bluuebunny/crossref_metadata_2025 huggingface dataset:
The relationship between payer type and quality of care for women undergoing emergency cesarean section at three hospitals in rural Uganda
Authors: Mwiindi Jonathan , Delgado Rigoberto , Revere Lee , Wangigi Beth , Muguthu Edward , Busingye Priscilla
Published: March 2024

Background

The study examined the relationship between payer type, and quality of care among mothers who deliver through emergency cesarean section in rural Ugandan hospitals.

Methods

We analyzed retrospective, de-identified patient data from three rural private-not-for-profit hospitals in Uganda. Two groups were included in the study, a self-payer patient group and a group fully sponsored by an international funding organization. The data was analyzed using hierarchical linear regression models comparing length of stay against payer type, and controlling for patient age, education level, parity, and indication for C-section. Length of stay (LOS) was assumed to represent a realistic proxy variable for patient quality of care.

Results

The self-pay group had statistically significant longer postoperative LOS (surgery to clinical discharge), and longer aggregate LOS, or admission to clinical discharge, compared to the sponsored group. Payer type was not significant in the admission-to-decision LOS, but payer type was highly significant for aggregate LOS (p <.001).

Conclusion

Case management in rural Ugandan hospitals influences quality of post-operative care for patients undergoing emergency C-sections. Expanding surgical funding, combined with effective case management approaches, is likely to increase quality of surgical care as measured by length of stay.

Synopsis: Post-operative quality of care for emergency C-section cases, measured by length of stay in Ugandan rural hospitals, is impacted by case management.
Comprehensive evaluation of pipelines for diagnostic biomarkers of major depressive disorder using multi-site resting-state fMRI datasets
Authors: Takahara Yuji , Kashiwagi Yuto , Tokuda Tomoki , Yoshimoto Junichiro , Sakai Yuki , Yamashita Ayumu , Yoshioka Toshinori , Takahashi Hidehiko , Mizuta Hiroto , Kasai Kiyoto , Kunimitsu Akira , Okada Naohiro , Itai Eri , Shinzato Hotaka , Yokoyama Satoshi , Masuda Yoshikazu , Mitsuyama Yuki , Okada Go , Okamoto Yasumasa , Itahashi Takashi , Ohta Haruhisa , Hashimoto Ryu-ichiro , Harada Kenichiro , Yamagata Hirotaka , Matsubara Toshio , Matsuo Koji , Tanaka Saori C. , Imamizu Hiroshi , Ogawa Koichi , Momosaki Sotaro , Kawato Mitsuo , Yamashita Okito
Published: March 2024

The objective diagnostic and stratification biomarkers developed with resting-state functional magnetic resonance imaging (rs-fMRI) data are expected to contribute to more effective treatment for mental disorders. Unfortunately, there are currently no widely accepted biomarkers, partially due to the large variety of analysis pipelines for developing them. In this study we comprehensively evaluated analysis pipelines using a large-scale, multi-site fMRI dataset for major depressive disorder (MDD) (1162 participants from eight imaging sites). We explored the combinations of options in four subprocesses of analysis pipelines: six types of brain parcellation, four types of estimations of functional connectivity (FC), three types of site difference harmonization, and five types of machine learning methods. 360 different MDD diagnostic biomarkers were constructed using the SRPBS dataset acquired with unified protocols (713 participants from four imaging sites) as a discovery dataset and evaluated with datasets from other projects acquired with heterogeneous protocols (449 participants from four imaging sites) for independent validation. To identify the optimal options regardless of the discovery dataset, we repeated the same procedure after swapping the roles of the two datasets. We found pipelines that included Glasser’s parcellation, tangent-covariance, no harmonization, and non-sparse machine learning methods tended to result in high classification performance. The diagnosis results of the top 10 biomarkers showed high similarity, and weight similarity was also observed between eight of the biomarkers, except two that used both data-driven parcellation and FC computation. We applied the top 10 pipelines to the datasets of other mental disorders (autism spectral disorder: ASD and schizophrenia: SCZ) and eight of the ten biomarkers showed sufficient classification performances for both disorders, except two pipelines that included Pearson correlation, ComBat harmonization and random forest classifier combination.

Highlights

We evaluated the analysis pipelines of rsFC biomarker development.

Four subprocesses in them were investigated with two multi-site datasets.

Glasser’s parcellation, tangent covariance, and non-sparse methods were preferred.

The weight patterns of eight of the top 10 biomarkers showed high commonality.

Eight of the top 10 pipelines were successful for developing SCZ/ASD biomarkers.
Nanoparticle-mediated delivery of peptide-based degraders enables targeted protein degradation
Authors: Ghosal Souvik , Robertus Cara , Wang Jeanette , Chan Harrison W. , Alamgir Azmain , Almonte Joshua , Alabi Christopher A.
Published: March 2024

