bluuebunny/crossref_metadata_2025 huggingface dataset:
Genomic Surveillance for Enhanced Healthcare Outbreak Detection and Control
Authors: Sundermann Alexander J. , Kumar Praveen , Griffith Marissa P. , Waggle Kady D. , Srinivasa Vatsala Rangachar , Raabe Nathan , Mills Emma G. , Coyle Hunter , Ereifej Deena , Creager Hannah M. , Ayres Ashley , Tyne Daria Van , Pless Lora Lee , Snyder Graham M. , Roberts Mark , Harrison Lee H.
Published: September 2024

Background

Current methods are insufficient alone for outbreak detection in hospitals. Real-time genomic surveillance using offers the potential to detect otherwise unidentified outbreaks. We initiated and evaluated the Enhanced Detection System for Healthcare-associated Transmission (EDS-HAT), a real-time genomic surveillance program for outbreak detection and mitigation.

Methods

This study was conducted at UPMC Presbyterian Hospital from November 2021 to October 2023. Whole genome sequencing (WGS) was performed weekly on healthcare-associated clinical bacterial isolates to identify otherwise undetected outbreaks. Interventions were implemented in real-time based on identified transmission. A clinical and economic impact analysis was conducted to estimate infections averted and net cost savings.

Results

There were 3,921 bacterial isolates from patient healthcare-associated infections that underwent WGS, of which 476 (12.1%) clustered into 172 outbreaks (size range 2-16 patients). Of the outbreak isolates, 292 (61.3%) had an identified epidemiological link. Among the outbreaks with interventions, 95.6% showed no further transmission on the intervened transmission route. The impact analysis estimated that, over the two-year period, 62 infections were averted, with gross cost savings of $1,011,146, and net savings of $695,706, which translates to a 3.2-fold return on investment. Probabilistic sensitivity analysis showed EDS-HAT was cost-saving and more effective in 98% of simulations.

Conclusion

Real-time genomic surveillance enabled the rapid detection and control of outbreaks in our hospital and resulted in economic benefits and improvement in patient safety. This study demonstrates the feasibility and effectiveness of integrating genomic surveillance into routine infection prevention practice, offering a paradigm shift in healthcare outbreak detection and control.
Molecular Characterization of Pediatric Acute Lymphoblastic Leukemia via Integrative Transcriptomics: A Multicenter Study in Argentina
Authors: Ruiz María Sol , Abbate María Mercedes , Sosa Ezequiel , Avendaño Daniel , Mercado Ignacio Gomez , Lacreu María Laura , Riccheri María Cecilia , Schuttenberg Virginia , Aversa Luis , Vazquez Elba , Gueron Geraldine , Cotignola Javier
Published: September 2024

Pediatric acute lymphoblastic leukemia (ALL) is a highly heterogeneous disease at the molecular level, with over 20 subtypes of B-cell ALL (B-ALL) identified to date. These subtypes are critical for guiding risk-adapted therapy and precision medicine, as they are defined by specific chromosomal rearrangements, gene expression profiles, aneuploidies and point mutations. However, the ability to accurately classify these subtypes is limited by the technical and economic challenges faced by many centers, particularly in low- and middle-income countries. In this study, we employed transcriptome sequencing to perform molecular classification of B-ALL at diagnosis in pediatric patients enrolled in the multicentric ALLIC-GATLA-2010 clinical protocol in Argentina. Using a combination of bioinformatic tools, we successfully identified single nucleotide variants, fusion transcripts and gene expression profiles, achieving molecular classification in over 90% of patients. Our analysis also revealed high-risk molecular features and novel genetic alterations. These findings hold potential clinical value for improving risk stratification and identifying therapeutic targets, particularly for patients who remain unclassified by conventional diagnostic methods.
RaBIt: An Effective Visualization-Driven Tool for Power and Sample Size Estimation in Two-Stage General Randomized Basket Trial Designs
Authors: Chen Desmond Zeya , Patel Sahil S. , Xie Aoqi , Chen Jiayin , Castle David , Ma Clement
Published: September 2024

Basket trial designs with interim analysis have gained significant attention due to their adaptability, flexibility, and scalability. In response to the need for user-friendly tools that enhance the real-world applicability of these designs, we developed a web-based interface aimed at facilitating two-stage basket trial designs. Built using R Shiny, the tool was rigorously validated for output consistency by comparing it to an established R pipeline. Additionally, user testing was conducted to ensure the interface is intuitive and easy to use. The result is a freely accessible tool that provides effective and convenient visualizations for general basket trial designs with interim analysis, available athttps://desmondzeyachen.shinyapps.io/AdaptiveTwoStageBasketTrialFeb14/. Future improvements may further expand the tool’s capabilities to accommodate the increasing complexity of trial designs needed by the research community.
AI-VOICE: A Method to Measure and Incorporate Patient Utilities Into AI-Informed Healthcare Workflows
Authors: Morse Keith E. , Higgins Michael C. , Qian Yichun , Callahan Alison , Shah Nigam H.
Published: September 2024

Background

Patients are important participants in their medical care, yet artificial intelligence (AI) models are used to guide care with minimal patient input. This limitation is made partially worse due to a paucity of rigorous methods to measure and incorporate patient values of the tradeoffs inherent in AI applications.

