bluuebunny/crossref_metadata_2025 huggingface dataset:
EVALUATION OF THE SAFETY AND TOLERABILITY OF EXOGENOUS KETOSIS INDUCED BY ORALLY ADMINISTERED FREE BETA-HYDROXYBUTYRATE IN HEALTHY ADULT SUBJECTS
Authors: Pimentel-Suarez Lisa Isabel , Soto-Mota Luis Adrian
Published: June 2023

Beta-hydroxybutyrate (D-BHB) is a metabolite with intrinsic signalling activity that has gained attention as a potentially clinically useful supplement. There are available supplements for inducing ketosis: ketone salts, ketone esters, and medium-chain triglycerides. Even when all of them raise the beta-hydroxybutyrate in the blood and all are safe and well tolerated, they significantly differ in their safety profile, their palatability, and their price. A fourth and potentially interesting option is to use biologically identical beta-hydroxybutyrate, while it is already commercially available in the United States (American Ketone LLC) and Greater China (MedPHA Ltd). However, its safety and tolerability had not yet been documented in the scientific literature. We evaluated the safety and tolerability of orally administered Free D-BHB in a gender and age-balanced sample of 24 asymptomatic and overtly healthy adults. No participant showed acid-base abnormalities or electrolyte abnormalities. Secondary symptoms were reported after only 6.2% of all drink takes and none of the reports described the symptom as “severe”. The most frequently reported secondary effects (19/720 or 2.6%) were gastrointestinal discomfort, headache (7/720 or 1%), and loss of appetite (7/720 or 1%). No correlation between weight-adjusted dose and frequency of secondary symptoms was observed. Free D-BHB was a safe and well-tolerated intervention for inducing sustained exogenous ketosis. Being bio-identical, salt-free, and lacking intermediate metabolites, this form of supplementation could have a larger safety spectrum than salt or alcohol-based exogenous ketones. More research is warranted to assess its clinical efficacy in those clinical scenarios in which achieving ketosis rapidly could be beneficial.

KEY MESSAGES

What is already known on this topic

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Ketogenic supplements could be useful therapeutic tools in certain time-sensitive circumstances. A previously unexplored but attractive option is using bio-identical D-BHB.

What this study adds

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Diluted Free D-BHB is a safe and well-tolerated intervention for inducing sustained exogenous ketosis.

How this study might affect research, practice, or policy

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Being bio-identical, salt-free, further research is warranted on the potential clinical uses of Free-BHB.
Visualising candidate behaviour in computer-based testing: UsingClickMapsfor exploringClickStreamsin undergraduate and postgraduate medical examinations
Authors: McManus I. C. , Chis Liliana , Ferro Albert , Oram S. Helen , Galloway James , O’Neill Vikki , Myers Gil , Sturrock Alison
Published: June 2023

Background

The rapid introduction of computer-based testing (CBT) in UK (United Kingdom) undergraduate and postgraduate medical education, mainly as a result of the COVID-19 pandemic, has generated large amounts of examination data, which we call theClickStream. As candidates navigate through exams, read questions, view images, choose answers and sometimes change answers and return, re-read, and make further changes, the multiple actions are recorded as a series of time-stamped clicks or keystrokes. Analysing that mass of data is far from simple, and here we describe the creation ofClickMaps, which allow examiners, educationalists and candidates to visualise behaviour in examinations.

Methods

As an example ofClickMaps, we describe data from a single examination lasting three hours, with 100 ‘best-of-five’ questions, which was one of two papers sat in 2021 by 508 candidates as a part of the MRCP(UK) Part 2 exam. TwoClickMapswere generated for each candidate. TheFull ClickMapallows the complete three-hours of the examination to be visualised, while theEarly ClickMap, shows in more detail how candidates responded during the first six minutes of presentation of each of the 100 questions in the exam.

Results

Since the primary purpose of this paper is expository, detailed descriptions and examples ofClickMapsfrom eleven candidates were chosen to illustrate different patterns of responding, both common and rare, and to show how straightforward areClickMapsto read and interpret.

Conclusions

The richness of the data inClickStreamsallows a wide range of practical and theoretical questions to be asked about how candidates behave in CBTs, which are considered in detail.ClickMapsmay also provide a useful method for providing detailed feedback to candidates who have taken CBTs, not only of their own behaviour but also for comparison with different strategies used by other candidates, and the possible benefits and problems of different approaches. In research terms, educationalists urgently need to understand how differences inClickMapsrelate to differences in student characteristics and overall educational performance.
Lower Dynamic Cerebral Autoregulation following Acute Bout of Low-Volume High-Intensity Interval Exercise in Chronic Stroke Compared to Healthy Adults
Authors: Whitaker Alicen A. , Aaron Stacey E. , Chertoff Mark , Brassard Patrice , Buchanan Jake , Nguyen Katherine , Vidoni Eric D. , Waghmare Saniya , Eickmeyer Sarah M. , Billinger Sandra A.
Published: June 2023

