsAn Internet-based, region-stratified discrete-choice experiment was conducted among 352 HCWs and 189 general population respondents recruited in March 2020 from 26 Chinese provinces. We accessed knowledge of disease, attitude towards and acceptance of COVID-19 vaccination. Several attributes (related to COVID-19 disease, COVID-19 vaccination and one social acceptance) were identified as key determinants of vaccine acceptance.
ResultsHCWs had a more in-depth understanding of COVID-19 and showed a higher willingness to accept COVID-19 vaccines with lower effectiveness and/or more severe adverse effects compared to the general population. 76.4% of HCWs (vs 72.5% of the general population) expressed willingness to receive vaccination ({chi}2=2.904, p=0.234). High levels of willingness to accept influenza (65.3%) and pneumococcal (55.7%) vaccination were also seen in HCWs. Future COVID-19 disease incidence (OR: 4.367, 95% CI 3.721-5.126), decisions about vaccination among social contacts of respondents (OR 0.398, 95% CI 0.339-0.467), and infection risk >30% (OR 2.706, 95% CI 1.776-2.425) significantly increased the probability of vaccination acceptance in HCWs.
ConclusionMulti-component interventions to address the key determinants of hesitancy in both HCWs and in the general population should be considered for COVID-19 vaccination programs. | public and global health |
10.1101/2020.04.08.20058842 | The Epidemiological Implications of Incarceration Dynamics in Jails for Community, Corrections Officer, and Incarcerated Population Risks from COVID-19 | COVID-19 is challenging many societal institutions, including our criminal justice systems. Some have proposed or enacted (e.g. the State of New Jersey) reductions in the jail and/or prison populations. We present a mathematical model to explore the epidemiological impact of such interventions in jails and contrast them with the consequences of maintaining unaltered practices. We consider infection risk and likely in-custody deaths, and estimate how within-jail dynamics lead to spill-over risks, not only affecting incarcerated people, but increasing exposure, infection, and death rates for both corrections officers, and the broader community beyond the justice system. We show that, given a typical jail-community dynamic, operating in a business-as-usual way will result in significant and rapid loss of life. Large scale reductions in arrest and speeding of releases are likely to save the lives of incarcerated people, jail staff, and the community at large. | epidemiology |
10.1101/2020.04.09.20058537 | Observable Variations in Human Sex Ratio at Birth | The human sex ratio at birth (SRB), defined as the ratio between the number of newborn boys to the total number of newborns, is typically slightly greater than 1/2 (more boys than girls) and tends to vary across different geographical regions and time periods. In this large-scale study, we sought to validate previously-reported associations and test new hypotheses using statistical analysis of two very large datasets incorporating electronic medical records (EMRs). One of the datasets represents over half ([~]150 million) of the US population for over 8 years (IBM Watson Health MarketScan insurance claims) while another covers the entire Swedish population ([~]9 million) for over 30 years (the Swedish National Patient Register). After testing more than 100 hypotheses, we showed that neither dataset supported models in which the SRB changed seasonally or in response to variations in ambient temperature. However, increased levels of a diverse array of air and water pollutants, were associated with lower SRBs, including increased levels of industrial and agricultural activity, which served as proxies for water pollution. Moreover, some exogenous factors generally considered to be environmental toxins turned out to induce higher SRBs. Finally, we identified new factors with signals for either higher or lower SRBs. In all cases, the effect sizes were modest but highly statistically significant owing to the large sizes of the two datasets. We suggest that while it was unlikely that the associations have arisen from sex-specific selection mechanisms, they are still useful for the purpose of public health surveillance if they can be corroborated by empirical evidences.
Author SummaryThe human sex ratio at birth (SRB), usually slightly greater than 1/2, have been reported to vary in response to a wide array of exogenous factors. In the literature, many such factors have been posited to be associated with higher or lower SRBs, but the studies conducted so far have focused on no more than a few factors at a time and used far smaller datasets, thus prone to generating spurious correlations. We performed a series of statistical tests on 2 large, country-wide health datasets representing the United States and Sweden to investigate associations between putative exogenous factors and the SRB, and were able to validate a set of previously-reported associations while also discovering new signals. We propose to interpret these results simply as public health indicators awaiting further empirical confirmation rather than as implicated in (adaptive) sexual selection mechanisms. | sexual and reproductive health |
10.1101/2020.04.11.20056523 | The effect of Arbidol Hydrochloride on reducing mortality of Covid-19 patients: a retrospective study of real world date from three hospitals in Wuhan | BACKGROUNDThe worldwide COVID-19 pandemic is increasing exponentially and demands an effective and promising therapy at most emergency.
METHODSWe have assembled a cohort consisting 504 hospitalized COVID-19 patients. Detailed information on patients characteristics and antiviral medication use during their stay at designated hospitals along with their pre and post treatment results were collected. The study objective is to evaluate the treatment efficacy of Arbidol, together with the concurrent drugs Oseltamivir and Lopinavir/Ritonavir on mortality and lesion absorption based on chest CT scan.
FINDINGSThe overall mortality rate was 15.67% in the cohort. The older age, lower SpO2 level, larger lesion, early admission date, and the presence of pre-existing conditions were associated with higher mortality. After adjusting for the patients age, sex, pre-existing condition, SpO2, lesion size, admission date, hospital, and concurrent antiviral drug use, Arbidol was found promising and associated with reduced mortality. The OR for Arbidol is 0{middle dot}183 (95% CI, 0{middle dot}075 to 0{middle dot}446; P<0{middle dot}001). Furthermore, Arbidol is also associated with faster lesion absorption after adjusting for patients characteristics and concurrent antiviral drug use (P=0{middle dot}0203).
INTERPRETATIONThe broad-spectrum antiviral drug Arbidol was found to be associated with faster | epidemiology |
10.1101/2020.04.12.20063032 | Differential Effects of Pathological Beta Burst Dynamics Between Parkinson's Disease Phenotypes Across Different Movements | BackgroundResting state beta band (13 - 30 Hz) oscillations represent pathological neural activity in Parkinsons disease (PD). It is unknown how the peak frequency or dynamics of beta oscillations may change among fine, limb and axial movements and different disease phenotypes. This will be critical for the development of personalized closed loop deep brain stimulation (DBS) algorithms during different activity states.
MethodsSubthalamic (STN) local field potentials (LFPs) were recorded from a sensing neurostimulator (Activa(R) PC+S, Medtronic PLC.,) in fourteen PD participants (six tremor-dominant, 8 akinetic-rigid) off medication/off STN DBS during thirty seconds of repetitive alternating finger tapping, wrist-flexion extension, stepping in place, and free walking. Beta power peaks and beta burst dynamics were identified by custom algorithms and were compared among movement tasks and between tremor-dominant and akinetic-rigid groups.
ResultsBeta power peaks were evident during fine, limb, and axial movements in 98% of movement trials; the peak frequencies were similar during each type of movement. Burst power and duration were significantly larger in the high beta band, but not in the low beta band, in the akinetic-rigid group compared to the tremor-dominant group.