The development of small molecule-based degraders against intracellular protein targets is a rapidly growing field that is hindered by the limited availability of high-quality small molecule ligands that bind to the target of interest. Despite the feasibility of designing peptide ligands against any protein target, peptide-based degraders still face significant obstacles such as, limited serum stability and poor cellular internalization. To overcome these obstacles, we repurposed lipid nanoparticle (LNP) formulations to facilitate the delivery of Peptide-based proteolysis TArgeting Chimeras (PepTACs). Our investigations reveal robust intracellular transport of PepTAC-LNPs across various clinically relevant human cell lines. Our studies also underscore the critical nature of the linker and hydrophobic E3 binding ligand for efficient LNP packaging and transport. We demonstrate the clinical utility of this strategy by engineering PepTACs targeting two critical transcription factors, β-catenin and CREPT (cell-cycle-related and expression-elevated protein in tumor), involved in the Wnt-signalling pathway. The PepTACs induced target-specific protein degradation and led to a significant reduction in Wnt-driven gene expression and cancer cell proliferation. Mouse biodistribution studies revealed robust accumulation of PepTAC-LNPs in the spleen and liver, among other organs, and PepTACs designed against β-catenin and formulated in LNPs showed a reduction in β-catenin levels in the liver. Our findings demonstrate that LNPs can be formulated to encapsulate PepTACs, thus enabling robust delivery and potent intracellular protein degradation.
Ornamental radiance as a defence against mimicry at the monogamy-polygyny interface
Authors: Crompton Andrew
Published: March 2024

Ornament evolves though sexual selection when both monogamy or polygyny are equally viable. In this special situation monogamous females will be be able to reject unwanted polygynous suitors only if monogamous males are able distinguish themselves with a sign of fidelity. Since the most sexually advantageous trait value for any male to possess is the one that matches the mean female preference, any signs so created will persist when either monogamy or polygyny subsequently becomes a dominant strategy. Species will therefore accumulate traces of each passage through the monogamous-polygynous boundary which, in birds, can lead, among other outcomes, to a collage of patches of coloured plumage. If a species lives at the interface long enough a polygynous bird might be able to copy the sign of fidelity. One defence against this aggressive mimicry will be to evolve to a sign that is costly or difficult to copy. This process is modelled mathematically showing that if variation of female preference is increased the male phenotype will alter in unpredictable ways that defy a mimic, at a cost of possibly being maladapted. This causes an ornamental radiance that matches ideas of beauty in the human world.
Rapid High-Throughput Isolation and purification of Chicken Myoblasts Based on Deterministic Lateral Displacement Microfluidic Chips
Authors: Gu Lihong , Liu Hongju , Wang Long , Fan Haokai , Zheng Xinli , Xu Tieshan , Jiang Qicheng , Zhou Teng , Shi Liuyong
Published: March 2024

Myoblasts are defined as stem cells containing skeletal muscle cell precursors. However, there are some challenges associated with the purification of myoblast samples, including long culture times and ease of bacterial contamination. In this study, we propose a microfluidic myoblast cell enrichment and purification platform based on the principle of deterministic lateral displacement (DLD). To achieve this, we designed a DLD chip with three outlets and tested it on 11-day-old Wenchang chicken pectoral muscle tissue. A cell suspension was prepared using the collagenase method, pretreated, and then passed into the designed DLD chip for myoblast enrichment and purification. In this study, the number of myoblasts and the diameter of myoblasts increased slowly before E9, and the diameter of myofibers decreased and the number of myofibers increased rapidly after E9. The period when the number of muscle fibers is highest is E12, and the period when the diameter of muscle fibers increases again after the lowest point is also E12. After E12, the diameter of the muscle fibers increased and the number of muscle fibers decreased. At E12, myoblasts clustered and fused, and the proliferation of myoblasts was greatly reduced. E12 is both intact myoblasts and the most vigorous proliferation period, so the best time to determine isolation is E12. We attained a myoblast cell recovery rate of 80%, a target outlet collection purity of 99%, and a chip throughput of 50 μ m/min. This study provides a novel and effective method for the isolation and purification of skeletal muscle myoblasts.
Dissociable dorsal medial prefrontal cortex ensembles are necessary for cocaine seeking and fear conditioning in mice
Authors: Liu Shuai , Nawarawong Natalie , Liu Xiaojie , Liu Qing-song , Olsen Christopher M.
Published: March 2024

The dmPFC plays a dual role in modulating drug seeking and fear-related behaviors. Learned associations between cues and drug seeking are encoded by a specific ensemble of neurons. This study explored the stability of a dmPFC cocaine seeking ensemble over two weeks and its influence on persistent cocaine seeking and fear memory retrieval. In the first series of experiments, we trained TetTag mice in cocaine self-administration and tagged strongly activated neurons with EGFP during the initial day 7 cocaine seeking session. Subsequently, a follow-up seeking test was conducted two weeks later to examine ensemble reactivation between two seeking sessions via c-Fos immunostaining. In the second series of experiments, we co-injected viruses expressing TRE-cre and a cre-dependent inhibitory PSAM-GlyR into the dmPFC of male and femalec-fos-tTA mice to enable “tagging” of cocaine seeking ensemble or cued fear ensemble neurons with an inhibitory chemogenetic receptors. Then we investigated their contribution to subsequent cocaine seeking and fear recall during inhibition of the tagged ensemble by administering uPSEM792s (0.3 mg/kg), a selective ligand for PSAM-GlyR. In both sexes, there was a positive association between the persistence of cocaine seeking and the proportion of reactivated EGFP+ neurons within the dmPFC. More importantly, inhibition of the cocaine seeking ensemble suppressed cocaine seeking, but not recall of fear memory, while inhibition of the fear ensemble reduced conditioned freezing but not cocaine seeking. The results demonstrate that cocaine and fear recall ensembles in the dmPFC are stable, but largely exclusive from one another.
Chromosome-level Subgenome-awarede novoAssembly ofSaccharomyces bayanusProvides Insight into Genome Divergence after Hybridization
Authors: Gardner Cory , Chen Junhao , Hadfield Christina , Lu Zhaolian , Debruin David , Zhan Yu , Donlin Maureen J. , Lin Zhenguo , Ahn Tae-Hyuk
Published: March 2024