Fluctuating blood pressure during high-intensity interval exercise (HIIT) may challenge dynamic cerebral autoregulation (dCA), specifically post-stroke after an injury to the cerebrovasculature. We hypothesized dCA would be attenuated at rest and during a sit-to-stand, immediately following and 30 min after HIIT in individuals post-stroke compared to age- and sex-matched controls (CON). HIIT switched every minute between 70% and 10% estimated maximal watts for 10 min. Mean arterial pressure (MAP) and middle cerebral artery blood velocity (MCAv) were recorded. Resting dCA measured spontaneous fluctuations in MAP and MCAv via transfer function analysis. For sit-to-stand, time delay before an increase in cerebrovascular conductance index (CVCi = MCAv/MAP), rate of regulation, and %change in MCAv and MAP were measured. Twenty-two individuals post-stroke (age 60±12 yrs, 31±16 months) and twenty-four CON (age 60±13 yrs) completed the study. VLF gain (p=0.02, η2=0.18) and normalized gain (p=0.01, η2=0.43) had a group-by-time interaction, with CON improving immediately and 30 min after HIIT. Individuals post-stroke had impaired VLF phase (p=0.03, η2=0.22) immediately following HIIT compared to CON. We found no differences in the sit-to-stand. Our study showed lower resting dCA up to 30 min after HIIT in individuals post-stroke compared to CON while the sit-to-stand response was maintained.
Apixaban drug level monitoring in hemodialysis
Authors: Schietzel Simeon , Limacher Andreas , Moor Matthias B. , Czerlau Cecilia , Vogt Bruno , Aregger Fabienne , Uehlinger Dominik E.
Published: June 2023

Background

Apixaban is increasingly being used in hemodialysis patients. However, uncertainty remains regarding appropriate dosing and risk of accumulation.

Methods

We analyzed apixaban drug levels from a tertiary care dialysis unit collected between August 2017 and January 2023. We compared 2.5 mg once versus twice daily dosing. We applied mixed-effects models analyses including dialysis modality, adjusted standard Kt/V, ultrafiltration and dialyzer characteristics.

Results

We analyzed 143 apixaban drug levels from 24 patients. Mean (SD) age was 64.2 (15.3) years (45.2% female), median (IQR) follow up 12.5 (5.5 - 21) months. For the 2.5 mg once and twice daily groups, median (IQR) drug levels were 54.4 (< 40 - 72.1) and 71.3 (48.8 - 104.1) ng/mL (P < 0.001). Drug levels were below the detection limit in 30 % and 14 %. Only dosing group (twice versus once daily) was independently associated with higher drug levels (P = 0.002). Follow-up did not suggest accumulation. 95thpercentile did not exceed those of non-CKD populations taking 5 mg twice daily. Drug levels before a bleeding (8 episodes) were significantly higher than those without a subsequent bleeding: 115 (SD 51.6) versus 65.9 (SD 31.6) ng/mL (P < 0.001). Patients with versus without a bleeding took concomitant antiplatelet therapy in 86% versus 6% (P < 0.001). In 21% of patients, drug level monitoring resulted in change of dosing.

Conclusion

Apixaban drug monitoring might be a contributory tool to increase safety in patients on hemodialysis. Further prospective outcome studies are warranted to investigate possible target levels.
Real-life course and effectiveness of melatonin treatment for sleep disturbances in children with autism spectrum disorder
Authors: Sadeh Hadar , Meiri Gal , Zigdon Dikla , Ilan Michal , Faroy Michal , Michaelovski Analya , Tsadaka Yair , Dinstein Ilan , Menashe Idan
Published: June 2023

Objective

Melatonin is considered the most effective pharmacological treatment for the sleep disturbances that are reported in >50% of children with autism spectrum disorder (ASD). However, real-life data about the long-term course and effectiveness of melatonin treatment in children with ASD is lacking.

Methods

In this retrospective cohort study, we assessed the adherence to melatonin treatment and its effect on sleep quality and daytime behavior in children with ASD via a parental phone questionnaire of children in the Azrieli National Center for Autism and Neurodevelopment Research (ANCAN) database. Cox regression analysis was used to assess the effect of key demographic and clinical characteristics on treatment adherence.

Results

Melatonin was recommended for ∼8% of children in the ANCAN database. These children were characterized by more severe autistic symptomatology. The median adherence time for melatonin treatment exceeded 88 months, with the most common reason for discontinuation being a lack of effectiveness (14%). Mild side-effects were reported in 14% of children, and 86%, 54%, and 45% experienced improvements in sleep onset, sleep duration and night awakenings, respectively. Notably, melatonin also improved the daytime behaviors of >28% of the children. Adherence to treatment was independently associated with improvements in night awakenings and educational functioning (aHR=0.142, 95%CI=0.036-0.565; and aHR=0.195, 95%CI=0.047-0.806, respectively).