ConclusionsThe conservation of beta peak frequency during different activity states supports the feasibility of patient-specific closed loop DBS algorithms driven by the dynamics of the same beta band during different activities. Akinetic-rigid participants had greater power and longer burst durations in the high beta band than tremor-dominant participants during movement, which may relate to the difference in underlying pathophysiology between phenotypes. | neurology |
10.1101/2020.04.14.20065326 | Fatigue in perinatal stroke is associated with the functional connectivity | Fatigue is prevalent in youth with perinatal stroke, but the causes are unclear. Predictive coding models of adult post-stroke fatigue suggest that fatigue may arise from dysfunction in predictive processing networks. To date, the association between fatigue and neural network connectivity in youth with perinatal stroke has not been examined. The present study examined the association between fatigue and the functional connectivity of predictive processing neural networks, measured using resting-state functional magnetic resonance imaging, in individuals with perinatal stroke. Participants who reported experiencing fatigue had weaker functional connectivity between the non-lesioned middle frontal and supramarginal gyri and between the non-lesioned intracalcarine cortex and the lesioned paracingulate cortex. In contrast, participants reporting fatigue had stronger functional connectivity between the lesioned inferior temporal gyrus and non-lesioned insula. These results suggest that fatigue in youth with hemiparetic cerebral palsy caused by perinatal stroke is associated with the functional connectivity of hubs previously associated with predictive processing and fatigue. These results suggest potential cortical and behavioral targets for the treatment of fatigue in individuals with perinatal stroke. | neurology |
10.1101/2020.04.14.20065540 | The Longevity-Frailty Hypothesis: Evidence from COVID-19 Death Rates in Europe | By the end of spring (May 31st), the COVID-19 death rate was remarkably unevenly distributed across the countries Europe. While the risk of COVID-19 mortality is known to increase with age, age-specific COVID-19 death rates across Europe were similarly aberrantly distributed, implying that differences in age structure is an unlikely source of European variation in COVID-19 mortality. To explain these mortality distributions, we present a simple model where more favorable survival environments promote longevity and the accumulation of health frailty among the elderly while less favorable survival environments induce a mortality selection process that results in lower health frailty. Because the age-related conditions of frailty render the elderly less resistant to SARS-CoV-2, pre-existing survival environments may be non-obviously positively related to the COVID-19 death rate. To quantify the survival environment parameter of our model, we collected historic cohort- and period-based age-specific probabilities of death across Europe. We find strong positive relationships between survival indicators and COVID-19 death rates across Europe, a result that is robust to statistical control for the capacity of a healthcare system to treat and survive infected persons, the timing and stringency of non-pharmaceutical interventions, and the volume of inbound international travelers, among other factors. To address possible concerns over reporting heterogeneity across countries, we show that results are robust to the substitution of our response variable for a measure of cumulative excess mortality. Consistent with the intuition of our model, we also show a strong negative association between age-specific COVID-19 death rates and pre-existing all-cause age-specific mortality rates for a subset of European countries. Overall, results support the notion that variation in pre-existing frailty, resulting from heterogeneous survival environments, partially caused striking differences in COVID-19 death during the first wave of the pandemic. | epidemiology |
10.1101/2020.04.15.20066035 | Exploring health in the UK Biobank: associations with sociodemographic characteristics, psychosocial factors, lifestyle and environmental exposures | A greater understanding of factors associated with good health may help increase longevity and healthy life expectancy. Here we report associations between multiple health indicators and sociodemographic (age, sex, ethnicity, education, income and deprivation), psychosocial (loneliness and social isolation), lifestyle (smoking, alcohol intake, sleep, BMI, physical activity and stair climbing) and environmental (air pollution, noise and greenspace) factors, using data from 307,378 UK Biobank participants. Low income, being male, neighbourhood deprivation, loneliness, social isolation, short or long sleep duration, low or high BMI and smoking was associated with poor health. Walking, vigorous-intensity physical activity and more frequent alcohol intake was associated with good health. There was some evidence that airborne pollutants (PM2.5, PM10, and NO2) and noise (Lden) were associated with poor health, though findings were inconsistent in adjusted models. Our findings highlight the multifactorial nature of health, the importance of non-medical factors, such as loneliness, healthy lifestyle behaviours and weight management, and the need to examine efforts to improve health outcomes of individuals with low income. | epidemiology |
10.1101/2020.04.17.20069369 | Quantitative Trait Loci on Chromosome 21 have Pleiotropic Effects on %FEV1 and Allergen Polysensitization; asthma related traits in the EGEA study | To investigate whether the 21q21 region may contain a quantitative trait locus (QTL) with pleiotropic effect on % predicted FEV1 (forced expiratory volume in 1 second) and SPTQ (number of positive skin test responses to 11 allergens), in 295 EGEA families ascertained through asthmatic probands, we conducted a bivariate linkage analysis using two approaches:
(1) a bivariate variance components (VC) analysis and (2) A combined principal components (CPC) analysis, with 13 microsatellites covering the whole chromosome 21. To identify the genetic variants associated with these traits, we performed family-based association analysis (FBAT) for the second principal component (PC2) using two microsatellites and 27 SNPs belonging to three candidate genes, located in the vicinity of the linkage peak. Univariate linkage analyses showed suggestive evidence of linkage to %FEV1 and SPTQ at two positions. Bivariate VC linkage analysis of these phenotypes led to an increase in linkage signals as compared to univariate analysis at the same positions. The peaks obtained by the CPC led to similar results as the full bivariate VC approach; evidence for linkage mainly coming from PC2. The strongest association signal, using single marker analysis for PC2, was obtained with D21S1252 (p=0.003 for global test; p=0.004 for allele 2 and p=0.001 for allele 11) and rs2834213 of IFNGR2 (p=0.003), these two loci being 3 Mb apart. Multi-marker analysis further strengthened this finding. These results indicate that at least two genetic factors may be involved in SPTQ and %FEV1 variability but further genotyping is needed to better understand these findings. | respiratory medicine |
10.1101/2020.04.17.20069666 | Predicting the epidemic curve of the coronavirus (SARS-CoV-2) disease (COVID-19) using artificial intelligence | The aim of our study was to predict the epidemic curves (daily new cases) of COVID-19 pandemic using Artificial Intelligence (AI)-based Recurrent Neural Networks (RNNs), then to compare and validate the predicted models with the observed data. We used the publicly available datasets from the World Health Organization and Johns Hopkins University to create a training dataset, then we used RNNs with gated recurring units (Long Short-Term Memory) to create two prediction models. Information collected in the first t time-steps were aggregated with a fully connected (dense) neural network layer and a consequent regression output layer to determine the next predicted value. We also used Root Mean Squared Logarithmic Errors (RMSLE) to compare the predicted models with the observed data. The result of our study underscores that the COVID-19 pandemic is a propagated source epidemic, therefore repeated peaks on the epidemic curve are to be anticipated. Besides, the errors between the predicted and validated data and trends seems to be low. The influence of this pandemic is significant worldwide and has already impacted our daily life. Decision makers must be aware, that even if strict public health measures are executed and sustained, future peaks of infections are possible. | epidemiology |
10.1101/2020.04.17.20069047 | Spatial scales in human movement between reservoirs of infection | The life cycle of parasitic organisms that are the cause of much morbidity in humans often depend on reservoirs of infection for transmission into their hosts. Understanding the daily, monthly and yearly movement patterns of individuals between reservoirs is therefore of great importance to implementers of control policies seeking to eliminate various parasitic diseases as a public health problem. This is due to the fact that the underlying spatial extent of the reservoir of infection, which drives transmission, can be strongly affected by inputs from external sources, i.e., individuals who are not spatially attributed to the region defined by the reservoir itself can still migrate and contribute to it. In order to study the importance of these effects, we build and examine a novel theoretical model of human movement between spatially-distributed focal points for infection clustered into regions defined as reservoirs of infection. Using our model, we vary the spatial scale of human moment defined around focal points and explicitly calculate how varying this definition can influence the temporal stability of the effective transmission dynamics -- an effect which should strongly influence how control measures, e.g., mass drug administration (MDA), define evaluation units (EUs). Considering the helminth parasites as our main example, by varying the spatial scale of human movement, we demonstrate that a critical scale exists around infectious focal points at which the migration rate into their associated reservoir can be neglected for practical purposes. This scale varies by species and geographic region, but is generalisable as a concept to infectious reservoirs of varying spatial extents and shapes. Our model is designed to be applicable to a very general pattern of infectious disease transmission modified by the migration of infected individuals between clustered communities. In particular, it may be readily used to study the spatial structure of hosts for macroparasites with temporally stationary distributions of infectious focal point locations over the timescales of interest, which is viable for the soil-transmitted helminths and schistosomes. Additional developments will be necessary to consider diseases with moving reservoirs, such as vector-born filarial worm diseases. | epidemiology |
10.1101/2020.04.18.20070896 | Early Evidence and Predictors of Mental Distress of Adults One Month in the COVID-19 Epidemic in Brazil | ObjectiveWe aim to provide early evidence of mental distress and its associated predictors among adults one month into the COVID-19 crisis in Brazil.