This paper presents AI-VOICE (Values-Oriented Implementation and Context Evaluation), a novel method to collect patient values, or utilities, of the downstream consequences stemming from an AI model’s use to guide care. The results are then used to select the model’s risk threshold, offering a mechanism by which an algorithm can concretely reflect patient values.

Methods

The entity being evaluated by AI-VOICE is anAI-informed workflow, which is composed of the patient’s health state, an action triggered by the AI model, and the benefits and harms accrued as a consequence of that action. The utilities of these workflows are measured through a survey-based, standard gamble experiment. These utilities define a patient-specific ratio of the cost of an inaccurate prediction versus the benefits of an accurate one. This ratio is mapped to the receiver-operator-characteristic curve to identify the risk threshold that reflects the patient’s values.

The survey instrument is made freely available to researchers through a web-based application.

Results

A demonstration of AI-VOICE is provided using a hypothetical sepsis prediction algorithm.

Conclusion

AI-VOICE offers an accessible, quantitative method to incorporate patient values into AI-informed healthcare workflows.
Retrieval-Augmented Generation for Extracting CHA₂DS₂-VASc Risk Factors from Unstructured Clinical Notes in Patients with Atrial Fibrillation
Authors: Adejumo Philip , Thangaraj Phyllis , Shankar Sumukh Vasisht , Dhingra Lovedeep Singh , Aminorroaya Arya , Khera Rohan
Published: September 2024

Background

Assessment of stroke risk in patients with atrial fibrillation (AF) is crucial for guiding anticoagulation therapy. CHA₂DS₂-VASc is a widely used score for defining this risk, but current assessments rely on manual calculation by clinicians or approximations from structured EHR data elements. Unstructured clinical notes contain rich information that could enhance risk assessment. We developed and validated a Retrieval-Augmented Generation (RAG) approach to extract CHA₂DS₂-VASc risk factors from unstructured notes in patients with AF.

Methods

We employed a RAG architecture paired with the large language model, Llama3.1, to extract features relevant to CHA₂DS₂-VASc scores from unstructured notes. The model was deployed on a random set of 1,000 clinical notes (934 AF patients) from Yale New Haven Health System (YNHHS). To establish a gold standard, 2 clinicians manually reviewed and labeled CHA₂DS₂-VASc risk factors in a random subset of 200 notes. The CHA₂DS₂-VASc scores were calculated for each patient using structured data alone and by incorporating risk factors identified with RAG. We assessed performance across risk factors using macro-averaged area under the receiver operating characteristic (AUROC). For external validation, we utilized 100 manually labeled clinical notes from the MIMIC-IV database.

Results

The RAG model demonstrated robust performance in extracting risk factors from clinical notes. In the 1000 clinical notes, RAG identified several risk factors more frequently than structured elements, including hypertension (82.4% vs 26.2%), stroke/TIA (62.9% vs 45.5%), vascular disease (83.4% vs 56.6%), and diabetes (84.1% vs 47.2%). In the 200 expert-annotated notes, the RAG approach achieved high performance for various risk factors, with AUROCs ranging from 0.96 to 0.98 for hypertension, diabetes, and age ≥75 years. Incorporating risk factors identified by RAG increased CHA₂DS₂-VASc scores compared with using structured data alone.

Conclusion

An LLM-optimized RAG can accurately extract CHA₂DS₂-VASc risk factors from unstructured clinical notes in AF patients. This approach can enable computable risk assessment and guide appropriate anticoagulation therapy.
LD-informed deep learning for Alzheimer’s gene loci detection using WGS data
Authors: Jo Taeho , Bice Paula , Nho Kwangsik , Saykin Andrew J. ,   the Alzheimer’s Disease Sequencing Project
Published: September 2024

INTRODUCTION

The exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer’s disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk.

METHODS

The Deep-Block was applied to a large-scale whole genome sequencing (WGS) dataset from the Alzheimer’s Disease Sequencing Project (ADSP), comprising 7,416 non-Hispanic white participants (3,150 cognitively normal older adults (CN), 4,266 AD).

RESULTS

30,218 LD blocks were identified and then ranked based on their relevance with Alzheimer’s disease. Subsequently, the Deep-Block identified novel SNPs within the top 1,500 LD blocks and confirmed previously known variants, includingAPOErs429358 and rs769449. Expression Quantitative Trait Loci (eQTL) analysis across 13 brain regions provided functional evidence for the identified variants. The results were cross-validated against established AD-associated loci from the European Alzheimer’s and Dementia Biobank (EADB) and the GWAS catalog.

DISCUSSION

The Deep-Block framework effectively processes large-scale high throughput sequencing data while preserving SNP interactions during dimensionality reduction, minimizing bias and information loss. The framework’s findings are supported by tissue-specific eQTL evidence across brain regions, indicating the functional relevance of the identified variants. Additionally, the Deep-Block approach has identified both known and novel genetic variants, enhancing our understanding of the genetic architecture and demonstrating its potential for application in large-scale sequencing studies.
Analysis of facial expressions recorded from patients during psychiatric interviews
Authors: Mineur L. , Heide M. , Eickhoff S. , Avram M. , Franzen L. , Buschmann F. , Schröpfer F. , Rogg H.V. , Andreou C. , Brügge N.S. , Handels H. , Borgwardt S. , Korda A.
Published: September 2024

Mental health research increasingly focuses on the relationship between psychiatric symptoms and observable manifestations of the face and body1. In recent studies2,3, psychiatric patients have shown distinct patterns in movement, posture and facial expressions, suggesting these elements could enhance clinical diagnostics.