Conclusions

Our findings highlight the real-life safety and effectiveness of melatonin treatment in children with ASD. Increasing the awareness of this treatment among families and health providers will help to reduce the burden associated with sleep disturbances in children with ASD and their families.
Pandemic Vaccination Strategies: Global Optimization
Authors: Thompson James , Benitez-Paez Fernando , Guerrero Omar
Published: June 2023

In the event of a global pandemic, caused by an infectious disease of humans, we consider the scenario in which a safe and effective vaccine is available, with limited supply. We then investigate the optimal distribution of doses across countries and age groups. We employ a system of SIR equations to model the pandemic dynamics and utilize genetic algorithms to identify optimal allocations that minimize either total infections or total deaths. Our findings reveal that strategies aimed at reducing infections differ from those aimed at reducing deaths, with neither strategy advocating proportional dose allocation between countries based on population size. Our findings moreover bring to light potential ethical challenges associated with the implementation of strategy optimization.
Experimental Device to Evaluate Aerosol Dispersion in Venues
Authors: Schulz Isabell , Hehnen Felix , Lausch Kevin Harry , Geisler Sophia Mareike , Hasirci Ümit , Wolff Sophia , Rese Tim , Schimek Sebastian , Lommel Michael , Paschereit Christian Oliver , Moritz Stefan , Kriegel Martin , Kertzscher Ulrich
Published: June 2023

The COVID-19 pandemic has focused attention to the importance of understanding and mitigating the airborne transmission of pathogens in indoor environments. This study investigated the aerosol distribution in different indoor venues with varying ventilation concepts, including displacement, mixed, and natural ventilation. A measurement system was developed to investigate venue-specific aerosol distribution patterns using a sodium chloride solution as a tracer. To analyse the spatial dispersion of aerosols, Computational Fluid Dynamics (CFD) simulations were conducted in addition to experimental investigations. The investigations indicated the lowest aerosol load for the venue with displacement ventilation and the highest for the natural ventilated venue. The measurement system developed in this study provides a useful tool for assessing the effectiveness of ventilation measures in reducing airborne transmission of pathogens in indoor environments. It also proved its wide range of applications, as it can be used in various sized and shaped indoor environments, with or without an audience.
Lockdowns and Selection Pressure: A Modelling Study
Authors: Thompson James , Wattam Stephen
Published: June 2023

Since COVID-19 was first identified in China in 2019, the SARS-CoV-2 virus has mutated and given rise to a large number of variants. A range of non-pharmaceutical interventions have been deployed against the virus in an effort to save lives and reduce pressure on health-care systems. These interventions may have favoured some variants over others. Despite this possibility, there has thus far been very little work investigating the impact of such interventions on the evolution of the virus.

Using mathematical and computational models, we investigate the impact of a lockdown specifically, for the case in which two SARS-CoV-2 variants are circulating simultaneously in a population. We find that under certain conditions, lockdowns disrupt the competition between variants in such a way that highly transmissible variants with long infectious periods are selected for, ultimately leading tomorecases overall than would have occurred without the lockdown, due to larger second waves of cases.

These are the results of a modelling study and we do not claim to have found evidence of such unfavourable selection effects occurring in reality. On the other hand, our results are consistent with evolutionary theory and suggest that the selective effects of non-pharmaceutical interventions deserve greater scrutiny.
Progressive lesion necrosis is related to increasing aphasia severity in chronic stroke
Authors: Johnson Lisa , Newman-Norlund Roger , Teghipco Alex , Rorden Chris , Bonilha Leonardo , Fridriksson Julius
Published: June 2023

Background

Volumetric investigations of cortical damage resulting from stroke indicate that lesion size and shape continue to change even in the chronic stage of recovery. However, the potential clinical relevance of continued lesion growth has yet to be examined. In the present study, we investigated the prevalence of lesion expansion and the relationship between expansion and changes in aphasia severity in a large sample of individuals in the chronic stage of aphasia recovery.

Methods

Retrospective structural MRI scans from 104 stroke survivors with at least 2 observations more than 6 months apart (k=301 observations) were included. Lesion demarcation was performed using an automated lesion segmentation software and lesion volumes at each timepoint were subsequently calculated. A paired-sample t-test between initial and final scans was conducted to determine if chronic lesion volumes change over time. Finally, we investigated the association between lesion expansion and changes on the Western Aphasia Battery (WAB) in a group of participants assessed and scanned at 2 timepoints (N=54) using a GLM.

Results

Most participants (81%) showed evidence of lesion expansion. A t-test revealed lesion volumes at follow-up scans were significantly larger than initial scans (p<0.0001).

Change on the language performance was significantly associated with change in lesion volume (p=0.025) and age at stroke (p=0.031). The results suggest that with every 100cm3increase in lesion size, language performance decreases by 8.8 points, and for every 10-year increase in age at stroke, language performance decreases by 1.9 points.

Conclusions

The present study confirms and extends prior reports that lesion expansion occurs well into the chronic stage of stroke. For the first time, we present evidence that expansion is predictive of longitudinal changes in language performance in individuals with aphasia. Future research should focus on the potential mechanisms that may lead to necrosis in areas surrounding the chronic stroke lesion.
Comparison of CT-Derived Plaque Characteristic Index with CMR Perfusion for Ischemia Diagnosis in Stable CAD
Authors: Guo Wei-feng , Xu Hai-jia , Lu Yi-ge , Qiao Guan-yu , Yang Shan , Zhao Shi-hai , Jin Hang , Dai Neng , Yao Zhi-feng , Yin Jia-sheng , Li Chen-guang , He Wei , Zeng Mengsu
Published: June 2023

Background

Coronary CT angiography (CCTA) and cardiac magnetic resonance (CMR) have been used to diagnose lesion-specific ischemia in patients with coronary artery disease (CAD).