MethodsWe conducted an online survey of 638 adults in Brazil on March 25-28, 2020, about one month (32 days) cross-sectionally after the first COVID-19 case in South America was confirmed in Sao Paulo. The 638 adults were in 25 states out of the 26 Brazilian states, with the only exception being Roraima, the least populated state in the Amazon. Of all the participating adults, 24%, 20%, and 18% of them were located in Rio de Janeiro state, Santa Catarina state, and Sao Paulo state respectively.
ResultsIn Brazil, 52% (332) of the sampled adults experienced mild or moderate distress, and 18.8% (120) suffered severe distress. Adults who were female, younger, more educated, and exercised less reported higher levels of distress. Each individuals distance from the Brazilian epicenter of Sao Paulo interacted with age and workplace attendance to predict the level of distress. The "typhoon eye effect" was stronger for people who were older or attended their workplace less. The most vulnerable adults were those who were far from the epicenter and did not go to their workplace in the week before the survey.
ConclusionIdentifying the predictors of distress enables mental health services to better target finding and helping the more mentally vulnerable adults during the ongoing COVID-19 crisis. | psychiatry and clinical psychology |
10.1101/2020.04.18.20071142 | Is there evidence that BCG vaccination has non-specific protective effects for COVID 19 infections or is it an illusion created by lack of testing? | The goal of this paper is to showcase that the COVID-19 disease pattern is evolving and to study the relationship between mandatory BCG policy and caseload/million or death/per million. We analyze seven recent publications on the impact of BCG vaccinations on the development of COVID19 illness and extend presented findings using the latest data from April 10, 2020. We analyze data from 98 countries and we extend existing models by adding the dimension of COVID-19-related testing conducted by the analyzed countries. Similarly to prior studies, we find that COVID-19 attributable case and death incidences across countries share a relationship with a countrys BCG vaccination inclusion in the national immunization program when testing is not taken into consideration. However, this relationship vanishes when we add the dimension of testing. We observe that case and death incidences conditional on testing do not get affected by the countries BCG vaccination inclusion in the national immunization program. Therefore, we show that there is no statistical evidence to support the assertion that inclusion of BCG vaccination in national immunization program (NIP) has any impact of COVID 19 infections (cases) or mortality. | infectious diseases |
10.1101/2020.04.18.20070417 | Plasma lipidomics identifies a signature of NAFLD in children that couples with cardiometabolic outcomes in adults | Non-alcoholic fatty liver disease (NAFLD) is an increasingly common condition in children and adults characterized by insulin resistance and altered lipid metabolism. Affected patients are at increased risk of cardiovascular disease (CVD) and children with NAFLD are likely to be at risk of premature cardiac events. Evaluation of the plasma lipid profile of children with NAFLD offers the opportunity to investigate these perturbations and understand how closely they mimic the changes seen in adults with cardiometabolic disease. We hypothesized that change in the concentration of lipid species in pediatric NAFLD would mimic the alterations known to be associated with CVD in adults (and be largely reflective of insulin resistance). Here, we performed untargeted liquid chromatography mass spectrometry (LC-MS) plasma lipidomics on 287 children: 19 lean controls, 146 from an obese cohort, and 122 NAFLD cases who had undergone liver biopsy. Associations between lipid species and liver histology were assessed using regression adjusted for age and sex. Results were then replicated using data from 9,500 adults with metabolic phenotyping. Phosphatidylcholine (PC) and triglyceride (TG) desaturation and chain length were inversely associated with histological severity of paediatric NAFLD. Nine lipids species (lyso-PC, PC, and TG classes) were also associated with hepatic steatosis and insulin resistance in an independent cohort of adults. Five of the 9 lipids replicated in the adults cohort (including PC(36:4)) have been directly linked to death and cardiometabolic disease in adults, as well as indirectly via genetic variants that influence the concentration of these species. Together, these findings suggest that lipid metabolism is altered in paediatric NAFLD in a similar way as in cardiometabolic disease in adults and it is therefore critical to alleviate insulin resistance in these children to mitigate their long-term morbidity. | gastroenterology |
10.1101/2020.04.20.20045690 | Audiometric profiles and patterns of benefit. A data-driven analysis of subjective hearing difficulties and handicaps. | ObjectiveHearing rehabilitation attempts to compensate for auditory dysfunction, reduce hearing difficulties and minimize participation restrictions that can lead to social isolation. However, there is no systematic approach to assess the quality of the intervention at an individual level that might help to evaluate the need of further hearing rehabilitation in the hearing care clinic.
DesignA data-driven analysis on subjective data reflecting hearing disabilities and handicap was chosen to explore "benefit patterns" as a result of rehabilitation in different audiometric groups. The method was based on: 1) Dimensionality reduction; 2) Stratification; 3) Archetypal analysis; 4) Clustering; and 5) Item importance estimation.
Study sample572 hearing-aid users completed questionnaires of hearing difficulties (speech, spatial and qualities hearing scale; SSQ) and hearing handicap (HHQ).
ResultsThe data-driven approach revealed four benefit profiles that were different for each audiometric group. The groups with low degree of high-frequency hearing loss (HLHF) showed a priority for rehabilitating hearing handicaps, whereas the groups with HLHF > 50 dB HL showed a priority for improvements in speech understanding.
ConclusionsThe patterns of benefit and the stratification approach might guide the clinical intervention strategy and improve the efficacy and quality of service in the hearing care clinic. | otolaryngology |
10.1101/2020.04.19.20071357 | Clonal chromosomal mosaicism and loss of chromosome Y in men are risk factors for SARS-CoV-2 vulnerability in the elderly | The ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) has an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome events (CME) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (CME and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, CME and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. | genetic and genomic medicine |
10.1101/2020.04.21.20073494 | The effect of short-graft preparation with tape suspension and screw fixation on loss of knee extension following anterior cruciate ligament reconstruction: A retrospective cross-sectional analysis of public hospital cases from 2015 - 2017 | IntroductionThe short graft with tape suspension (SGTS) is a technique for ACL reconstruction that has gained popularity in recent years. Though the construct utilises a hamstring tendon, its biomechanical properties more closely resemble a stiffer graft such as bone-patella-bone. Due to these properties, there are concerns this technique may increase the likelihood of postoperative loss of extension (LOE), particularly if the surgeon does not modify their tensioning technique. This study compared LOE in patients undergoing ACLR with the SGTS technique, versus other ACLR techniques. We hypothesised that with appropriate technique modifications, the SGTS technique would not be inferior to long hamstring graft techniques with respect to LOE observed clinically during supervised rehabilitation.
Materials and MethodsWe retrospectively reviewed 138 patients who received primary ACLR at one of two hospitals between January 2015 and December 2017 and elected to participate in a rehabilitation program with the hospital physiotherapy department. Postoperative knee extension was assessed by a department physiotherapist until satisfactory function was achieved. Patients were classified as SGTS ACLR or non-SGTS ACLR during chart review and LOE compared at initial assessment and at the time of maximum extension, via a noninferiority analysis.
ResultsThe grafts for the SGTS group (N=44) were significantly larger in diameter (median 8.5mm vs. 8.0mm, P <0.001) and less incidence of notchplasties (17.8% vs. 44.7%, P <0.001) compared with the non-SGTS group (N=94). The upper 95% confidence interval for the difference in proportions between groups did not exceed the non-inferiority margin (0.3 or 30%) at either Initial or Maximum timepoints.