The analysis of the facial expressions is grounded on the Facial Action Coding System (FACS)4. FACS provides a systematic method for categorizing facial expressions based on specific muscle movements, enabling detailed analysis of emotional and communicative behaviors. This method combined with recent advancements in Artificial Intelligence (AI) has shown promising results for the detection of the patient mental state.

We analyze video data from patients with various psychiatric symptoms, using open-source Python toolboxes for facial expression and body movement analysis. These toolboxes facilitate face detection, facial landmark detection, emotion detection and motion recognition. Specifically, we aim to explore the connection between these physical expressions and established diagnostic tools, like symptom severity scores, and finally enhance psychiatric diagnostics by integrating AI-driven analysis of video data.

By providing a more objective and detailed understanding of psychiatric symptoms, this study could lead to earlier detection and more personalized treatment approaches, ultimately improving patient outcomes. The findings will contribute to the development of innovative diagnostic tools that are both efficient and accurate, addressing a critical need in mental health care.
Returning Individual-Level Urgent or Emergent Research Results to Participants: The Project Baseline Health Study Experience
Authors: Pagidipati Neha , Heidenfelder Brooke , Kwee Lydia Coulter , Rodriguez Fatima , Chatterjee Ranee , Parikh Kishan S. , Khouri Michel G. , Stiller Jennifer , Eckstrand Julie , Marcom P. Kelly , Mettu Priyatham S. , Jaffe Glenn J. , Shashidhar Sumana , Swope Susan , Spielman Susan , Fraulo Elizabeth , Newby L. Kristin , Douglas Pamela , Wong Charlene , Green Robert , Shore Scarlet , Mega Jessica , Hernandez Adrian , Campbell Paul , Mahaffey Kenneth W. , Shah Svati H.
Published: September 2024

Background

Returning results to research participants is increasingly recognized as an ethical mandate, yet little is known about best practices to optimally communicate urgent or emergent results.

Methods

The Project Baseline Health Study (PBHS) was a prospective observational cohort study of 2,502 participants enrolled from 2017-2019 and followed through 2023. The cohort represented a broad spectrum of health and disease, enriched to include participants with an elevated risk for breast or ovarian cancer, lung cancer, and/or atherosclerotic cardiovascular disease (60% of participants). Urgent or emergent results were returned during or after the baseline visit from vital signs; clinical laboratory testing; and ocular, cardiovascular, and pulmonary imaging.

Results

Among 2,002 participants in this analysis, 39.7% had at least one urgent or emergent finding returned, representing a total of 1,159 results returned over 3 years. The most commonly returned results were eye findings (n=246), pulmonary nodules (n=159), abnormal stress echocardiograms (n=123), abnormal rest electrocardiograms (bradycardia) (n=74), and lung parenchyma findings (n=55). Participants with urgent or emergent incidental findings were older (mean [SD] 58.0 [16.2] years vs. 48.0 [16.6] years) with a greater burden of cardiovascular, metabolic, or cancer comorbidities than those without urgent or emergent incidental findings.

Conclusions

This report from the PBHS study is one of the first to describe a process to systematically return urgent or emergent results to research participants. This process led to the successful return of clinically important results to participants but also required significant time and effort from study clinicians and staff.

ClinicalTrials.govIdentifier:NCT03154346
Tissue of Origin Characterization of Cell Free DNA in Seminal Plasma: Implications for New Liquid Biopsies
Authors: Huang Stephanie , Hart James C. , Smith James F , Bench Shellie , Yepes Laura Rivas , Griscom Bailey , Clark-Langone Kim M.
Published: September 2024

Liquid biopsies are becoming increasingly used for the detection and monitoring of disease states. While cell free DNA (cfDNA) in blood and urine have been well studied, much less is known about the composition of cfDNA in seminal fluid. We sought to characterize cfDNA in seminal fluid through tissue of origin studies using methylation analysis in men aged 21-60 yrs. We confirmed the observations of others that seminal fluid contains an abundance of cfDNA that is both nucleosomal and >1 kb. However, here we demonstrate for the first time that the high molecular weight (HMW) DNA harbors a lower sperm signal and higher somatic cell signal compared to the nucleosomal fraction. Prostate, granulocytes and kidney showed a mean predicted increased contribution of 6.2%, 4.9% and 2.9%, respectively in the HMW fraction. While sperm was the predominant signal in most men without vasectomies, the proportion of predicted prostate contribution reached as high as 26.5% in the HMW fraction. In other subjects without vasectomies, granulocyte cfDNA made up most of the signal. We also observed subject-specific cfDNA size distribution patterns that were reproducible over time, irrespective of abstinence times. These results suggest that seminal fluid is a rich source of cfDNA from various somatic cell types, and enriching for the HMW fraction would yield even higher sensitivity for somatic cfDNA detection. Considering these novel findings, it appears that seminal fluid may be able to serve as liquid biopsy for the detection and monitoring of prostate cancer, benign prostate hyperplasia, prostatitis and infertility.
Transformers in Skin Lesion Classification and Diagnosis: A Systematic Review
Authors: Adebiyi Abdulmateen , Abdalnabi Nader , Simoes Eduardo J. , Becevic Mirna , Smith Emily Hoffman , Rao Praveen
Published: September 2024