Objective

The aim of this study was to investigate the diagnostic performance of CCTA-derived plaque characteristic index compared with myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) derived from CMR perfusion in the assessment of lesion-specific ischemia.

Methods

Between October 2020 and March 2022, consecutive patients with suspected or known CAD, who were clinically referred for ICA were prospectively enrolled. All participants sequentially underwent CCTA and CMR and invasive fractional flow reserve (FFR) within 2 weeks. The diagnostic performance of CCTA-derived plaque characteristics, CMR perfusion-derived stress MBF, and MPR were compared. Lesions with FFR ≤ 0.80 were considered to be hemodynamically significant stenosis.

Results

Nighty-two patients with 141 vessels were included in this study. Plaque length, minimum luminal area, plaque area, percent area stenosis, total atheroma volume, vessel volume, lipid rich volume, spotty calcium, napkin-ring signs, stress MBF and MPR in flow-limiting stenosis group were significantly different from non-flow limiting group. The overall accuracy, sensitivity, specificity, PPV, and NPV of lesion-specific ischemia diagnosis were 61.0%, 55.3%, 63.1%, 35.6%, 79.3% for stress MBF, and 89.4%, 89.5%, 89.3%, 75.6%, 95.8% for MPR, meanwhile 82.3%, 79.0%, 84.5%, 65.2%, 91.6% for CCTA-Derived plaque characteristic index.

Conclusion

In our prospective study, CCTA-derived plaque characteristics and MPR derived from CMR performed well in diagnosing lesion-specific myocardial ischemia, and were significantly better than stress MBF in stable coronary artery disease.
Food insecurity, adolescent suicidal thoughts and behaviours, and country-level context: a multi-country cross-sectional analysis
Authors: Steare Thomas , Lewis Gemma , Evans-Lacko Sara , Pitman Alexandra , Rose-Clarke Kelly , Patalay Praveetha
Published: June 2023

Background

Preventing adolescent suicide is a global priority. Inequalities in adolescent suicide and attempt rates are reported across countries, including a greater risk in adolescents experiencing food insecurity. Little is known about the extent to which country-level contextual factors moderate the magnitude of socio-economic inequalities in suicidal thoughts and behaviours. We aimed to examine the cross-country variability and national moderators of the association between food insecurity and suicidal thoughts and behaviours in school-attending adolescents.

Methods

We analysed data on 309,340 school-attending adolescents from 83 countries that participated in the Global School-based Student Health Survey between 2003 and 2018. We used Poisson regression to identify whether suicidal thoughts and behaviours were more prevalent in adolescents experiencing food insecurity compared to food-secure adolescents. Meta-regression and mixed-effects regression were used to determine whether country-level indicators moderated the magnitude of inequality.

Findings

Suicidal ideation, suicide planning and suicide attempts were more prevalent in food-insecure adolescents compared to food-secure adolescents in 72%, 78%, and 90% of countries respectively; however, the magnitude of these associations varied between countries. We observed wider inequalities in countries with greater levels of national wealth and universal health coverage and lower prevalence of adolescent food insecurity. Economic inequality had no moderating role.

Interpretation

Food insecurity could contribute to the development of adolescent suicidal thoughts and behaviours, and this association is likely to be moderated by country-level context. Food insecurity may be a modifiable target to help prevent adolescent suicide, especially in countries where food insecurity is less common.

Funding

Wellcome Trust.
Childhood maltreatment influences adult brain structure through its effects on immune, metabolic and psychosocial factors
Authors: Orellana Sofia C. , Bethlehem Richard A.I. , Simpson-Kent Ivan , van Harmelen Anne-Laura , Vértes Petra E. , Bullmore Edward T.
Published: June 2023

Childhood maltreatment (CM) leads to a lifelong susceptibility to mental ill-health which might be reflected by it’s effects on adult brain structure, perhaps indirectly mediated by its effects on adult metabolic, immune, and psychosocial systems. Indexing these systemic factors via body mass index (BMI), C-reactive protein (CRP) and rates of adult trauma (AT), respectively, we tested three hypotheses: (H1) CM has direct or indirect causal effects on adult trauma, BMI and CRP; (H2) adult trauma, BMI and CRP are all independently related to adult brain structure; and (H3) effects of CM on adult brain structure are mediated by its effects on adult trauma, BMI and CRP. Using path analysis and data from N=116,887 participants in UK Biobank we find that CM is related to greater BMI and AT levels, and that only these two variables mediate CM’s effects on CRP [H1]. Regression analyses on the UKB MRI sub-sample (N=21,738) revealed that greater CRP and BMI were both related to a spatially convergent pattern of cortical effects (Spearman’sρ=0.87) characterised by fronto-occipital increases and temporo-parietal reductions in thickness, and that AT is related to lower subcortical volumes [H2]. Finally, path models indicated that CM has indirect effects in a subset of brain regions through its influence on BMI, CRP and AT [H3]. Results provide evidence that childhood maltreatment can influence brain structure decades after exposure by increasing individual risk towards adult trauma, obesity or inflammation.
Identifying gaps in health literacy research through parental participation
Authors: Grepmeier Eva-Maria , Pöhnl Laura , von Sommoggy Julia , Pawellek Maja , Lander Jonas , Schulz Anja Alexandra , Hasenpusch Claudia , Schwalfenberg Anja , Dierks Marie-Luise , Bitzer Eva Maria , Apfelbacher Christian
Published: June 2023

Introduction

Involving patients and the public in design, conduct and dissemination of research has gained momentum in recent years. While methods to prioritize research on treatment uncertainties have been successfully applied for various disease entities, patient and public involvement has not been prominent to prioritize research in health literacy (HL). This study aimed to set up a participatory process on identifying HL research gaps from a parent’s perspective in two use cases: early childhood allergy prevention (ECAP) and COVID-19 in children with allergies (COVICAL).