Interspecies hybridization is prevalent in various eukaryotic lineages and plays important roles in phenotypic diversification, adaption, and speciation. To better understand the changes that occurred in the different subgenomes of a hybrid species and how they facilitated adaptation, we completed chromosome-levelde novoassemblies of all 16 pairs chromosomes for a recently formed hybrid yeast,Saccharomyces bayanusstrain CBS380 (IFO11022), using Nanopore MinION long-read sequencing. Characterization ofS. bayanussubgenomes and comparative analysis with the genomes of its parent species,S. uvarumandS. eubayanus,provide several new insights into understanding genome evolution after a relatively recent hybridization. For instance, multiple recombination events between the two subgenomes have been observed in each chromosome, followed by loss of heterozygosity (LOH) in most chromosomes in nine chromosome pairs. In addition to maintaining nearly all gene content and synteny from its parental genomes,S. bayanushas acquired many genes from other yeast species, primarily through the introgression ofS. cerevisiae, such as those involved in the maltose metabolism. In addition, the patterns of recombination and LOH suggest an allotetraploid origin ofS. bayanus. The gene acquisition and rapid LOH in the hybrid genome probably facilitated its adaption to maltose brewing environments and mitigated the maladaptive effect of hybridization.
Risk factors for breast cancer subtypes by race and ethnicity: A scoping review of the literature
Authors: Hurson Amber N , Ahearn Thomas U , Koka Hela , Jenkins Brittany D , Harris Alexandra R , Roberts Sylvia , Fan Sharon , Franklin Jamirra , Butera Gisela , Keeman Renske , Jung Audrey Y , Middha Pooja , Gierach Gretchen L , Yang Xiaohong R , Chang-Claude Jenny , Tamimi Rulla M , Troester Melissa A , Bandera Elisa V , Abubakar Mustapha , Schmidt Marjanka K , Closas Montserrat Garcia-
Published: March 2024

Background

Breast cancer is comprised of distinct molecular subtypes. Studies have reported differences in risk factor associations with breast cancer subtypes, especially by tumor estrogen receptor (ER) status, but their consistency across racial and ethnic populations has not been comprehensively evaluated.

Methods

We conducted a qualitative, scoping literature review using the Preferred Reporting Items for Systematic Reviews and Meta-analysis, extension for Scoping Reviews to investigate consistencies in associations between 18 breast cancer risk factors (reproductive, anthropometric, lifestyle, and medical history) and risk of ER-defined subtypes in women who self-identify as Asian, Black or African American, Hispanic or Latina, or White. We reviewed publications between January 1, 1990 and July 1, 2022. Etiologic heterogeneity evidence (convincing, suggestive, none, or inconclusive) was determined by expert consensus.

Results

Publications per risk factor ranged from 14 (benign breast disease history) to 66 (parity). Publications were most abundant for White women, followed by Asian, Black or African American, and Hispanic or Latina women. Etiologic heterogeneity evidence was strongest for parity, followed by age at first birth, post-menopausal BMI, oral contraceptive use, and estrogen-only and combined menopausal hormone therapy. Evidence was limited for other risk factors. Findings were consistent across racial and ethnic groups, although the strength of evidence varied.

Conclusion

The literature supports etiologic heterogeneity by ER for some established risk factors that are consistent across race and ethnicity groups. However, in non-White populations evidence is limited. Larger, more comparable data in diverse populations is needed to better characterize breast cancer etiologic heterogeneity.
Exploring Early Perceptions and Experiences of ChatGPT in Pediatric Critical Care: A Qualitative Study Among Healthcare Professionals
Authors: Temsah Mohamad-Hani , Abouammoh Noura , Alsatrawi Mohammed , Almazyad Mohammed , Aljamaan Fadi , Vargas-Gutierrez Mariella , Hay Rebecca , Al-Jelaify Muneera , Alabdulkreem Wejdan , Assiri Nawal , Muaygil Ruaim , Altamimi Ibraheem , Alshahrani Fatimah S. , Alhasan Khalid , Malki Khalid H. , Jamal Amr , Al-Tawfiq Jaffar A. , Al-Eyadhy Ayman
Published: March 2024