Skin lesion classification is a critical task in dermatology, aiding in the early diagnosis and treatment of skin cancer. In recent years, transformer-based models, originally developed for Natural Language Processing (NLP) tasks, have shown promising results in many classification tasks specifically the image classification domains. This systematic review aims to provide a comprehensive overview of the current state of research on the application of transformers in skin lesion classification. Over the period 2017-2023, this systematic review investigated the application of transformer-based models in skin lesion classification, focusing on 57 articles retrieved from prominent databases which are PubMed, Scopus, and Medline. The inclusion criteria encompass studies centering on transformer-based models for skin lesion classification, utilization of diverse datasets (dermoscopic images, clinical images, or histopathological images), publication in peer-reviewed journals or conferences, and availability in English. Conversely, exclusion criteria filter out studies not directly related to skin lesion classification, research applying algorithms other than transformer-based models, non-academic articles lacking empirical data, papers without full-text access, and those not in English. Our findings underscore the adaptability of transformers to diverse skin lesion datasets, the utilization of pre-trained models, and the integration of various mechanisms to enhance feature extraction.
Cardiomyocyte-derived circulating extracellular vesicles allow a non-invasive liquid biopsy of myocardium in health and disease
Authors: Spanos Michail , Gokulnath Priyanka , Li Guoping , Hutchins Elizabeth , Meechoovet Bessie , Sheng Quanhu , Chatterjee Emeli , Sharma Ritin , Carnel-Amar Natacha , Lin Claire , Azzam Christopher , Ghaeli Ima , Amancherla Kaushik V , Victorino José Fabian , Garcia-Mansfield Krystine , Pfeffer Ryan , Sahu Parul , Lindman Brian R. , Elmariah Sammy , Gamazon Eric R. , Betti Michael J. , Bledsoe Xavier , Lance Michelle L. , Absi Tarek , Su Yan Ru , Do Ngoc , Contreras Marta Garcia , Varrias Dimitrios , Kladas Michail , Radulovic Miroslav , Tsiachris Dimitris , Spanos Anastasios , Tsioufis Konstantinos , Ellinor Patrick T. , Tucker Nathan R. , Januzzi James L. , Pirrotte Patrick , Talisman Tijana Jovanovic- , Keuren-Jensen Kendall Van , Shah Ravi , Das Saumya
Published: September 2024

The ability to track disease without tissue biopsy in patients is a major goal in biology and medicine. Here, we identify and characterize cardiomyocyte-derived extracellular vesicles in circulation (EVs; “cardiovesicles”) through comprehensive studies of induced pluripotent stem cell-derived cardiomyocytes, genetic mouse models, and state-of-the-art mass spectrometry and low-input transcriptomics. These studies identified two markers (POPDC2,CHRNE) enriched on cardiovesicles for biotinylated antibody-based immunocapture. Captured cardiovesicles were enriched in canonical cardiomyocyte transcripts/pathways with distinct profiles based on human disease type (heart failure, myocardial infarction). In paired myocardial tissue-plasma from patients, highly expressed genes in cardiovesicles were largely cardiac-enriched (vs. “bulk” EVs, which were more organ non-specific) with high expression in myocardial tissue by single nuclear RNA-seq, largely in cardiomyocytes. These results demonstrate the first “liquid” biopsy discovery platform to interrogate cardiomyocyte states non-invasively in model systems and in human disease, allowing non-invasive characterization of cardiomyocyte biology for discovery and therapeutic applications.
Correspondence: Recurrent ECSIT mutation encoding V140A triggers hyperinflammation and promotes hemophagocytic syndrome in extranodal NK/T cell lymphoma
Authors: Lim Jing Quan , Huang Dachuan , Ong Choon Kiat
Published: September 2024

Recurrent somatic mutation in theECSITgene encoding p.V140A was reported in 19.3% (17/88) extranodal natural-killer/T cell lymphoma (ENKTL) and was associated with hemophagocytic syndrome (HPS). However, another cohort of similar geographical descent also had the ECSITV140Amutation as germline in 20.0% (5/25) of ENKTL and none were somatic. The reanalysis of published data revealed that the reported somatic ECSITV140Acould be germline as well. First-digit analysis on the IDs of sequencing read also found irregularity among the data that initially reported the somatic ECSITV140Amutation. As such, this study questions the only somatic genetic link of HPS in ENKTL and also introduces a simple well-known algorithm to detect data irregularity in voluminous genomic sequencing data.
DNA methylation age acceleration is associated with incident cognitive impairment in the Health and Retirement Study
Authors: Blostein Freida , Bakulski Kelly M. , Fu Mingzhou , Wang Herong , Zawistowski Matthew , Ware Erin B.
Published: September 2024

Background

DNA methylation clocks have emerged as promising biomarkers for cognitive impairment and dementia. Longitudinal studies exploring the link between DNA methylation clocks and cognitive decline have been constrained by limited sample sizes and a lack of diversity.

Objective

Our study aimed to investigate the longitudinal associations between DNA methylation clocks and incident cognitive impairment using a larger sample size encompassing a US nationally representative sample from the Health and Retirement Study.

Methods

We measured DNA methylation age acceleration in 2016 by comparing the residuals of DNA methylation clocks, including GrimAge, against chronological age. Cognitive decline was determined by the change in Langa-Weir cognition status from 2016 to 2018. Using multivariable logistic regression, we evaluated the link between DNA methylation age acceleration and cognitive decline, adjusting for cell-type proportions, demographic, and health factors. We also conducted an inverse probability weighting analysis to address potential selection bias from varying loss-to-follow-up rates.