ConclusionsThe SGTS technique was not inferior to other hamstring-graft ACLR techniques with respect to postoperative LOE. Surgeons using or considering using the SGTS construct can rule out increased incidence of LOE as a factor in their decision-making, providing the grafts are prepared according to existing guidance and tensioned in full extension. Further studies are recommended to assess longer term functional outcomes and ultimately treatment success. | orthopedics |
10.1101/2020.04.23.20073601 | Predictive modeling of secondary pulmonary hypertension in left ventricular diastolic dysfunction | Diastolic dysfunction is a common pathology occurring in about one third of patients affected by heart failure. This condition is not associated with a marked decrease in cardiac output or systemic pressure and therefore is more difficult to diagnose than its systolic counterpart. Compromised relaxation or increased stiffness of the left ventricle with or without mitral valve stenosis induces an increase in the upstream pulmonary pressures, and is classified as secondary or group II (2018 Nice classification) pulmonary hypertension. This may result in an increase in the right ventricular afterload leading to right ventricular failure. Elevated pulmonary pressures are therefore an important clinical indicator of diastolic heart failure (sometimes referred to as heart failure with preserved ejection fraction, HFpEF), showing significant correlation with associated mortality. Accurate measurements of this quantity, however, are typically obtained through invasive catheterization, and after the onset of symptoms. In this study, we use the hemodynamic consistency of a differential-algebraic circulation model to predict pulmonary pressures in adult patients from other, possibly non-invasive, clinical data. We investigate several aspects of the problem, including the ability of model outputs to represent a sufficiently wide pathologic spectrum, identifiability of its parameters, to the accuracy of the predicted pulmonary pressures. We also find that a classifier using the assimilated model parameters as features is free from the problem of missing data and is able to detect pulmonary hypertension with sufficiently high accuracy. For a cohort of 82 patients suffering from various degrees of heart failure severity we show that systolic, diastolic and wedge pulmonary pressures can be estimated on average within 8, 6 and 6 mmHg, respectively. We also show that, in general, increased data availability leads to improved predictions. | health informatics |
10.1101/2020.04.22.20075127 | White matter variability, cognition, and disorders: a systematic review. | Inter-individual differences can inform treatment procedures and - if accounted for - have the potential to significantly improve patient outcomes. However, when studying brain anatomy, these inter-individual variations are commonly unaccounted for, despite reports of differences in gross anatomical features, cross-sectional and connectional anatomy. Brain connections are essential to facilitate functional organisation and, when severed, cause impairments or complete loss of function. Hence the study of cerebral white matter may be an ideal compromise to capture inter-individual variability in structure and function. We reviewed the wealth of studies that associate functions and clinical symptoms with individual tracts using diffusion tractography. Our systematic review indicates that tractography has proven to be a sensitive method in neurology, psychiatry, and healthy populations to identify variability and its functional correlates. However, the literature may be biased, as we determined that the most commonly studied tracts are not necessarily those with the highest sensitivity to cognitive functions and pathologies. Additionally, the hemisphere of the studied tract is often unreported, thus neglecting functional laterality and asymmetries. Finally, we demonstrate that tracts, as we define them, are not usually correlated with only one, but rather multiple cognitive domains or pathologies. While our systematic review identified some methodological caveats, it also suggests that tract-function correlations might be a promising biomarker for precision medicine. It characterises variations in brain anatomy, differences in functional organisation, and predicts resilience and recovery in patients. | neurology |
10.1101/2020.04.22.20075127 | White matter variability, cognition, and disorders: a systematic review. | Inter-individual differences can inform treatment procedures and - if accounted for - have the potential to significantly improve patient outcomes. However, when studying brain anatomy, these inter-individual variations are commonly unaccounted for, despite reports of differences in gross anatomical features, cross-sectional and connectional anatomy. Brain connections are essential to facilitate functional organisation and, when severed, cause impairments or complete loss of function. Hence the study of cerebral white matter may be an ideal compromise to capture inter-individual variability in structure and function. We reviewed the wealth of studies that associate functions and clinical symptoms with individual tracts using diffusion tractography. Our systematic review indicates that tractography has proven to be a sensitive method in neurology, psychiatry, and healthy populations to identify variability and its functional correlates. However, the literature may be biased, as we determined that the most commonly studied tracts are not necessarily those with the highest sensitivity to cognitive functions and pathologies. Additionally, the hemisphere of the studied tract is often unreported, thus neglecting functional laterality and asymmetries. Finally, we demonstrate that tracts, as we define them, are not usually correlated with only one, but rather multiple cognitive domains or pathologies. While our systematic review identified some methodological caveats, it also suggests that tract-function correlations might be a promising biomarker for precision medicine. It characterises variations in brain anatomy, differences in functional organisation, and predicts resilience and recovery in patients. | neurology |
10.1101/2020.04.23.20076612 | A systematic review and meta-analysis of Anakinra, Sarilumab, Siltuximab and Tocilizumab for Covid-19 | BackgroundThere is accumulating evidence for an overly activated immune response in severe Covid-19, with several studies exploring the therapeutic role of immunomodulation. Through systematic review and meta-analysis, we assess the effectiveness of specific interleukin inhibitors for the treatment of Covid-19.
MethodsElectronic databases were searched on 7th January 2021 to identify studies of immunomodulatory agents (anakinra, sarilumab, siltuximab and tocilizumab) for the treatment of Covid-19. The primary outcomes were severity on an ordinal scale measured at day 15 from intervention and days to hospital discharge. Key secondary endpoints included overall mortality.
Results71 studies totalling 22,058 patients were included, six were randomised trials. Most explored outcomes in patients who received tocilizumab (59/71). In prospective studies, tocilizumab was associated with improved unadjusted survival (RR 0.83 95%CI 0.72;0.96 I2 = 0.0%), but conclusive benefit was not demonstrated for other outcomes. In retrospective studies, tocilizumab was associated with less severe outcomes on an ordinal scale (Generalised odds ratio 1.34 95%CI 1.10;1.64, I2=98%) and adjusted mortality risk (HR 0.52 95%CI 0.41;0.66, I2 =76.6%). The mean difference in duration of hospitalisation was 0.36 days (95%CI -0.07;0.80, I2 =93.8%). There was substantial heterogeneity in retrospective studies, and estimates should be interpreted cautiously. Other immunomodulatory agents showed similar effects to tocilizumab, but insufficient data precluded meta-analysis by agent.
ConclusionTocilizumab was associated with a lower relative risk of mortality in prospective studies, but effects were inconclusive for other outcomes. Current evidence for the efficacy of anakinra, siltuximab or sarilumab in Covid-19 is insufficient, with further studies urgently needed for conclusive findings. | infectious diseases |
10.1101/2020.04.23.20076612 | A systematic review and meta-analysis of Anakinra, Sarilumab, Siltuximab and Tocilizumab for Covid-19 | BackgroundThere is accumulating evidence for an overly activated immune response in severe Covid-19, with several studies exploring the therapeutic role of immunomodulation. Through systematic review and meta-analysis, we assess the effectiveness of specific interleukin inhibitors for the treatment of Covid-19.
MethodsElectronic databases were searched on 7th January 2021 to identify studies of immunomodulatory agents (anakinra, sarilumab, siltuximab and tocilizumab) for the treatment of Covid-19. The primary outcomes were severity on an ordinal scale measured at day 15 from intervention and days to hospital discharge. Key secondary endpoints included overall mortality.
Results71 studies totalling 22,058 patients were included, six were randomised trials. Most explored outcomes in patients who received tocilizumab (59/71). In prospective studies, tocilizumab was associated with improved unadjusted survival (RR 0.83 95%CI 0.72;0.96 I2 = 0.0%), but conclusive benefit was not demonstrated for other outcomes. In retrospective studies, tocilizumab was associated with less severe outcomes on an ordinal scale (Generalised odds ratio 1.34 95%CI 1.10;1.64, I2=98%) and adjusted mortality risk (HR 0.52 95%CI 0.41;0.66, I2 =76.6%). The mean difference in duration of hospitalisation was 0.36 days (95%CI -0.07;0.80, I2 =93.8%). There was substantial heterogeneity in retrospective studies, and estimates should be interpreted cautiously. Other immunomodulatory agents showed similar effects to tocilizumab, but insufficient data precluded meta-analysis by agent.
ConclusionTocilizumab was associated with a lower relative risk of mortality in prospective studies, but effects were inconclusive for other outcomes. Current evidence for the efficacy of anakinra, siltuximab or sarilumab in Covid-19 is insufficient, with further studies urgently needed for conclusive findings. | infectious diseases |
10.1101/2020.04.23.20076612 | A systematic review and meta-analysis of Anakinra, Sarilumab, Siltuximab and Tocilizumab for Covid-19 | BackgroundThere is accumulating evidence for an overly activated immune response in severe Covid-19, with several studies exploring the therapeutic role of immunomodulation. Through systematic review and meta-analysis, we assess the effectiveness of specific interleukin inhibitors for the treatment of Covid-19.