This qualitative inquiry explores the initial impressions and firsthand encounters of healthcare professionals (HCPs) with ChatGPT, a Generative Pre-trained Transformer, within Pediatric Intensive Care Units (PICUs). Through focus group discussions held at a tertiary academic center, a diverse cadre of HCPs was engaged to ascertain their awareness, utilization patterns, perceived advantages, and apprehensions regarding ChatGPT. The analysis revealed three primary themes: understanding and ease of use of ChatGPT, its practical applications in clinical workflows for critically ill children and information retrieval, and the ethical considerations associated with its deployment. While participants praised ChatGPT for its engaging interface and potential to streamline tasks and provide prompt information, notable reservations surfaced regarding its limitations, particularly in medical accuracy, currency of data, and ethical implications. The findings suggest a cautious optimism towards integrating Generative Artificial Intelligence (GAI), like ChatGPT, in pediatric critical care, highlighting the need for balanced, informed, and transparent applications, with ongoing evaluation of GAI technologies in pediatric healthcare settings.
Demographic variation and socioeconomic inequalities associated with the triple burden of malnutrition in Vietnamese children aged 6 months to 9 years old: Findings from the Vietnamese General Nutrition Survey 2020
Authors: Tan Pui Yee , Som Somphos Vicheth , Nguyen Son Duy , Tan Xiaomian , Tran Do Tranh , Tran Nga Thuy , Tran Van Khanh , Dye Louise , Moore J Bernadette , Caton Samantha , Ensaff Hannah , Lin Xiaodong , Smith Geoffry , Gong YunYun
Published: March 2024

Introduction: The triple burden of malnutrition (TBM) is a growing public health issue worldwide. This study examined the prevalence and association between undernutrition, overnutrition and micronutrient deficiencies (MNDs), and the associated demographic and socioeconomic determinants, among Vietnamese children, using the nationally representative General Nutrition Survey 2020. Methods: Data on anthropometric parameters, micronutrients biomarkers, demographic and socioeconomic indicators for 7,289 children aged 6 months to 9 years old were analysed. Determinants of malnutrition were assessed using logistic regressions and reported as odds ratio (OR) [95% confidence intervals (CI)]. Results: Overall, 12.7%, 10.5% and 4.7% of children were stunted, underweight and wasted/thin; while 7.3% and 7.1% were living with overweight and obesity, respectively. Low serum zinc, anaemia and iron deficiency (ID) were the common MNDs observed, affecting 53.1%, 15.2% and 13.9% of the study participants. Older children aged 2-4 years old [OR (95% CI): 1.43 (1.20, 1.72)], ethnic minorities [5.94 (3.78, 9.36)] and living in mountainous areas [5.06 (1.18, 14.42)] had increased odds of stunting, whereas reduced odds were found in children from the richest quintile [0.13 (0.05, 0.32)]. Similar determinants were found to be associated with underweight and MNDs. Males [1.43 (1.16, 1.76)], children aged 5-9 years old [10.02 (6.71, 14.97) and children from the richest quintile [2.91 (1.20, 7.05)] had increased odds of overweight. Children with anaemia, low serum retinol and low serum zinc had increased odds of stunting and underweight than non-micronutrient deficient children (adjusted OR=1.43-1.71). Compared to children without MNDs, those with ≥3 MNDs had almost double the odds of stunting and underweight, whereas those with ≤3 MNDs had reduced odds of overweight (adjusted OR=0.38-0.60). Conclusions: Significant demographic variation and socioeconomic inequalities in child malnutrition were identified. National policies and programmes in Vietnam should address age-specific, sex-specific, geographical and socioeconomic disparities to accelerate progress in reducing child malnutrition.
Decoding Prodromal Parkinson’s Disease: Clinical Differences between Isolated Hyposmia and REM Sleep Behavior Disorder
Authors: Banerjee Luke Vikram , Pasquini Jacopo , Henderson Robin , Pavese Nicola , Anderson Kirstie N
Published: March 2024

Background

The prodromal phase of Parkinson’s disease (PD), much like the disease itself, displays marked heterogeneity, with varied rates of progression and symptom severities. A detailed clinical characterization of prodromal subgroups may provide useful insights for both clinical and research settings.

Objectives

To compare clinical assessments in patients with idiopathic rapid eye movement sleep behavior disorder (iRBD) and those with isolated hyposmia.

Methods

A cross-sectional study was conducted on 191 patients with iRBD, 213 patients with isolated hyposmia and 150 healthy controls recruited in the Parkinson’s Progression Markers Initiative. The earliest available assessment for each participant was selected. Our analysis investigated and compared the Montreal Cognitive Assessment, Scales for Outcomes in Parkinson’s Disease Autonomic Dysfunction (SCOPA-AUT) and Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) Parts I, II and III scores across the three groups. To assess differences, after adjusting for age and sex, we employed permutations testing. We further investigated the specific question items that contributed most significantly to the observed variations between the groups.

Results

We found significant differences between the healthy control group and a combined prodromal group across all assessment categories, with prodromal participants displaying poorer scores. For between prodromal groups comparison, significant differences emerged in SCOPA-AUT and MDS-UPDRS Part I scores, with the iRBD group presenting with more severe scores.

Conclusion

Our study highlights that even in the premotor stage of PD, clinical distinctions exist in terms of autonomic burden between individuals with iRBD and those with isolated hyposmia.
COGNITIVE ASSESSMENT WITH COGNIVUECLARITY®: PSYCHOMETRIC PROPERTIES AND ENHANCED NORMATIVE RANGES IN A DIVERSE POPULATION
Authors: Galvin James E. , Chang Lun-Ching , Estes Paul , Harris Heather M. , Fung Ernest
Published: March 2024

Background

Detecting cognitive impairment in clinical practice is challenging as most instruments do not perform well in diverse samples of older adults. These same instruments are often used for eligibility into clinical trials making it difficult to recruit minoritized adults into Alzheimer’s disease (AD) studies. CognivueClarity®is an FDA-cleared computerized cognitive screening platform using adaptive psychophysics to detect cognitive impairment.