Results

The analytic sample (N=2,713) at baseline had an average of 68 years old, and during the two years of follow-up, 12% experienced cognitive decline. Participants who experienced cognitive decline during follow-up had higher baseline GrimAge (mean = 1.2 years) acceleration compared to those who maintained normal cognitive function (mean = -0.8 years, p < 0.001). A one-year increase in GrimAge acceleration was associated with 1.05 times higher adjusted and survey-weighted odds of cognitive decline during follow-up (95% CI: 1.01-1.10). This association was consistent after accounting for loss-to-follow-up (OR = 1.07, 95% CI: 1.04-1.11).

Conclusion

Our study offers insights into DNA methylation age acceleration associated with cognitive decline, suggesting avenues for improved prevention, diagnosis, and treatment.
Severe Mitral Regurgitation in Paradoxical Low-Flow Low-Gradient Severe Aortic Stenosis
Authors: Dahan Shani , Dal-Bianco Jacob , Plakht Ygal , Namasivayam Mayooran , Capoulade Romain , Zeng Xin , Passeri Jonathan J , Yucel Evin , Picard Michael H , Levine Robert A , Hung Judy
Published: September 2024

Background

Patients with paradoxical low-flow, low-gradient severe aortic stenosis (LFLGAS) exhibit low transvalvular flow rate (Q), while maintaining preserved left ventricular ejection fraction (LVEF). Concomitant severe mitral regurgitation (MR) contributes to the low flow state, adding complexity to diagnosis and management. This study aimed to examine the impact of severe MR on outcomes in paradoxical LFLGAS.

Methods

Data from an institutional echo database identified 1,189 patients with adjudicated severe aortic stenosis (AVA≤1.0 cm2), low transaortic gradients (mean gradient<40 mmHg), preserved LVEF (≥50%), and low flow rate (Q≤210 ml/sec), to confirm paradoxical LFLGAS. Subgroups were based on MR severity (severe and non-severe). Clinical outcomes included all-cause mortality, aortic valve replacement (AVR), heart failure hospitalizations, and a composite outcome.

Results

In the severe MR group (n=80), patients had lower flow rates, increased LV dimensions and a more eccentric hypertrophy pattern compared to non-severe MR (n=1,109). Over a median 5-year follow-up, severe MR correlated with higher all-cause mortality (p=0.02) and AVR rates (p=0.012). After adjustment, severe MR was independently associated with increased all-cause mortality risk (HR=1.43, p=0.011) and composite outcome (HR=1.64, p<0.001). AVR significantly reduced mortality at every MR degree, with the most substantial impact in severe MR (HR=0.18, p<0.001). Propensity-adjusted models demonstrated a stronger AVR impact with increasing MR degree (p-for-interaction=0.044).

Conclusions

Severe MR in paradoxical LFLGAS is associated with adverse outcomes and distinctive LV remodeling. Aortic valve replacement improves survival across all MR grades, with greater impact in severe MR.
Study Protocol. The CASPAR study protocol. Can cervical stiffness predict successful vaginal delivery after induction of labour? A feasibility, cohort study
Authors: Medford Elizabeth , Lane Steven , Merriel Abi , Sharp Andrew , Care Angharad
Published: September 2024

Background

Induction of labour (IOL) is a common obstetric intervention in the UK, affecting up to 33% of deliveries. IOL aims to achieve a vaginal delivery prior to spontaneous onset of labour to prevent harm from ongoing pregnancy complications and is known to prevent stillbirths and reduce neonatal intensive care unit admissions. However, IOL doesn’t come without risk and overall, 20% of mothers having an induction will still require a caesarean section birth and in primiparous mothers this rate is even higher.

There is no reliable predictive bedside tool available in clinical practice to predict which patient’s undergoing the IOL process will result in a vaginal birth; the fundamental aim of the IOL process. The Bishop’s Score (BS) remains in routine clinical practice as the examination tool to assess the cervix prior to IOL, despite it being proven to be ineffective as a predictive tool and largely subjective. This study will assess the use of the Pregnolia System, a new objective antenatal test of cervical stiffness. This study will explore its’ potential for pre-induction cervical assessment and indication of delivery outcome following IOL.

Methods

CASPAR is a feasibility study of term, primiparous women with singleton pregnancies undergoing IOL. Cervical stiffness will be assessed using the Pregnolia System; a novel, non-invasive, licensed, CE-marked, aspiration-based device proven to provide objective, quantitative cervical stiffness measurements represented as the Cervical Stiffness Index (CSI, in mbar). A measurement is obtained by applying the sterile single-use Pregnolia Probe directly to the anterior lip of the cervix, visualised via placement of a speculum.

Following informed consent, CASPAR study participants will undergo the Pregnolia System cervical stiffness assessment prior to their IOL process commencing. Participant questionnaires will evaluate the acceptability of this assessment tool in this population. This study will directly compare this novel antenatal test to the current BS for both patient experience of the different cervical assessment tools and for IOL outcome prediction.