MethodsElectronic databases were searched on 7th January 2021 to identify studies of immunomodulatory agents (anakinra, sarilumab, siltuximab and tocilizumab) for the treatment of Covid-19. The primary outcomes were severity on an ordinal scale measured at day 15 from intervention and days to hospital discharge. Key secondary endpoints included overall mortality.
Results71 studies totalling 22,058 patients were included, six were randomised trials. Most explored outcomes in patients who received tocilizumab (59/71). In prospective studies, tocilizumab was associated with improved unadjusted survival (RR 0.83 95%CI 0.72;0.96 I2 = 0.0%), but conclusive benefit was not demonstrated for other outcomes. In retrospective studies, tocilizumab was associated with less severe outcomes on an ordinal scale (Generalised odds ratio 1.34 95%CI 1.10;1.64, I2=98%) and adjusted mortality risk (HR 0.52 95%CI 0.41;0.66, I2 =76.6%). The mean difference in duration of hospitalisation was 0.36 days (95%CI -0.07;0.80, I2 =93.8%). There was substantial heterogeneity in retrospective studies, and estimates should be interpreted cautiously. Other immunomodulatory agents showed similar effects to tocilizumab, but insufficient data precluded meta-analysis by agent.
ConclusionTocilizumab was associated with a lower relative risk of mortality in prospective studies, but effects were inconclusive for other outcomes. Current evidence for the efficacy of anakinra, siltuximab or sarilumab in Covid-19 is insufficient, with further studies urgently needed for conclusive findings. | infectious diseases |
10.1101/2020.04.23.20076075 | Small-sample estimation of the mutational support and the distribution of mutations in the SARS-Cov-2 genome | AO_SCPLOWBSTRACTC_SCPLOWThe problem of estimating unknown features of viral species using a limited collection of observations is of great relevance in computational biology. We consider one such particular problem, concerned with determining the mutational support and distribution of the SARS-Cov-2 viral genome and its open reading frames (ORFs). The mutational support refers to the unknown number of sites that is expected to be eventually mutated in the SARS-Cov-2 genome. It may be used to assess the virulence of the virus or guide primer selection for real-time RT-PCR tests during the early stages of an outbreak. Estimating the unknown distribution of mutations in the genome of different subpopulations while accounting for the unseen may aid in discovering adaptation mechanisms used by the virus to evade the immune system. To estimate the mutational support in the small-sample regime, we use GISAID sequencing data and new state-of-the-art polynomial estimation techniques based on weighted and regularized Chebyshev approximations. For distribution estimation, we adapt the well-known Good-Turing estimator. We also perform a differential analysis of mutations and their sites across different populations. Our analysis reveals several findings: First, the mutational supports exhibit significant differences in the ORF6 and ORF7a regions (older vs younger patients), ORF1b and ORF10 regions (females vs males) and as may be expected, in almost all ORFs (for Asia versus Europe and North America). Second, despite the fact that the N region of SARS-Cov-2 has a predicted 10% mutational support, almost all observed mutations fall outside of the two regions of paired primers recommended for testing by the CDC.
Author SummaryWe introduce the new problem of small-sample estimation of the number of mutations and the distribution of mutations in viral and bacterial genomes, and in particular, in the SARS-Cov-2 genome. The approach is of interest due to the fact that it aims to predict which regions in the genome will mutate in the future and with what frequency, given only a very limited number of complete viral sequences. This setting is usually encountered during the early stages of an outbreak when it is critical to assess the potential of the virus to gain mutations advantageous for its spreading. The results may also be used to guide the selection of genomic (primer) regions that are not subject to mutational pressure and can consequently be used as identifiers in the process of testing for the disease. They can also highlight differences in the mutation rates and locations of the SARS-Cov-2 virus affecting diverse subpopulations and therefore potentially suggest the role of certain mutations in evading the immune system. Our approach uses a new class of estimation methods that may find other applications in bioinformatics. | epidemiology |
10.1101/2020.04.22.20074351 | Resilient SARS-CoV-2 diagnostics workflows including viral heat inactivation | There is a worldwide need for reagents to perform SARS-CoV-2 detection. Some laboratories have implemented kit-free protocols, but many others do not have the capacity to develop these and/or perform manual processing. We provide multiple workflows for SARS-CoV-2 nucleic acid detection in clinical samples by comparing several commercially available RNA extraction methods: QIAamp Viral RNA Mini Kit (QIAgen), RNAdvance Blood/Viral (Beckman) and Mag-Bind Viral DNA/RNA 96 Kit (Omega Bio-tek). We also compared One-step RT-qPCR reagents: TaqMan Fast Virus 1-Step Master Mix (FastVirus, ThermoFisher Scientific), qPCRBIO Probe 1-Step Go Lo-ROX (PCR Biosystems) and Luna(R) Universal Probe One-Step RT-qPCR Kit (Luna, NEB). We used primer-probes that detect viral N (EUA CDC) and RdRP (PHE guidelines). All RNA extraction methods provided similar results. FastVirus and Luna proved most sensitive. N detection was more reliable than that of RdRP, particularly in samples with low viral titres. Importantly, we demonstrate that treatment of nasopharyngeal swabs with 70 degrees for 10 or 30 min, or 90 degrees for 10 or 30 min (both original variant and B 1.1.7) inactivates SARS-CoV-2 employing plaque assays, and that it has minimal impact on the sensitivity of the qPCR in clinical samples. These findings make SARS-CoV-2 testing portable to settings that do not have CL-3 facilities. In summary, we provide several testing pipelines that can be easily implemented in other laboratories and have made all our protocols and SOPs freely available at https://osf.io/uebvj/. | infectious diseases |
10.1101/2020.04.24.20078808 | Reacting to outbreaks at neighboring localities | We study the dynamics of epidemics in a networked metapopulation model. In each subpopulation, representing a locality, the disease propagates according to a modified susceptible-exposed-infected-recovered (SEIR) dynamics. In the modified SEIR dynamics, individuals reduce their number of contacts as a function of the weighted sum of cumulative number of cases within the locality and in neighboring localities. We consider a scenario with two localities where disease originates in one locality and is exported to the neighboring locality via travel of exposed (latently infected) individuals. We establish a lower bound on the outbreak size at the origin as a function of the speed of spread. Using the lower bound on the outbreak size at the origin, we establish an upper bound on the outbreak size at the importing locality as a function of the speed of spread and the level of preparedness for the low mobility regime. We evaluate the critical levels of preparedness that stop the disease from spreading at the importing locality. Finally, we show how the benefit of preparedness diminishes under high mobility rates. Our results highlight the importance of preparedness at localities where cases are beginning to rise such that localities can help stop local outbreaks when they respond to the severity of outbreaks in neighboring localities. | epidemiology |
10.1101/2020.04.24.20078949 | Reconstructed diagnostic sensitivity and specificity of the RT-PCR test for COVID-19 | Real-time reverse transcription polymerase chain reaction (RT-PCR) targeting select genes of the SARS-CoV-2 RNA has been the main diagnostic tool in the global response to the COVID-19 pandemic. This study was aimed at the estimation of diagnostic sensitivity and specificity of the first RT-PCR test developed by China CDC in January 2020. The study design is a secondary analysis of published findings on 1014 patients in Wuhan, China, of whom 59.3% tested positive for COVID-19 in RT-PCR tests and 87.6% tested positive in chest CT exams. We utilized previously ignored expert opinions in the form of verbal probability classifications of patients with conflicting test results to estimate the informative prior distribution of the infected proportion. It was then used in a Bayesian version of a previously developed model to reconstruct the sensitivity and specificity of the diagnostic tests without the need for specifying an inaccurate test as the gold standard. The sensitivity of the RT-PCR diagnostic test was estimated to be 0.707 (95% CI: 0.668, 0.749), while the specificity was 0.851 (95% CI: 0.774, 0.941). Caution is advised in generalizing these findings to other versions of the RT-PCR test that are being used in diverse geographic regions. | infectious diseases |
10.1101/2020.04.25.20079467 | Predicting the COVID-19 epidemic in Algeria using the SIR model | The aim of this study is to predict the daily infected cases with Coronavirus (COVID-19) in Algeria. We apply the SIR model on data from 25 February 2020 to 24 April 2020 for the prediction. Following Huang et al (12), we develop two SIR models, an optimal model and a model in a worst-case scenario COVID-19. We estimate the parameters of our models by minimizing the negative log likelihood function using the Nelder-Mead method. Based on the simulation of the two models, the epidemic peak of COVID-19 is predicted to attain 24 July 2020 in a worst-case scenario, and the COVID-19 disease is expected to disappear in the period between September 2020 and November 2020 at the latest. We suggest that Algerian authorities need to implement a strict containment strategy over a long period to successfully decrease the epidemic size, as soon as possible. | epidemiology |
10.1101/2020.04.26.20080762 | Mathematical Modeling of Listeriosis Incorporating Effects of Awareness Programs | Awareness programs by the media play a pivotal role in the control of infectious diseases. In this paper, we formulate and analyse a mathematical model for listeriosis incorporating aware individuals. Mathematical analyses of the model are done and equilibrium points determined. The model has three equilibria; namely; the disease-free, the bacteria-free, and the endemic equilibria. Local asymptotic stability of the equilibria is established based on the food contamination number [R]f. Numerical simulations are carried out and the effects of various parameters on the model state variables investigated. The results from numerical simulations reveal that an increase in the efficacy of awareness programs, the rate of implementation of awareness programs, and the rate at which unaware susceptible become aware result in the reduction of listeriosis in the human population. The results have important implications in the control and management of listeriosis. | infectious diseases |
10.1101/2020.04.26.20080820 | Knowledge, attitudes, and practices (KAP) towards COVID-19: A quick online cross-sectional survey among Tanzanian residents. | BackgroundThe Corona Virus Disease -19 (COVID-19) pandemic is a global health emergency that requires the adoption of unprecedented measures to control its rapid spread. Tanzanians adherence to control measures is affected by their knowledge, attitudes, and practices (KAP) towards the disease. This study was carried out to investigate knowledge, attitudes and practices towards COVID-19 among residents in Tanzania during the April - May 2020 period of the epidemic.