Objective

Test the ability of CognivueClarityto detect cognitive impairment in a diverse community sample compared with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS).

Methods

This study enrolled 452 participants across 6 US study sites and completed both CognivueClaritydevice and RBANS. Psychometric properties and exploratory factor analysis of CognivueClaritywere explored and comparisons against RBANS across different age, sex, education, and ethnoracial groups were conducted.

Results

Participants had a mean age of 47.9±16.1 years (range: 18-85), 63.6% were female, 45.9% had<12 years of education, 31.2% were African American and 9.2% were Hispanic. CognivueClarityhad strong internal consistency, test-retest and minimal practice effects. A 4-factor structure (Memory, Attention, Visuomotor, and Discrimination) had excellent goodness of fit. Normalizing age effects improved performance. Race and education effects were similar to those seen with RBANS. CognivueClarityhad strong correlation with RBANS.

Conclusions

Our study supports the use of CognivueClarityas an easy-to-use, brief, and valid cognitive assessment that can be used for identifying individuals with likely cognitive impairment in the clinical setting and those who could be candidates for AD research studies.
Identifying Psychosis Episodes in Psychiatric Admission Notes via Rule-based Methods, Machine Learning, and Pre-Trained Language Models
Authors: Hua Yining , Blackley Suzanne V. , Shinn Ann K. , Skinner Joseph P. , Moran Lauren V. , Zhou Li
Published: March 2024

Early and accurate diagnosis is crucial for effective treatment and improved outcomes, yet identifying psychotic episodes presents significant challenges due to its complex nature and the varied presentation of symptoms among individuals. One of the primary difficulties lies in the underreporting and underdiagnosis of psychosis, compounded by the stigma surrounding mental health and the individuals’ often diminished insight into their condition. Existing efforts leveraging Electronic Health Records (EHRs) to retrospectively identify psychosis typically rely on structured data, such as medical codes and patient demographics, which frequently lack essential information. Addressing these challenges, our study leverages Natural Language Processing (NLP) algorithms to analyze psychiatric admission notes for the diagnosis of psychosis, providing a detailed evaluation of rule-based algorithms, machine learning models, and pre-trained language models. Additionally, the study investigates the effectiveness of employing keywords to streamline extensive note data before training and evaluating the models. Analyzing 4,617 initial psychiatric admission notes (1,196 cases of psychosis versus 3,433 controls) from 2005 to 2019, we discovered that the XGBoost classifier employing Term Frequency-Inverse Document Frequency (TF-IDF) features derived from notes pre-selected by expert-curated keywords, attained the highest performance with an F1 score of 0.8881 (AUROC [95% CI]: 0.9725 [0.9717, 0.9733]). BlueBERT demonstrated comparable efficacy an F1 score of 0.8841 (AUROC [95% CI]: 0.97 [0.9580, 0.9820]) on the same set of notes. Both models markedly outperformed traditional International Classification of Diseases (ICD) code-based detection methods from discharge summaries, which had an F1 score of 0.7608, thus improving the margin by 0.12. Furthermore, our findings indicate that keyword pre-selection markedly enhances the performance of both machine learning and pre-trained language models. This study illustrates the potential of NLP techniques to improve psychosis detection within admission notes and aims to serve as a foundational reference for future research on applying NLP for psychosis identification in EHR notes.
Burden of Disease of Respiratory Syncytial Virus in Older Adults and Adults Considered at High Risk of Severe Infection
Authors: Abrams Elissa , Doyon-Plourde Pamela , Davis Phaedra , Lee Liza , Rahal Abbas , Brousseau Nicholas , Siu Winnie , Killikelly April
Published: March 2024

Background

Vaccine products for adults have increased interest in understanding Canada’s respiratory syncytial virus (RSV) burden in older adults and adults considered at high risk of severe infection.

Objective

To characterize the burden of RSV disease in Canada by joint analysis of the published literature and hospitalization data from a healthcare administrative database.

Methods

Electronic databases of published literature were searched to identify studies and systematic reviews reporting data on outpatient visits, hospitalizations, intensive care unit (ICU) admissions and deaths associated with RSV infection in adults. For the hospitalization data analysis, hospital discharge records were extracted from the Canadian Institute of Health Information (CIHI) Discharge Abstract Database (DAD) for all patients admitted to an acute care facility for RSV infection defined by ICD-10 codes from 2010-2020 and 2021-2023.