Discussion

This feasibility study will explore the use of this novel device in clinical practice for pre-induction cervical assessment and delivery outcome prediction. Our findings will provide novel data that could be instrumental in transforming clinical practice surrounding IOL. Determining recruitment rates and acceptability of this new assessment tool in this population will inform design of a further powered study using the Pregnolia System as the point-of-care, bedside cervical assessment tool within an IOL prediction model.

Study registration

This study is sponsored by The University of Liverpool and registered at ClinicalTrials.gov, identifierNCT05981469, date of registration 7thJuly 2023.
Effect of non-drug Intervention on Cognitive Function and Blood Sugar Control of Type 2 Diabetes patients with Mild Cognitive Impairment: A Meta-analysis Protocol
Authors: Wenhao Su , Hairong Jia , Yanru Wang , Luo Yang , Xueling Li , Jiaqi Zhang , Zhaoyang Wei , Pepertual Tsikwa
Published: September 2024

This study aims to assess non-drug therapies’ safety and effectiveness on cognitive function and blood glucose control of type 2 diabetes with mild cognitive impairment (T2DM-MCI) patients in randomized controlled trials by meta-analysis, providing constructive evidence for non-drug treatment decision-making. The system review plan will strictly follow the Systematic Review and Meta-Analysis Protocols entry for reporting. PubMed, EMBASE, Cochrane Library, CINAHL, Web of Science, CNKI, WANGFANG Database, and SinoMed will be systematically searched with Chinese and English language restrictions, and all randomized controlled trials comparing non-drug treatment with usual care or no intervention or placebo to study cognitive impairment in T2DM-MCI patients will be included. We will also manually search for cited literature. Our primary outcomes are cognitive function and blood sugar control. The risk of bias will be assessed for all studies using the Cochrane risk-of-bias tool (RoB 2) for Systematic Review of Intervention-version 5.1.0. Where possible, meta-analysis using random-effects models will be performed, otherwise, a qualitative summary will be provided. We will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-P) guidelines. This meta-analysis compares the efficacy of non-drug interventions for mild cognitive impairment in type 2 diabetes mellitus. It will provide reliable evidence for patients, clinicians, and researchers.

The methodological protocol was in registered in the PROSPERO (CRD 42024496248).
Construction of the index system for screening and assessment of dysphagia in Chinese elderly people based on Delphi method
Authors: Gaoqiang Li , Yue Chen , Qinge Yong
Published: September 2024

Background

Dysphagia is an important factor affecting aspiration pneumonia in the elderly, which will greatly increase the risk of poor prognosis and even death. Early detection, diagnosis and effective prevention are the key to improve the prognosis of patients. However, there is currently no systematic tool for screening and evaluating swallowing disorders in the elderly.

Objective

This study aimed to establish an index system for the screening and evaluation of dysphagia in the elderly, and to provide evidence for the screening and evaluation of dysphagia in the community and clinic.

Methods

The draft of the index system was determined based on the combination of literature review and clinical practice. The Delphi method was applied to conduct expert correspondence consultation, and the index system for screening and evaluation of dysphagia in the elderly was established. The weight of each index was determined by analytic hierarchy process.

Results

A total of 19 experts in related fields were consulted for 3 rounds. The questionnaire recovery rates were 94.7%, 100% and 100%, respectively. 17 (89.5%), 14 (73.7%) and 5 (26.3%) experts put forward modification opinions, respectively. The expert authority coefficient was 0.920, and the Kendall harmony coefficient was 0.219, 0.261 and 0.306, respectively, with statistical significance (P < 0.001). Finally, the index system for the screening and evaluation of dysphagia in the elderly includes 3 first-level indicators, 10 second-level indicators and 26 third-level indicators.

Conclusion

The experts in this study are highly motivated and authoritative, and the established index system for the screening and evaluation of dysphagia in the elderly is scientific, reasonable and targeted, which can provide reference for the screening and evaluation of dysphagia in the community and clinical elderly patients.
Epidemiological pattern of trauma among children 0 - 9 years in Cameroon
Authors: Kibu Odette , Maqungo Sithombo , Nguefack-Tsague Georges , Maqungo Sithombo , Nsagha Dickson Shey , Dissak Delon Fanny N. , Touko Darwin , Tanue Elvis Asangbeng , Oke Rasheedat , McCoy Sandra I. , Christie Sabrinah Ariane , Juillard Catherine , Mefire Alain Chichom
Published: September 2024

Background

In low- and middle-income countries, trauma is the leading cause of death among youth and it is also a major cause of disability. Globally, more than 1,600 children and adolescents below the age of 19-years die every day from preventable injuries. Traffic-related injuries, falls, sports-related injuries, assaults, burns, and drownings are the most commonly reported causes of traumatic mortality among children. The mechanism of injury is always diverse in different contexts due to the differences in social determinants of health.

Objectives

To determine the epidemiological pattern of trauma among children 0 – 9 years in Cameroon.

Methods

This is a retrospective analysis of prospectively collected data from the Cameroon Trauma Registry currently running in 10 pilot sites across seven of the ten regions of Cameroon. We retrieved data for all children aged 0 - 9 years from June 2022 to August 2023. Data was analyzed with respect to the demographics, injury characteristics and outcomes.