MethodsThis cross-sectional study analyzes responses of self-selected Tanzanians who responded to an invitation to complete an online questionnaire. Survey Monkey tool was used to develop the questionnaire used for data collection. The survey assessed demographic characteristics of participants as well as their knowledge, attitudes, and practices toward COVID-19. A Chi-square analysis was used to compare proportions. Analysis of variance (ANOVA) was used to determine differences among age groups, whereas results were considered significant if the p-value was <0.05
ResultsFour hundred residents completed the survey. The mean age of study participants was 32 years, and the majority was female (n= 216,54.0%). There were no significant differences in demographic variables). Participants with a bachelors degree or above (n= 241, 60.3%) had higher scores. Overall, 84.4% (n=338) of participants had good knowledge, which was significantly associated with education level (p=0.001). Nearly all participants (n=384, 96.0%) had confidence that COVID-19 will be eliminated. The majority of respondents (n=308, 77.0%) did not go to a crowded place in recent days. Multiple linear regression analysis showed that males, age-group 16-29 years, and education of secondary or lower (OR = 1.2, CI = 1.3-1.5) were significantly associated with lower knowledge score.
ConclusionsOur findings revealed good knowledge, optimistic attitudes, and appropriate practices towards preventing COVID-19 infection. Suggesting that community-based health education programs about COVID-19 is helpful and necessary to control the disease. | infectious diseases |
10.1101/2020.04.27.20075531 | Indications that Chymotrypsin-like Elastase 1 is Involved in Emphysema | Emphysema is a major contributor to the morbidity and mortality of chronic obstructive pulmonary disease (COPD), and there are no disease modifying therapies. Three leading pathophysiologic models are the altered protease/antiprotease balance model, the biomechanical model in which loss of one alveolar wall increases strain on adjacent wall predisposing them to failure, and the accelerated aging model. Chymotrypsin-like elastase 1 (CELA1) is a novel serine protease with a physiological role in reducing postnatal lung elastance that mechanistically links these three models. CELA1 is expressed by alveolar type 2 (AT2) cells and is found adjacent to lung elastin fibers. The KF4 antibody neutralizes CELA1 by binding to its catalytic triad. CELA1 binding to lung elastin fibers increases 4-fold with strain, and application of biaxial strain induces lung elastase activity which is blocked with the KF4 anti-CELA1 antibody. Cela1-/- mice were protected from airspace simplification in hyperoxia, elastase and cigarette-smoke induced emphysema, and age-related airspace simplification. CELA1 mRNA was correlated with human lung elastolytic activity, and anti-CELA1 KF4 antibody protected mice from hyperoxia-induced alveolar simplification and elastase emphysema. CELA1-mediated lung matrix remodeling in response to strain is an important contributor to postnatal airspace simplification. Matrix stabilization by KF4 represents a potential therapeutic approach to preventing emphysema progression.
One Sentence SummaryNeutralization of chymotrypsin-like elastase 1 prevents strain-induced emphysema. | respiratory medicine |
10.1101/2020.04.27.20075531 | Anti-CELA1 KF4 Antibody Prevents Emphysema by Inhibiting Stretch-Mediated Remodeling | Emphysema is a major contributor to the morbidity and mortality of chronic obstructive pulmonary disease (COPD), and there are no disease modifying therapies. Three leading pathophysiologic models are the altered protease/antiprotease balance model, the biomechanical model in which loss of one alveolar wall increases strain on adjacent wall predisposing them to failure, and the accelerated aging model. Chymotrypsin-like elastase 1 (CELA1) is a novel serine protease with a physiological role in reducing postnatal lung elastance that mechanistically links these three models. CELA1 is expressed by alveolar type 2 (AT2) cells and is found adjacent to lung elastin fibers. The KF4 antibody neutralizes CELA1 by binding to its catalytic triad. CELA1 binding to lung elastin fibers increases 4-fold with strain, and application of biaxial strain induces lung elastase activity which is blocked with the KF4 anti-CELA1 antibody. Cela1-/- mice were protected from airspace simplification in hyperoxia, elastase and cigarette-smoke induced emphysema, and age-related airspace simplification. CELA1 mRNA was correlated with human lung elastolytic activity, and anti-CELA1 KF4 antibody protected mice from hyperoxia-induced alveolar simplification and elastase emphysema. CELA1-mediated lung matrix remodeling in response to strain is an important contributor to postnatal airspace simplification. Matrix stabilization by KF4 represents a potential therapeutic approach to preventing emphysema progression.
One Sentence SummaryNeutralization of chymotrypsin-like elastase 1 prevents strain-induced emphysema. | respiratory medicine |
10.1101/2020.04.27.20081893 | Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold | Individual variation in susceptibility and exposure is subject to selection by natural infection, accelerating the acquisition of immunity, and reducing herd immunity thresholds and epidemic final sizes. This is a manifestation of a wider population phenomenon known as "frailty variation". Despite theoretical understanding, public health policies continue to be guided by mathematical models that leave out considerable variation and as a result inflate projected disease burdens and overestimate the impact of interventions. Here we focus on trajectories of the coronavirus disease (COVID-19) pandemic in England and Scotland until November 2021. We fit models to series of daily deaths and infer relevant epidemiological parameters, including coefficients of variation and effects of non-pharmaceutical interventions which we find in agreement with independent empirical estimates based on contact surveys. Our estimates are robust to whether the analysed data series encompass one or two pandemic waves and enable projections compatible with subsequent dynamics. We conclude that vaccination programmes may have contributed modestly to the acquisition of herd immunity in populations with high levels of pre-existing naturally acquired immunity, while being critical to protect vulnerable individuals from severe outcomes as the virus becomes endemic.