Results

Overall, 26 studies, including 7 systematic reviews, were identified and summarized in the rapid review. Evidence suggests that medically attended RSV respiratory tract infections (RTI) are frequent causing 4.7 to 7.8% of symptomatic RTI in adults 60 years of age and older. Incidence of RSV RTI increases with age and presence of underlying medical conditions, such as cardiorespiratory disease, diabetes, and immunocompromising conditions. This trend was consistently observed across all RSV clinical outcomes of interest (i.e., hospitalization, ICU admission and death). Patients who reside in long-term care or other chronic care facilities have higher likelihood of severe clinical outcomes (i.e., ICU admission, receiving mechanical ventilation and/or death) compared to patients with other living situations upon hospital admission. Approximately 10% of older adults hospitalized with RSV infection require ICU admission. Although data are limited, evidence suggests that case fatality ratio (CFR) among those admitted to hospital varies between 5 and 10%. Some evidence suggests that RSV burden may be close to influenza burden in older adults. In general, the results from the Canadian hospitalization data support the rapid review findings Rates of hospitalization, ICU admission and death associated with RSV all increased with age, with 16% of hospitalizations resulting in ICU admission and with an in-hospital CFR of 9%.

Conclusion

In adults, risk of severe RSV outcomes in general increases with increasing age and presence of comorbidities.
Study Protocol for the Artificial Intelligence-Driven Evaluation of Structural Heart Diseases Using Wearable Electrocardiogram (ID-SHD)
Authors: Aminorroaya Arya , Dhingra Lovedeep Singh , Pedroso Camargos Aline , Vasisht Shankar Sumukh , Khunte Akshay , Sangha Veer , Sen Sounok , McNamara Robert L , Haynes Norrisa , Oikonomou Evangelos K , Khera Rohan
Published: March 2024

Introduction

Portable devices capable of electrocardiogram (ECG) acquisition have the potential to enhance structural heart disease (SHD) management by enabling early detection through artificial intelligence-ECG (AI-ECG) algorithms. However, the performance of these AI algorithms for identifying SHD in a real-world screening setting is unknown. To address this gap, we aim to evaluate the validity of our wearable-adapted AI algorithm, which has been previously developed and validated for detecting SHD from single-lead portable ECGs in patients undergoing routine echocardiograms in the Yale New Haven Hospital (YNHH).

Research Methods and Analysis

This is the protocol for a cross-sectional study in the echocardiographic laboratories of YNHH. The study will enroll 585 patients referred for outpatient transthoracic echocardiogram (TTE) as part of their routine clinical care. Patients expressing interest in participating in the study will undergo a screening interview, followed by enrollment upon meeting eligibility criteria and providing informed consent. During their routine visit, patients will undergo a 1-lead ECG with two devices - one with an Apple Watch and the second with another portable 1-lead ECG device. With participant consent, these 1-lead ECG data will be linked to participant demographic and clinical data recorded in the YNHH electronic health records (EHR). The study will assess the performance of the AI-ECG algorithm in identifying SHD, including left ventricular systolic dysfunction (LVSD), valvular disease and severe left ventricular hypertrophy (LVH), by comparing the algorithm’s results with data obtained from TTE, which is the established gold standard for diagnosing SHD.

Ethics and Dissemination

All patient EHR data required for assessing eligibility and conducting the AI-ECG will be accessed through secure servers approved for protected health information. Data will be maintained on secure, encrypted servers for a minimum of five years after the publication of our findings in a peer-reviewed journal, and any unanticipated adverse events or risks will be reported by the principal investigator to the Yale Institutional Review Board, which has reviewed and approved this protocol (Protocol Number: 2000035532).
A survey of experts to identify methods to detect problematic studies: Stage 1 of the INSPECT-SR Project
Authors: Wilkinson Jack , Heal Calvin , Antoniou George A , Flemyng Ella , Avenell Alison , Barbour Virginia , Bordewijk Esmee M , Brown Nicholas J L , Clarke Mike , Dumville Jo , Grohmann Steph , Gurrin Lyle C. , Hayden Jill A , Hunter Kylie E , Lam Emily , Lasserson Toby , Li Tianjing , Lensen Sarah , Liu Jianping , Lundh Andreas , Meyerowitz-Katz Gideon , Mol Ben W , O’Connell Neil E , Parker Lisa , Redman Barbara , Seidler Anna Lene , Sheldrick Kyle , Sydenham Emma , Dahly Darren L , van Wely Madelon , Bero Lisa , Kirkham Jamie J
Published: March 2024

Background

Randomised controlled trials (RCTs) inform healthcare decisions. Unfortunately, some published RCTs contain false data, and some appear to have been entirely fabricated. Systematic reviews are performed to identify and synthesise all RCTs which have been conducted on a given topic. This means that any of these ‘problematic studies’ are likely to be included, but there are no agreed methods for identifying them. The INSPECT-SR project is developing a tool to identify problematic RCTs in systematic reviews of healthcare-related interventions. The tool will guide the user through a series of ‘checks’ to determine a study’s authenticity. The first objective in the development process is to assemble a comprehensive list of checks to consider for inclusion.

Methods

We assembled an initial list of checks for assessing the authenticity of research studies, with no restriction to RCTs, and categorised these into five domains: Inspecting results in the paper; Inspecting the research team; Inspecting conduct, governance, and transparency; Inspecting text and publication details; Inspecting the individual participant data. We implemented this list as an online survey, and invited people with expertise and experience of assessing potentially problematic studies to participate through professional networks and online forums. Participants were invited to provide feedback on the checks on the list, and were asked to describe any additional checks they knew of, which were not featured in the list.

Results

Extensive feedback on an initial list of 102 checks was provided by 71 participants based in 16 countries across five continents. Fourteen new checks were proposed across the five domains, and suggestions were made to reword checks on the initial list. An updated list of checks was constructed, comprising 116 checks. Many participants expressed a lack of familiarity with statistical checks, and emphasized the importance of feasibility of the tool.