Results

Of the 5,439 patients captured in the trauma registry, 267 (4.9%) were children aged 0-9 years. Over 50% (152/267) of the patients were males with 35% (93/267) from rural settings. The top injury mechanism was road traffic injuries (RTI) [137(52.1%)]. These injuries occurred on the streets [142(53.4%)] during leisure activities [205(78.5%)]. Majority of children [104(39%)] involved in RTI injuries were pedestrians and no prehospital care offered to 216(82.8%) of injured children. A total of 39 (16.9%) were discharged with major disability, 111 (48.1%) had limited ability to move and 5 (2.2%) demised or succumbed to their injuries. There was a significant association between injury activity and gender (P = 0.006). Unlike the females, majority of the males were discharged with major disability [21 (53.8%)].

Conclusion

This preliminary analysis highlights the burden of trauma among children aged 0 – 9 years and its contribution to the proportion of disabled persons in Cameroon. Leisure activities on the streets increased the number of pediatric injuries especially among males. It is therefore imperative to put in place or reinforce environmental interventions to reduce the burden of pediatric injuries.
Telehealth during and beyond the COVID-19 Pandemic: Evidence from Licensed Dietitians in an Emerging Economy
Authors: Assaad Maya , Chamma Nour , Mateev Miroslav , Rizk Rana
Published: September 2024

Background

The SARS-Cov-2 pandemic (COVID-19) sudden onset disrupted the direct access to face-to-face nutrition consultation fostering the rapid adoption of Telehealth by dietitians.

Objective

This study investigates Telehealth use among Lebanese Licensed Dietitians (LDs) amid COVID-19, in the absence of national Telehealth practical guidelines (TPG), and offers insights on Telehealth application under uncertainties of pandemic event, economic crisis, and destructed infrastructure occurring simultaneously in Lebanon.

Design

A cross-sectional study during March 2023, using an anonymous online survey (44 questions), diffused through the Lebanese Order of Dietitians and social media platforms.

Participants

The sample (n=94) consisted mostly of females (98.9%) and young dietitians (mean(SD) age: 30.54(6.41) years) having a mean(SD) of 7.89(5.7) years of experience. Most respondents identified clinical nutrition as their primary practice area (87.2%), mostly in weight management (84%).

Main outcome measures

Telehealth experience amid COVID-19 including tools utilized in remote consultations, barriers, facilitators, and perspectives of Telehealth use.

Statistical analyses

Descriptive analysis (counts, frequencies) using SPSS version 28.

Results

Although 48.4% of LDs reported using Telehealth prior COVID-19, this proportion increased to 97.8% during the pandemic. The most common tools used were WhatsApp (90.3%), Zoom (72.0%), and E-mails (41.9%). Reported barriers included bad internet connection (74.2%), patients preferring face-to-face consultation (61.3%), and patients lacking technical literacy (33.3%); benefits included scheduling and time flexibility (83.9%), decrease in practice-related costs (77.4%), and compliance with social distancing measures (53.8%). The majority agreed that Telehealth is needed (78.5%) and applicable in the Lebanese context (64.6%) and expressed the need for Telehealth trainings (78.5%) and TPG for nutrition care (74.2%).

Conclusions

This study recognizes increasing use of Telehealth in Lebanon, warranting the development of Telehealth nutrition care infrastructure comprising national regulations and evidence-based practical guidelines to respond to the innovation in the healthcare industry, and to assure Telehealth sustainability in LDs’ routine practice.
COVID-19 Vaccine effectiveness among Healthcare Workers during the Omicron Period in the country of Georgia, January – June 2022
Authors: Ward Caleb L. , Rojas Castro Madelyn Yiseth , Chakhunashvili Giorgi , Chitaze Nazibrola , Finci Iris , Pebody Richard , Kissling Esther , Katz Mark A. , Sanodze Lia
Published: September 2024

Introduction

Understanding COVID-19 vaccine effectiveness (VE) in healthcare workers (HCWs) is critical to inform vaccination policies. We measured COVID-19 VE against laboratory-confirmed symptomatic infection in HCWs in the country of Georgia from January – June 2022, during a period of Omicron circulation.

Methods

We conducted a cohort study of HCWs in six hospitals in Georgia. HCWs were enrolled in early 2021. Participants completed weekly symptom questionnaires. Symptomatic HCWs were tested by RT-PCR and/or rapid antigen test (RAT). Participants were also routinely tested, at varying frequencies during the study period, for SARS-CoV-2 by RT-PCR or RAT, regardless of symptoms. Serology was collected quarterly throughout the study and tested by electrochemiluminescence immunoassay for SARS-CoV-2 antibodies. We estimated absolute and relative VE of a first booster dose compared to a primary vaccine series as (1-hazard ratio)*100 using Cox proportional hazards models.

Results

Among 1253 HCWs, 141 (11%) received a primary vaccine series (PVS) and a first booster, 855 (68%) received PVS only, and 248 (20%) were unvaccinated. Most boosters were BNT162b2 (Comirnaty original monovalent) vaccine (90%) and BIBP-CorV vaccine (Sinopharm) (9%). Most PVS were BNT162b2 vaccine (68%) and BIBP-CorV vaccine (24%). Absolute VE for a first booster was 40% (95% Confidence Interval (CI) -56 – 77) at 7– 29 days following vaccination, -9% (95% CI -104 – 42) at 30 – 59 days, and - 46% (95% CI -156 – 17) at ≥ 60 days. Relative VE of first booster dose compared to PVS was 58% (95% CI 1 – 82) at 7– 29 days following vaccination, 21% (95% CI -33 – 54) at 30 – 59 days, and -9% (95% CI -82 – 34) at ≥ 60 days.