Methods

To prepare and empower parents, we developed and provided preparatory webinars, introductory materials, i.e., factsheets and a brochure, and a scientific podcast with seven episodes. Recruitment was carried out by our cooperation partner German Allergy and Asthma Association e. V., via local day care centres and paediatricians as well as via snowballing. The identification of research gaps took place within five workshops with n= 55 participants, four face-to-face-workshops across Germany, one online workshop. Research ideas and needs were reviewed for overlap and redundancy and compared to the existing research state of the art.

Results

More than 150 initial research ideas and needs were collected which after review were reduced to a total of 37 ECAP, 33 COVICAL and 7 generic HL research questions. These were particularly related to the ease of finding and presenting good quality health information, information environment, health communication, professional education, and HL testing.

Conclusions

Involving parents in the formulation of HL research priorities proved to be challenging but feasible. Research ideas often reflect wishes directed at health professionals and the health system, i.e., organizational, and systemic HL. An e Delphi process will follow to elicit the TOP 10 research priorities in each use case. This project will help to plan patient/parent centred HL research in ECAP and COVICAL.

Plain Language Summary

We carried out a participatory HL research exercise to identify HL research gaps from a parent’s perspective. The aim was to learn about parents’/participants’ uncertainty in two use cases ECAP and COVICAL and what issues they would like to be answered by scientists. This resulted in a total of 37 ECAP, 33 COVICAL and 7 generic HL research questions.
AI-MET: A Deep Learning-based Clinical Decision Support System for Distinguishing Multisystem Inflammatory Syndrome in Children from Endemic Typhus
Authors: Bautista-Castillo Abraham , Chun Angela , Vogel Tiphanie P. , Kakadiaris Ioannis A.
Published: June 2023

Abstract

The COVID-19 pandemic brought several diagnostic challenges, including the post-infectious sequelae multisystem inflammatory syndrome in children (MIS-C). Some of the clinical features of this syndrome can be found in other pathologies such as Kawasaki disease, toxic shock syndrome, and endemic typhus. Endemic typhus, or murine typhus, is an acute infection treated much differently than MIS-C, so early detection is crucial to a favorable prognosis for patients with these disorders. Clinical Decision Support Systems (CDSS) are computer systems designed to support the decision-making of medical teams about their patients and intended to improve uprising clinical challenges in healthcare. In this article, we present a CDSS to distinguish between MIS-C and typhus that includes a scoring system that allows the timely distinction of both pathologies only using clinical and laboratory features typically available within the first six hours of presentation to the Emergency Department (ED). The proposed approach was trained and tested on datasets of 87 typhus patients and 133 MIS-C patients. A comparison was made against five well-known statistical and machine-learning models. A second dataset with 111 MIS-C patients was used to verify the AI-MET effectiveness and robustness. The performance assessment for AI-MET and the five statistical and machine learning models was done by computing Sensitivity, Specificity, Accuracy, and Precision. The AI-MET system scores 100 percent in the five metrics used on the training and testing dataset and 99 percent on the validation dataset.
Covid19Vaxplorer: a free, online, user-friendly COVID-19 Vaccine Allocation Comparison Tool
Authors: Trejo Imelda , Hung Pei-Yao , Matrajt Laura
Published: June 2023

Background

There are many COVID-19 vaccines currently available, however, Low- and middle-income countries (LMIC) still have large proportions of their populations unvaccinated. Decision-makers must decide how to effectively allocate available vaccines (e.g. boosters or primary series vaccination, which age groups to target) but LMIC often lack the resources to undergo quantitative analyses of vaccine allocation, resulting in adhoc policies. We developedCovid19Vaxplorer(https://covid19vaxplorer.fredhutch.org/), a free, user-friendly online tool that simulates region-specific COVID-19 epidemics in conjunction with vaccination with the purpose of providing public health officials worldwide with a tool for vaccine allocation planning and comparison.

Methods

We developed an age-structured mathematical model of SARS-CoV-2 transmission and COVID-19 vaccination. The model considers vaccination with up to three different vaccine products, primary series and boosters. We simulated partial immunity derived from waning of natural infection and vaccination. The model is embedded in an online tool,Covid19Vaxplorerthat was optimized for its ease of use. By prompting users to fill information through several windows to input local parameters (e.g. cumulative and current prevalence), epidemiological parameters (e.g basic reproduction number, current social distancing interventions), vaccine parameters (e.g. vaccine efficacy, duration of immunity) and vaccine allocation (both by age groups and by vaccination status).Covid19Vaxplorerconnects the user to the mathematical model and simulates, in real time, region-specific epidemics. The tool then produces key outcomes including expected numbers of deaths, hospitalizations and cases, with the possibility of simulating several scenarios of vaccine allocation at once for a side-by-side comparison.