Conclusions

A comprehensive list of trustworthiness checks has been produced. The checks will be evaluated to determine which should be included in the INSPECT-SR tool.
Assessing the Seasonality of Lab Tests Among Patients with Alzheimer’s Disease and Related Dementias in OneFlorida Data Trust
Authors: Han Wenshan , Bhasuran Balu , Muse Victorine Patricia , Brunak Søren , Lin Lifeng , Hanna Karim , Huang Yu , Bian Jiang , He Zhe
Published: March 2024

About 1 in 9 older adults over 65 has Alzheimer’s disease (AD), many of whom also have multiple other chronic conditions such as hypertension and diabetes, necessitating careful monitoring through laboratory tests. Understanding the patterns of laboratory tests in this population aids our understanding and management of these chronic conditions along with AD. In this study, we used an unimodal cosinor model to assess the seasonality of lab tests using electronic health record (EHR) data from 34,303 AD patients from the OneFlorida+ Clinical Research Consortium. We observed significant seasonal fluctuations—higher in winter in lab tests such as glucose, neutrophils per 100 white blood cells (WBC), and WBC. Notably, certain leukocyte types like eosinophils, lymphocytes, and monocytes are elevated during summer, likely reflecting seasonal respiratory diseases and allergens. Seasonality is more pronounced in older patients and varies by gender. Our findings suggest that recognizing these patterns and adjusting reference intervals for seasonality would allow healthcare providers to enhance diagnostic precision, tailor care, and potentially improve patient outcomes.
Trends and Determinants of Neonatal Mortality in Rural Ethiopia
Authors: Asaye Sintayehu , Saketa Dawit , Birhanu Dires , Gudeta Tadesse , Besho Merga , Getnet Masrie , Debelew Gurmesa Tura , Berhanu Negalign , Siraneh Yibeltal , Abamecha Fira , Tamiru Dessalegn
Published: March 2024

Background

Neonatal mortality is a significant challenge that affects babies within the first 28 days of life. The issue is particularly challenging for healthcare systems in developing countries, where interventions are required. Although there has been a decline in neonatal mortality worldwide, comprehensive data on the patterns of neonatal mortality and the contributing factors in rural regions of Ethiopia is lacking.

Objective

To determine neonatal mortality trends and mortality in rural Ethiopia using 2011-2019 DHS data

Methods

Ethiopian demographic health survey (EDHS) program conducted a cross-sectional community-based study in rural Ethiopia in 2011, 2016, and 2019. The study included women who gave birth within the specified timeframe and agreed to participate. Sampling was done through a multistage cluster approach, and STATA version 17 was used to analyze the data. Predictor variables were validated through multiple logistic regression analysis. Weighted estimates were used to derive population-level statistics and a p-value less than 0.05 was considered significant.

Results

The study analyzed data from 22,755 women who participated in EDHS surveys between 2011 and 2019. Neonatal mortality rates decreased from 7.5% to 6.03%. Regional variations were observed, with Gambela and Tigrai having the lowest rates, and Dire Dawa and the Somali region having higher rates. Factors like mother’s age, wealth index, birth order, neonate’s sex, and presence of twins, immediate breastfeeding, and baby’s size were associated with neonatal mortality.

Conclusion and recommendation

Despite significant advancements that have been made to decrease neonatal mortality, there remain challenges that need to be addressed. Therefore, regional health bureaus should strengthen their strategies to enhance antenatal care (ANC) visits and promote birth delivery at health facilities.
Patient Preferences for Diagnostic Imaging Services: Decentralize or not?
Authors: van den Broek-Altenburg Eline M. , Benson Jamie S. , Atherly Adam J. , DeStigter Kristen K.
Published: March 2024

The objective of this study was to identify patient preferences for outpatient diagnostic imaging services and analyze how patients make trade-offs between attributes of these services using a discrete choice experiment (DCE).

We used a DCE with 14 choice questions asking which imaging locations patients would prefer. We used latent class analysis to analyze preference heterogeneity between different patient groups and to estimate the relative value they assign to different attributes of imaging services.

Our analysis showed that the “Experienced Patients” subgroup generally value diagnostic imaging services in both acute and chronic situations and had a strong preference for hospital outpatient radiology departments (HORD) that would provide services at lower costs, where their images would be interpreted by a specialty radiologist, the clinic would be recommended by their PCP, online scheduling would be available, service rating were higher, and travel and wait times would be shorter. New Patients significantly valued the service rating of the hospital outpatient radiology departments (HORD) and online scheduling.