Conclusion

In Georgia, first booster dose VE against symptomatic SARS-CoV-2 infection among HCWs was moderately effective but waned very quickly during Omicron. Increased efforts to vaccinate priority groups in Georgia, such as healthcare workers, prior to periods of anticipated high COVID-19 incidence are essential.
A pilot study to identify blood-based markers associated with response to treatment with Vedolizumab in patients with Inflammatory Bowel Disease
Authors: Rioux John D. , Boucher Gabrielle , Forest Anik , Bouchard Bertrand , Coderre Lise , Daneault Caroline , Frayne Isabelle Robillard , Legault Julie Thompson , Consortium iGenoMed , Bitton Alain , Ananthakrishnan Ashwin , Lesage Sylvie , Xavier Ramnik J. , Rosiers Christine Des
Published: September 2024

The inflammatory bowel diseases (IBD) known as Crohn’s disease (CD) and ulcerative colitis (UC) are chronic inflammatory diseases of the gastrointestinal tract believed to arise because of an imbalance between the epithelial, immune and microbial systems. It has been shown that biological differences (genetic, epigenetic, microbial, environmental, etc.) exist between patients with IBD, with multiple risk factors been associated with disease susceptibility and IBD-related phenotypes (e.g. disease location). It is also known that there is heterogeneity in terms of response to therapy in patients with IBD, including to biological therapies that target very specific biological pathways (e.g. TNF-alpha signaling, IL-23R signaling, immune cell trafficking, etc.). It is hypothesized that the better the match between the biology targeted by these advanced therapies and the predominant disease-associated pathways at play in each patient will favor a beneficial response. The aim of this pilot study was to identify potential biological differences associated with differential treatment response to the anti α4β7 integrin therapy known as Vedolizumab. Our approach was to measure a broad range of analytes in the serum of patients prior to initiation of therapy and at the first clinical assessment visit, to identify potential markers of biological differences between patients at baseline and to see which biomarkers are most affected by treatment in responders. Our focus on early clinical response was to study the most proximal effects of therapy and to minimize confounders such as loss of response that occurs further distal to treatment initiation. Specifically, we performed targeted analyses of >150 proteins and metabolites, and untargeted analyses of >1100 lipid entities, in serum samples from 92 IBD patients (42 CD, 50 UC) immediately prior to initiation of therapy with vedolizumab (baseline samples) and at their first clinical assessment (14-week samples). We found lower levels of SDF-1a, but higher levels of PDGF-ββ, lactate, lysine, phenylalanine, branched chain amino acids, alanine, short/medium chain acylcarnitines, and triglycerides containing myristic acid in baseline serum samples of responders as compared to non-responders. We also observed an increase in serum levels of CXCL9 and citrate, as well as a decrease in IL-10, between baseline and week 14 samples. In addition, we observed that a group of metabolites and protein analytes was strongly associated with both treatment response and BMI status, although BMI status was not associated with treatment response.
AlphaFold2 and AlphaFold3 leads to significantly different results in human-parasite interaction prediction
Authors: Ozden Burcu , Cuesta-Astroz Yesid , Karaca Ezgi
Published: September 2024

Parasitic diseases pose a significant global health challenge with substantial socioeconomic impact, especially in developing countries. Combatting these diseases is difficult due to two factors: the resistance developed by parasites to existing drugs and the underfunded research efforts to resolve host-parasite interactions. To address the latter, we focused on 276 human-parasite interaction predictions involving 15 parasitic species known to cause infections in humans. We aimed to validate these interactions by using AlphaFold2-Multimer v2.2 (AF2) and AlphaFold3 (AF3) modeling. Overall, our findings show that, in the context of human-parasite interactions, AF2 and AF3 produce distinct models and score distributions, with no significant correlation between their top-ranked predictions. We recognize that predicting host-parasite interactions is particularly challenging due to the absence of typical coevolutionary signals. Nevertheless, the differences in scores and models between AF2 and AF3 are striking and warrant further investigation, which could only be performed upon the release of AF3.
High-risk neuropsychiatric copy number variants are associated with convergent transcriptomic changes in human brain cells
Authors: Dugan Gabi , Akula Nirmala , Marenco Stefano , Auluck Pavan K , Raznahan Armin , Liu Siyuan , DeCasien Alex , Xu Qing , Feng Ningping , Kolachana Bhaskar , Jiang Xueying , Gregory Michael D , Berman Karen F , Hoffman Gabriel , Roussos Panos , McMahon Francis J , Schulmann Anton
Published: September 2024

Large, recurrent copy number variants (CNVs) are among the strongest risk factors for neuropsychiatric conditions, contributing to multiple phenotypes with overlapping psychiatric and cognitive symptoms. However, the molecular basis of this convergent risk remains unknown. We evaluated the human brain transcriptome in carriers of nine high-risk neuropsychiatric CNVs and matched non-carriers using single nucleus RNA-sequencing. Brain tissue from carriers displayed widespread disruptions of gene expression, with deletions showing greater changes than the reciprocal duplications. Functional enrichment analysis revealed changes in mitochondrial energy metabolism and synaptic function that converged across CNVs and cell types. For mirror CNVs, the direction of effects was often reversed between deletions and duplications and showed correlation with CNV gene dosage. These findings suggest that a shared pathophysiology underlies risk for convergent brain phenotypes across CNVs and point toward promising therapeutic targets.