Graphical Abstract
O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC="FIGDIR/small/20081893v5_ufig1.gif" ALT="Figure 1">
View larger version (19K):
org.highwire.dtl.DTLVardef@aeb87forg.highwire.dtl.DTLVardef@d2c441org.highwire.dtl.DTLVardef@152aeceorg.highwire.dtl.DTLVardef@1526779_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIVariation in susceptibility/exposure responds to selection by natural infection
C_LIO_LISelection on susceptibility/exposure flattens epidemic curves
C_LIO_LIModels with incomplete heterogeneity overestimate intervention impacts
C_LIO_LIIndividual variation lowered the natural herd immunity threshold for SARS-CoV-2
C_LI | epidemiology |
10.1101/2020.04.27.20081893 | Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold | Individual variation in susceptibility and exposure is subject to selection by natural infection, accelerating the acquisition of immunity, and reducing herd immunity thresholds and epidemic final sizes. This is a manifestation of a wider population phenomenon known as "frailty variation". Despite theoretical understanding, public health policies continue to be guided by mathematical models that leave out considerable variation and as a result inflate projected disease burdens and overestimate the impact of interventions. Here we focus on trajectories of the coronavirus disease (COVID-19) pandemic in England and Scotland until November 2021. We fit models to series of daily deaths and infer relevant epidemiological parameters, including coefficients of variation and effects of non-pharmaceutical interventions which we find in agreement with independent empirical estimates based on contact surveys. Our estimates are robust to whether the analysed data series encompass one or two pandemic waves and enable projections compatible with subsequent dynamics. We conclude that vaccination programmes may have contributed modestly to the acquisition of herd immunity in populations with high levels of pre-existing naturally acquired immunity, while being critical to protect vulnerable individuals from severe outcomes as the virus becomes endemic.
Graphical Abstract
O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC="FIGDIR/small/20081893v5_ufig1.gif" ALT="Figure 1">
View larger version (19K):
org.highwire.dtl.DTLVardef@aeb87forg.highwire.dtl.DTLVardef@d2c441org.highwire.dtl.DTLVardef@152aeceorg.highwire.dtl.DTLVardef@1526779_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIVariation in susceptibility/exposure responds to selection by natural infection
C_LIO_LISelection on susceptibility/exposure flattens epidemic curves
C_LIO_LIModels with incomplete heterogeneity overestimate intervention impacts
C_LIO_LIIndividual variation lowered the natural herd immunity threshold for SARS-CoV-2
C_LI | epidemiology |
10.1101/2020.04.28.20079582 | Predicted impact of the COVID-19 pandemic on global tuberculosis deaths in 2020 | Policies widely adopted in response to the ongoing pandemic of Covid-19, particularly lockdowns and reassignments of health personnel and equipment, are impacting the performance of TB prevention and care programmes. Estimates of the impact of reductions in the performance of global TB detection and care on TB mortality over 2020 are presented. A global TB case detection decrease by an average 25% over a period of 3 months (as compared to the level of detection before the pandemic), will lead to a predicted additional 190 000 (56 000 - 406 000) TB deaths. | epidemiology |
10.1101/2020.04.28.20080630 | Cohort Profile: A national prospective cohort study of SARS-CoV-2 pandemic outcomes in the U.S. - The CHASING COVID Cohort Study | PurposeThe CHASING COVID Cohort study is a U.S.-based prospective cohort study launched during the upswing of the U.S. COVID-19 epidemic. The objectives are to: 1) estimate and evaluate determinants of the cumulative incidence of SARS-CoV-2 infection, disease, and deaths; 2) assess the impact of the pandemic on psychosocial and economic outcomes; and 3) assess the uptake of pandemic mitigation strategies.
ParticipantsWe began enrolling participants March 28, 2020 using internet-based strategies. Adults [≥]18 years residing anywhere in the U.S. or U.S. territories were eligible. 6,753 people are enrolled in the cohort, including participants from all 50 U.S. states, the District of Columbia, Puerto Rico, and Guam. Participants are contacted regularly to complete study assessments, including interviews and specimen collection.
Findings to dateOf 4,247 participants who provided a specimen for baseline serologic testing, 135 were seropositive by screening antibody testing (3.2%, 95% CI 2.7%-3.5%) and 90 were seropositive by confirmatory antibody testing (2.1%, 95% CI 1.7%-2.6%). Cohort data have been used to assess the role of household crowding and the presence of children in the household as potential risk factors for severe COVID-19 early in the U.S. pandemic; to describe the prevalence of anxiety symptoms and its relationship to COVID-19 outcomes and other potential stressors; and to identify preferences for SARS-CoV-2 diagnostic testing when community transmission is on the rise via a discrete choice experiment.
Future plansThe CHASING COVID Cohort Study has outlined a research agenda that involves ongoing monitoring of the cumulative incidence and determinants of SARS-CoV-2 outcomes, mental health outcomes and economic outcomes. Additional priorities include COVID-19 vaccine hesitancy, uptake and effectiveness; incidence, prevalence and correlates of long-haul COVID-19; and the extent and duration of the protective effect of SARS-CoV-2 antibodies. | infectious diseases |
10.1101/2020.05.04.20082081 | ai-corona: Radiologist-Assistant Deep Learning Framework for COVID-19 Diagnosis in Chest CT Scans | Generation of medical assisting tools using recent artificial intelligence advances is beneficial for the medical workers in the global fight against COVID-19 outbreak. In this article we introduce ai-corona, a radiologist-assistant deep learning framework for COVID-19 infection diagnosis using the chest CT scans. Our framework incorporates an Efficient NetB3-based feature extractor. We employed three independent dataset in this work named: CC-CCII, MDH, and MosMedData; all includes 7184 scans from 5693 subjects which contained pneumonia, common pneumonia (CP), non-pneumonia, normal and COVID-19 classes. We evaluated ai-corona on test sets from the CC-CCII set and MDH cohort and the entirety of the MosMedData cohort, for which it gained AUC score of 0.997, 0.989, and 0.954, respectively. We further compared our frameworks performance with other deep learning models developed on our employed data sets, as well as RT-PCR. Our results show that ai-corona outperforms all. Lastly, our frameworks diagnosis capabilities was evaluated as assistant to several experts. We demonstrated an increase in both speed and accuracy of expert diagnosis when incorporating ai-coronas assistance. | health informatics |
10.1101/2020.04.29.20084707 | Pandemic Lock-down, Isolation, and Exit Policies Based on Machine Learning Predictions | The widespread lockdowns imposed in many countries at the beginning of the COVID-19 pandemic elevated the importance of research on pandemic management when medical solutions such as vaccines are unavailable. We present a framework that combines a standard epidemiological SEIR (susceptible-exposed-infected-removed) model with an equally standard machine learning classification model for clinical severity risk, defined as an individuals risk needing intensive care unit (ICU) treatment if infected. Using COVID-19-related data and estimates for France as of spring 2020, we then simulate isolation and exit policies. Our simulations show that policies considering clinical risk predictions could relax isolation restrictions for millions of the lowest-risk population months earlier while consistently abiding by ICU capacity restrictions. Exit policies without risk predictions, meanwhile, would considerably exceed ICU capacity or require the isolation of a substantial portion of population for over a year in order to not overwhelm the medical system. Sensitivity analyses further decompose the impact of various elements of our models on the observed effects.