HORDs can be more competitive by providing services that live up to expectations better than available retail radiology clinics (RRCs). Most RRCs do not currently offer online scheduling so ease of use may also steer patients towards HORDs. HORDs have the advantage of being linked to the main medical center which has the reputation of having clinical expertise and more sophisticated technology. We conclude that there is room for medical centers to build HORDs that provide an appealing and competitive alternative to current RRC.
How to measure functional connectivity using resting-state fMRI? A comprehensive empirical exploration of different connectivity metrics
Authors: Roell Lukas , Wunderlich Stephan , Roell David , Raabe Florian , Wagner Elias , Shi Zhuanghua , Schmitt Andrea , Falkai Peter , Stoecklein Sophia , Keeser Daniel
Published: March 2024

Background: Functional connectivity in the context of functional magnetic resonance imaging is typically quantified by Pearson or partial correlation between regional time series of the blood oxygenation level dependent signal. However, a recent interdisciplinary methodological work proposes more than 230 different metrics to measure similarity between different types of time series. Objective: Hence, we systematically evaluated how the results of typical research approaches in functional neuroimaging vary depending on the functional connectivity metric of choice. We further explored which metrics most accurately detect neural decline induced by age and malignant brain tumors, aiming to initiate a debate on how best assessing brain connectivity in functional neuroimaging research. Methods: We addressed both research questions using four independent neuroimaging datasets, comprising multimodal data from a total of 1187 individuals. We analyzed resting-state functional sequences to calculate functional connectivity using 20 representative metrics from four distinct mathematical domains. We further used T1- and T2-weighted images to compute regional brain volumes, diffusion-weighted imaging data to build structural connectomes, and pseudo-continuous arterial spin labeling to measure regional brain perfusion. Results: First, our results demonstrate that the results of typical functional neuroimaging approaches differ fundamentally depending on the functional connectivity metric of choice. Second, we show that correlational and distance metrics are most appropriate to cover neural decline induced by age. In this context, partial correlation performs worse than other correlational metrics. Third, our findings suggest that the FC metric of choice depends on the utilized scanning parameters, the regions of interest, and the individual investigated. Lastly, beyond the major objective of this study, we provide evidence in favor of brain perfusion measured via pseudo-continuous arterial spin labeling as a robust neural entity mirroring age-related neural and cognitive decline. Conclusion: Our empirical evaluation supports a recent theoretical functional connectivity framework. Future functional imaging studies need to comprehensively define the study-specific theoretical property of interest, the methodological property to assess the theoretical property, and the confounding property that may bias the conclusions.
Characterising the stimulus-response function of mouse C-Low threshold mechanoreceptors to mechanical stimuliin vivo
Authors: Semizoglou Evangelia , Lo Re Laure , Middleton Steven J. , Perez-Sanchez Jimena , Tufarelli Tommaso , Bennett David L. , Chisholm Kim I.
Published: March 2024

C-low threshold mechanoreceptors (C-LTMRs) in animals (termed C-tactile (CT) fibres in humans) are a subgroup of C-fibre primary afferents, which innervate hairy skin and respond to low threshold punctate indentations and brush stimuli. These afferents respond to gentle, touch stimuli and are implicated in mediating pleasant/affective touch. These afferents have traditionally been studied using low-throughput, technically challenging approaches, including microneurography in humans and teased fibre electrophysiology in other mammals. Here we suggest a new approach to studying genetically labelled C-LTMRs usingin vivocalcium imaging. We used an automated rotating brush stimulus and Von Frey filaments, applied to the hairy skin of anaesthetised mice to mirror light and affective touch. Simultaneously we visualised changes in C-LTMR activity and confirmed that these neurons are sensitive to low-threshold punctate mechanical stimuli and brush stimuli with a strong preference for slow brushing speeds. We also reveal that C-LMTRs are directionally sensitive, showing more activity when brushed against the natural orientation of the hair. We presentin vivocalcium imaging of genetically labelled C-LTMRs as a useful approach that can reveal new aspects of C-LTMR physiology.
Limb connective tissue is organized in a continuum of promiscuous fibroblast identities during development
Authors: Hirsinger Estelle , Blavet Cédrine , Bonnin Marie-Ange , Bellenger Léa , Gharsalli Tarek , Duprez Delphine
Published: March 2024

Tight developmental coordination of muscle attachments with skeletal muscle is fundamental for building functional limbs and allowing locomotion. Muscle attachments include connective tissue fibroblasts of tendon and muscle connective tissue. Although muscle attachments play critical roles in development, our understanding of connective tissue fibroblast developmental programs lags behind that of other components of the musculoskeletal system, mainly because fibroblasts are highly heterogeneous and poorly characterized. Combining single-cell RNA-sequencing-based strategies including trajectory inference andin situhybridization analyses, we address the diversity of connective tissue fibroblasts and their developmental trajectories during chicken limb fetal development. We show that fibroblasts switch from a program providing positional information to a program of lineage diversification at the onset of fetal period. Muscle connective tissue and tendon contain several fibroblast populations that emerge asynchronously. Once the final muscle pattern is set,in silicofibroblast populations that are close in transcriptional identity are found in neighbouring locations in limbs, prefiguring the adult fibroblast layers associated to muscle. We propose that the limb connective tissue is organised in a continuum of promiscuous fibroblast identities, allowing for the robust and efficient connection of the muscular system to bone and skin.

Highlights

Dissection of connective tissue heterogeneity using single-cell RNA-sequencing andin situRNA staining

In silicofibroblast populations map to distinct fibroblast layers in limbs

Molecular signatures of fetal fibroblast populations at the origin of limb adult connective tissue

Epimysium and endomysium fibroblasts are transcriptionally distinct at fetal stage

Limb fibroblasts display promiscuous identities reflecting their interconnected 3D-network

Fibroblasts switch from providing positional information to differentiation during development