Results

We provide two usage examples ofCovid19Vaxplorerfor vaccine allocation in Haiti and Afghanistan, which had as of Spring 2023 2% and 33% of their populations vaccinated, and show that for these particular examples, using available vaccine as primary series vaccinations prevents more deaths than using them as boosters. Covid19Vaxplorer allows users in 183 regions in the world to compare several vaccination strategies simultaneously, adjusting parameters to their local epidemics, infrastructure and logistics.Covid19Vaxploreris an online, free, user-friendly tool that facilitates evidence-based decision making for vaccine distribution.
Stacking multiple prediction models to optimise performance in local settings: exemplars in cardiometabolic disease
Authors: Ghosh Sreejita , Gratton Jasmine , Vermeulen Roel , Asselbergs Folkert , Vlaanderen Jelle J. , Schmidt A. Floriaan
Published: June 2023

Background

Risk prediction models are used in healthcare settings to tailor therapies to individuals most likely to benefit. Despite appropriate external validation, difference in local characteristics (e.g. patient mix) may attenuate model performance. Prior to any implementation it is therefore advisable to explore local performance, typically requiring a modest amount of historic data. Depending on model performance, model adjustments might be necessary which often require large amounts of data. Here we explore a small sample size approach approximating de novo derivation, by combining model stacking and transfer learning, referred to asstacked transfer learning. As an example we focus on stacking previously trained risk prediction models for cardiovascular disease (CVD), stroke, (chronic) kidney disease, and diabetes.

Methods

We leverage data from the UK biobank to illustrate the benefits of stacking previously trained risk prediction models, predicting the risk of incident CVD, chronic kidney disease (CKD) or diabetes. To mimic sample sizes available in local settings, such as a small to large healthcare trust, we iterated the number of training cases between 10 and 1000. Model stacking was performed using a LASSO penalized logistic regression model, and compared performance of ade novomodel estimating the local association of 33 variables used in the aforementioned risk prediction models.

Results

We found that stacked models require roughly one-tenths of the training sample size compared to de novo derivation of a prediction model. For example, predicting CVD the stacked model required 30 cases to reach a area under the curve (AUC) value (with 95% CI) of 0.732 (0.728, 0.735), while thede novomodel required 300 cases to reach approximately the same performance. As expected, the absolute performance depended on the predicted outcome, where for example the difference betweende novoand stacked modelling was smaller for CKD prediction.

Conclusion

We show that our proposed ”stacked transfer learning” approach closely approximated the predictive performance of ade novomodel, often requiring only a fraction of the data. As such, this approach should be considered when tailoring a model to a local setting.
Quantifiable identification of flow-limited ventilator dyssynchrony with the deformed lung ventilator model
Authors: Agrawal Deepak. K. , Smith Bradford J. , Sottile Peter D. , Hripcsak George , Albers David J.
Published: June 2023

Objective

Ventilator dyssynchrony (VD) is potentially harmful to patients with or at risk for acute respiratory distress syndrome (ARDS). In addition to injury solely caused by the ventilator, ventilator-induced lung injury may be instigated and exacerbated by patient respiratory efforts. Automated detection of VD from ventilator waveforms is challenging, and efforts have been made on a human-guided ML algorithm to detect some types of VD. We currently lack a methodological ability to define sub-breath phenotypes of VD that quantify severity anchored to physiologic understanding that could be used to relate VD to damage and guide ventilator management.

Materials and Methods

A mathematical model is developed that represents the pressure and volume waveform signals of a breath into several pathophysiological temporal features observed in ventilator waveforms and then deformation terms are added corresponding to hypothesized flow-limited (FL) dyssynchronous breaths. Model parameters are estimated at the resolution of a single breath using a deterministic, multivariate, constrained interior-point method to create a parametric representation of breaths. Differential estimates of different FL-VD breaths are used to create severity metrics for FL-VD breaths and their associations with the ventilator settings and healthcare interventions are analyzed.

Results

A total of 93,007 breaths were analyzed from the raw ventilator waveform dataset of 13 intensive care unit patients who met inclusion criteria. A quantitative method was developed to determine the continuously varying FL-VD severity for each breath and was successfully applied to a cohort of patient-ventilator waveform data. Additionally, cross-validation, using a previously developed ML categorical VD identification algorithm, produced an area under the receiver operator curve of 0.97.

Discussion & Conclusion

The VD-deformed lung ventilator (VD-DLV) model accurately detects FL-VD breaths and is able to quantify the severity of patient effort during patient-ventilator interaction. The presence and severity of deviations from normal are modeled in a way that is based on physiological hypotheses of lung damage and ventilator interactions. Therefore, the computed phenotypes have the predictive power to determine how the healthcare variables are associated with FL-VD breaths. This work paves the way for a large-scale study of VD causes and effects by identifying and quantifying VD breaths using the VD-DLV model.
Machine learning vs. traditional regression analysis for fluid overload prediction in the ICU
Authors: Sikora Andrea , Zhang Tianyi , Murphy David J. , Smith Susan E. , Murray Brian , Kamaleswaran Rishikesan , Chen Xianyan , Buckley Mitchell S. , Rowe Sandra , Devlin John W.
Published: June 2023

Background

Fluid overload, while common in the ICU and associated with serious sequelae, is hard to predict and may be influenced by ICU medication use. Machine learning (ML) approaches may offer advantages over traditional regression techniques to predict it. We compared the ability of traditional regression techniques and different ML-based modeling approaches to identify clinically meaningful fluid overload predictors.