Our work indicates that predictive modelling based on machine learning and artificial intelligence could bring significant value to managing pandemics. Such a strategy, however, requires governments to develop policies and invest in infrastructure to operationalize personalized isolation and exit policies based on risk predictions at scale. This includes health data policies to train predictive models and apply them to all residents, as well as policies for targeted resource allocation to maintain strict isolation for high-risk individuals. | epidemiology |
10.1101/2020.04.29.20085506 | Beyond Deaths per Capita: Comparative CoViD-19 Mortality Indicators | The number of CoViD-19 deaths more reliably tracks the progression of the disease across populations than the number of confirmed cases, but substantial age and sex differences in CoViD-19 mortality imply that the number of deaths should be adjusted for the age-and-sex composition of the population as well as its total size. Following well-established practices in demography, this article discusses several measures based on the cumulative number of CoViD-19 deaths and illustrate them with data from 362 national and subnational populations. The first measure is an unstandardized occurrence/exposure rate comparable to the Crude Death Rate. To date, we measured the highest value in New York, exceeding at its peak the states most recent annual Crude Death Rate. The second measure is an indirectly standardized rate which we show to perform quite like a directly standardized rate but without requiring a breakdown of CoViD-19 deaths by age and sex. Either way, standardization substantially modifies comparisons across populations: New Jersey has the highest unstandardized rate to date, but four states in Mexico and one in Brazil have higher standardized rates. Finally, extant life tables allow to estimate reductions in 2020 life expectancies, which are projected to exceed two years for New York, New Jersey and Peru, and possibly three years in Ecuador. To put these in perspective, with a 1.1-year projected reduction, the US life expectancy at birth should have in 2020 its largest annual decline since World War II and reach its lowest level since 2006. | infectious diseases |
10.1101/2020.04.29.20085571 | Lack of Evidence for a Reduced Late Positive Potential in Major Depressive Disorder | BackgroundIndividuals with major depressive disorder (MDD) present with deficits in emotional reactivity. Conflicting models have been proposed to explain this effect. We sought to test the emotional context insensitivity hypothesis, which suggests that reactivity to positive and negatively-valenced emotional stimuli is blunted in depression, in a preregistered study.
MethodsForty-one depressed participants and 41 age- and gender-matched healthy controls were presented a series of unpleasant and neutrally-valenced pictures in a passive view paradigm while acquiring electroencephalography (EEG). The late positive potential (LPP), an EEG correlate of emotional reactivity, was compared between groups using mixed-effects repeated-measures models and exploratory cluster-based permutation tests. A sensitivity analysis was performed to assess the robustness of LPP findings by reanalysing the LPPs using 22 EEG pipelines from studies identified in the literature.
ResultsWe found no difference in LPP amplitudes between MDD and healthy individuals using the preregistered analysis pipeline. The sensitivity analysis revealed that the magnitude and direction of LPP effect sizes were affected by the analysis pipeline. Exploratory permutation analyses revealed an electrode cluster that showed a significant reduction in the LPP for MDD participants while viewing unpleasant pictures.
ConclusionsThese results do not provide evidence in support of the emotional context insensitivity hypothesis, except for the exploratory data-driven approach. Methodological differences, in particular in the analysis pipeline, contribute to the heterogeneity of LPP modulation in depression. A standardised approach to quantify EEG correlates of emotional reactivity is needed to evaluate alternative models of emotional reactivity in depression. | psychiatry and clinical psychology |
10.1101/2020.05.01.20086801 | Using viral load and epidemic dynamics to optimize pooled testing in resource constrained settings | Extensive virological testing is central to SARS-CoV-2 containment, but many settings face severe limitations on testing. Group testing offers a way to increase throughput by testing pools of combined samples; however, most proposed designs have not yet addressed key concerns over sensitivity loss and implementation feasibility. Here, we combine a mathematical model of epidemic spread and empirically derived viral kinetics for SARS-CoV-2 infections to identify pooling designs that are robust to changes in prevalence, and to ratify losses in sensitivity against the time course of individual infections. Using this framework, we show that prevalence can be accurately estimated across four orders of magnitude using only a few dozen pooled tests without the need for individual identification. We then exhaustively evaluate the ability of different pooling designs to maximize the number of detected infections under various resource constraints, finding that simple pooling designs can identify up to 20 times as many positives compared to individual testing with a given budget. We illustrate how pooling affects sensitivity and overall detection capacity during an epidemic and on each day post infection, finding that sensitivity loss is mainly attributed to individuals sampled at the end of infection when detection for public health containment has minimal benefit. Crucially, we confirm that our theoretical results can be accurately translated into practice using pooled human nasopharyngeal specimens. Our results show that accounting for variation in sampled viral loads provides a nuanced picture of how pooling affects sensitivity to detect epidemiologically relevant infections. Using simple, practical group testing designs can vastly increase surveillance capabilities in resource-limited settings. | epidemiology |
10.1101/2020.05.01.20087833 | Spatial Inequities in COVID-19 Testing, Positivity, Confirmed Cases and Mortality in 3 US Cities: an Ecological Study | BackgroundPreliminary evidence has shown inequities in COVID-19 related cases and deaths in the US.
ObjectiveWe explored the emergence of spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in New York City, Philadelphia, and Chicago during the first six months of the pandemic.
DesignEcological, observational study at the zip code tabulation area (ZCTA) level from March to September 2020.
SettingChicago, New York City and Philadelphia.
ParticipantsAll populated ZCTAs in the three cities.
MeasuresOutcomes were ZCTA-level COVID-19 testing, positivity, confirmed cases, and mortality cumulatively through the end of September. Predictors were the CDC social vulnerability index and its four domains, obtained from the 2014-2018 American Community Survey. We examined the spatial autocorrelation of COVID-19 outcomes using global and local Morans I and estimated associations using spatial conditional autoregressive negative binomial models.
ResultsWe found spatial clusters of high and low positivity, confirmed cases and mortality, co-located with clusters of low and high social vulnerability. We also found evidence for the existence of spatial inequities in testing, positivity, confirmed cases and mortality for the three cities. Specifically, neighborhoods with higher social vulnerability had lower testing rates, higher positivity ratios, confirmed case rates and mortality rates.
LimitationsZCTAs are imperfect and heterogeneous geographical units of analysis. We rely on surveillance data, which may be incomplete.
ConclusionWe found spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in three large cities of the US.
RegistrationN/A
Funding sourceNIH (DP5OD26429) and RWJF (77644) | epidemiology |
10.1101/2020.05.01.20087833 | Spatial Inequities in COVID-19 Testing, Positivity, Confirmed Cases and Mortality in 3 US Cities: an Ecological Study | BackgroundPreliminary evidence has shown inequities in COVID-19 related cases and deaths in the US.
ObjectiveWe explored the emergence of spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in New York City, Philadelphia, and Chicago during the first six months of the pandemic.
DesignEcological, observational study at the zip code tabulation area (ZCTA) level from March to September 2020.
SettingChicago, New York City and Philadelphia.
ParticipantsAll populated ZCTAs in the three cities.
MeasuresOutcomes were ZCTA-level COVID-19 testing, positivity, confirmed cases, and mortality cumulatively through the end of September. Predictors were the CDC social vulnerability index and its four domains, obtained from the 2014-2018 American Community Survey. We examined the spatial autocorrelation of COVID-19 outcomes using global and local Morans I and estimated associations using spatial conditional autoregressive negative binomial models.
ResultsWe found spatial clusters of high and low positivity, confirmed cases and mortality, co-located with clusters of low and high social vulnerability. We also found evidence for the existence of spatial inequities in testing, positivity, confirmed cases and mortality for the three cities. Specifically, neighborhoods with higher social vulnerability had lower testing rates, higher positivity ratios, confirmed case rates and mortality rates.
LimitationsZCTAs are imperfect and heterogeneous geographical units of analysis. We rely on surveillance data, which may be incomplete.
ConclusionWe found spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in three large cities of the US.
RegistrationN/A
Funding sourceNIH (DP5OD26429) and RWJF (77644) | epidemiology |
10.1101/2020.05.02.20087544 | Evaluating growth pattern and assessing future scenario of COVID-19 epidemic of India | COVID-19 the modern pandemic has spread across the world at a rapid pace. SARS-CoV 2 is highly transmissible and the rate of infection is exponential for heavily infected countries. Asymptotic carriers and longer incubation period have been key towards such a large-scale distribution of disease. Data released by official authorities on COVID-19 cases is significantly affected by various factors such as size of sample, incubation period of disease and time taken to test the sample. These factors mask the useful pattern (signal) of disease spread. Thus, an ingenious method to group data into cycles of five and seven days, for studying pattern of disease spread is undertaken. Occurrence of recurrent peaks as indicated by Adjusted Rate of infection per day indicated the spread of disease has been non-uniform. Currently, India is yet to reach the critical point (peak of epidemic) with adjusted daily cases more than 1000. Increasing testing capacity along with random sampling and sample pooling can help in preventing formation of these peaks in future. The proposed method helps in assessing the current state and for predicting future scenarios epidemics. | epidemiology |
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