Methods

This was a retrospective, observational cohort study of adult patients admitted to an ICU ≥ 72 hours between 10/1/2015 and 10/31/2020 with available fluid balance data. Models to predict fluid overload (a positive fluid balance ≥10% of the admission body weight) in the 48-72 hours after ICU admission were created. Potential patient and medication fluid overload predictor variables (n=28) were collected at either baseline or 24 hours after ICU admission. The optimal traditional logistic regression model was created using backward selection. Supervised, classification-based ML models were trained and optimized, including a meta-modeling approach. Area under the receiver operating characteristic (AUROC), positive predictive value (PPV), and negative predictive value (NPV) were compared between the traditional and ML fluid prediction models.

Results

A total of 49 of the 391 (12.5%) patients developed fluid overload. Among the ML models, the XGBoost model had the highest performance (AUROC 0.78, PPV 0.27, NPV 0.94) for fluid overload prediction. The XGBoost model performed similarly to the final traditional logistic regression model (AUROC 0.70; PPV 0.20, NPV 0.94). Feature importance analysis revealed severity of illness scores and medication-related data were the most important predictors of fluid overload.

Conclusion

In the context of our study, ML and traditional models appear to perform similarly to predict fluid overload in the ICU. Baseline severity of illness and ICU medication regimen complexity are important predictors of fluid overload.
Prospective population-based observational study to estimate the incidence of T2DM in a metropolitan population in the north of Madrid (Spain) and to determine the effect of baseline glycaemic status through an explanatory Cox model. SPRINDIAP-1 study (Secondary PRevention of INcident DIAbetes in patients with Prediabetes)
Authors: Iriarte-Campo V , de Burgos-Lunar C , Mostaza J , Lahoz C , Cárdenas-Valladolid J , Gómez-Campelo P , Taulero-Escalera B , San-Andrés-Rebollo FJ , Rodriguez-Artalejo F , Salinero-Fort MA ,   SPREDIA-2 Group
Published: June 2023

Background

T2DM (Type 2 Diabetes mellitus) is preceded by basal glycaemic states (BGS) such as normoglycaemia (NG) or pre-T2DM, including impaired fasting glucose (IFG); impaired glucose tolerance (IGT) or both (IFG-IGT). A better understanding of the role of pre-T2DM in the progression to T2DM may help in the prevention of T2DM in patients with pre-T2DM.

Methods

Population-based cohort study to estimate the incidence of T2DM according to BGS and to study the adjusted effect of BGS on progression to T2DM using a Cox model (main model (MM) with reference category NG and sensitivity analysis (SA) in patients with pre-T2DM and reference IFG).

Results

1,209 patients aged 45-74 years (median follow-up=7.26 years). The crude T2DM incidence rate for the whole population was 11.21 per 1000 person-years (95%CI=9.09-13.68), 5.60 (95%CI=3.55-8.41) in patients with NG and 16.28 (95%CI=12.78-20.43) in patients with preT2DM. In both models, the significant variables showing risk of progression to T2DM were IGT BGS (MM: Hazard ratio HR=4.30; 95%CI=1.96-9.44; AS: HR=2.66, 95%CI=1.28-5.56) and IFG-IGT (MM: HR=3.71, 95%CI=1.97-6.99; AS: HR=2.45, 95%CI=1.41-4.23), and obesity (MM: HR=2.36, 95%CI=1.15-4.83; AS: HR=2.97, 95%CI=1.18-7.45). Being on diuretic treatment was a protective factor (MM: HR=0.47 CI95%=0.23-0.96; SA: HR=0.41, CI95%=0.19-0.92), as was, in SA only, self-perceived health status in the categories of: Very good (HR: 0.19, CI95%=0.06-0.67); Good (HR: 0.35, CI95%=0.13-0.96) and Fair (HR: 0.31, CI95%=0.11-0.93).

Conclusions

Our T2DM incidence rates are in line with other Spanish studies. In people with NG or preT2DM, EBG (IGT and IFG-IGT) and obesity increase the risk of progression to T2DM and being on diuretics is a protective factor as is fair to very good self-perceived health in patients with preT2DM.
Environmental adversity moderates polygenic score effects on childhood behavioral problems in the United States
Authors: Thomas Taylor R. , Casten Lucas G. , Michaelson Jacob J.
Published: June 2023

IMPORTANCE

Behavioral problems in children are influenced by environmental and genetic factors, but it is still unclear how much each contributes and if there are gene-by-environment interactions (GxE).

OBJECTIVE

Our object was to investigate how environmental adversity moderates the effects of polygenic scores (PGS) on childhood behavioral problems through additive and interaction effects.

DESIGN, SETTING, AND PARTICIPANTS

Participants wereN= 7, 191 children aged 7-15 years (50% autistic) from two United States cohorts, ABCD and SPARK.

MAIN OUTCOMES AND MEASURES

The main outcomes were five dimensional subscales from the Child Behavior Checklist (CBCL). The genetic variables were 20 behavior-related PGS, including psychiatric diagnoses, substance use disorders, cognition, and personality PGS. Environmental adversity was estimated by the Area Deprivation Index (ADI). The ADI is a composite variable of neighborhood adversity based on education, income, and housing.

RESULTS

Thirteen out of the 20 PGS were significantly associated with the ADI. PGS for psychiatric and substance use disorders were positively associated with the ADI, and PGS for educational attainment and cognitive performance were negatively associated. The ADI had significant SNP heritability:h2= 0.33 [0.24, 0.42], with the estimate similar between ABCD and SPARK. The ADI was positively associated with more behavioral problems and explained more variance than any PGS, but this effect was reduced after accounting for these potential genetic confounders. Several GxE effects were identified, including: 1.) the positive associations of the cannabis and alcohol dependency PGS with externalizing problems increased as the ADI increased, 2.) the positive associations of the anorexia PGS with thought and internalizing problems increased as the ADI increased, 3.) the positive associations of the autism PGS with internalizing problems decreased as the ADI increased, 4.) the negative associations of the educational attainment and cognitive performance PGS with several behavioral problems increased as the ADI increased, and 5.) the extraversion PGS association with social problems was negative in an advantaged environment but positive in a disadvantaged environment.

CONCLUSIONS AND RELEVANCE

Environmental adversity estimated by the ADI moderates the effects of some PGS on childhood behavioral problems through additive and interaction effects. This highlights the importance of considering both genetic and environmental factors in understanding childhood behavioral problems. Our findings emphasize the need to include PGS of personality and cognitive traits, in addition to psychiatric PGS.
A coupled electro-mechanical approach for early diagnostic of carpal tunnel syndrome
Authors: Peshin Saveliy , Karakulova Julia , Kuchumov Alex G.
Published: June 2023

Carpal tunnel syndrome (CTS) is a pathology affecting hand function caused by median nerve overload. Numbness in the fingers, a loss of sensory and motor function in the hand, and pain are all symptoms of carpal tunnel syndrome. The lack of numerical data about the median nerve mechanical strain inside the carpal tunnel is the main disadvantage of current clinical approaches employed in carpal syndrome diagnostics. Moreover, application of each diagnostic method alone often leads to misdiagnosis. We proposed a combined approach including hand motion capture, finite element modelling (FEM), and electromechanical simulations to evaluate median nerve compression and find a correlation with hand mobility. The hand motion capture provided the boundary conditions for FEM. After that, FEM simulations of finger flexion and hand flexion / extension were performed. Further, FEM results were put in the electrical model of nerve conduction based on the Hodgkin-Huxley model and extended cable equation. It was exhibited median nerve conduction reduced significantly throughout the flexion and extension of the hand that compared to finger flexion. During finger flexion and hand flexion and extension, the load distribution over each of nine finger flexor tendons was evaluated. The tendons of the index finger were found to have the highest Mises stress values. It was found how tendon and connective tissue contact types affected carpal tunnel pressure. The difference between the contact types was 31.7% for hand extension and 59.9% for hand flexion. The developed approach has the potential to become an alternative diagnostic method for CTS at early stages. Additionally, it can be employed as non-invasive procedure for evaluation of carpal nerve stress.
An ecological examination of early adolescent e-cigarette use: A machine learning approach to understanding a health epidemic
Authors: Vázquez Alejandro L. , Navarro Flores Cynthia M. , Garcia Byron H. , Barrett Tyson S. , Domenech Rodríguez Melanie M.
Published: June 2023

E-cigarette use among adolescents is a national health epidemic spreading faster than researchers can amass evidence for risk and protective factors and long-term consequences associated with use. New technologies, such as machine learning, may asset prevention programs in identifying at-risk youth and potential targets for intervention before adolescents enter developmental periods where e-cigarette use escalates. The current study utilized machine learning algorithms to explore a wide array of individual and socioecological variables in relation to patterns of lifetime e-cigarette use during early adolescence (i.e., exclusive, or with tobacco). Extant data was used from 14,346 students middle school students (Mage= 12.5, SD = 1.1; 6thand 8th grades) who participated in the Utah Prevention Needs Assessment survey. Students self-reported their substance use behaviors and related risk and protective factors. Machine learning algorithms examined 112 individual and socioecological factors as potential classifiers of lifetime e-cigarette use outcomes. The elastic net algorithm achieved outstanding classification for lifetime exclusive (AUC = .926) and dual use (AUC = .944) on a validation test set. Six high value classifiers were identified that varied in importance by outcome: Lifetime alcohol or marijuana use, perception of e-cigarette availability and risk, school suspension(s), and perceived risk of smoking marijuana regularly. Specific classifiers were important for lifetime exclusive (parent’s attitudes regarding student vaping, best friend[s] tried alcohol or marijuana) and dual use (best friend[s] smoked cigarettes, lifetime inhalant use). Our findings provide specific targets for the adaptation of existing substance use prevention programs to address early adolescent e-cigarette use.