bluuebunny/crossref_metadata_2025_split huggingface dataset:
A qualitative study exploring Emergency Department Staff attitudes to COVID-19 research
Authors: Quinn Joanna , Ho Antonia , Blunsum Andrew , Lowe David J 
Published: July 2024

ABSTRACTIntroductionResearch conducted in the Emergency Department (ED) is essential for improving patient care and advancing evidence-based practice. However, there are several challenges to research engagement in the ED, including lack of time, awareness of research opportunities, and concerns about the impact on clinical duties.This study aimed to explore the attitudes and perceptions of ED staff involved in an enhanced syndromic surveillance of hospitalised severe acute respiratory illness (CHARISMA study) during the COVID-19 pandemic.MethodsThis qualitative study utilised semi-structured interviews with a mix of nursing and medical staff with a range of experience levels. Thematic analysis was then undertaken.Results9 respondents informed our four key themes: the value of research, the user experience of the study tools, clinician research engagement and improvement recommendations for future iterations of the study. Our findings reveal that ED staff value research and recognise its importance in improving patient care and evidence-based practice. However, they also face significant challenges in participating in research due to time constraints, lack of awareness of research opportunities, and concerns about the impact on clinical duties.ConclusionTo address these challenges, we propose strategies to enhance research engagement in the ED, including providing more support from senior staff, more transparent communication about research studies, training on research methods and tools, and opportunities for feedback and input. Implementing these measures, we can enhance the environment for research in the ED, enabling wider staff contribution.What is already known on this topicData collected in the Emergency Department by clinical and research teams was an important contribution to COVID research including multinational platform studies. However, little is known about the attitudes of front-line staff involved in this process. This study responds to a paucity of literature with regards to clinician attitudes towards being asked to participate in research during the COVID-19 pandemic in an acute setting.What this study addsThis study provides the first published description of ED staff attitudes to their involvement in research during a global pandemic. It highlights the challenges that are posed by the unique pressures of the ED setting - namely activity and unpredictability, time pressure, and in some cases, a lack of resources.How this study might affect research, practice or policyThis study reinforces the need, value and support of staff to conduct research in an ED setting. We hope that this study provides useful insight to researchers on potential pitfalls to beware when undertaking their own original research. We anticipate that many of our findings are highly generalisable to other ED and acute care settings and hope that this encourages further expansion of this area.
Monovalent XBB.1.5 COVID-19 vaccine effectiveness against hospitalisations and deaths during the Omicron BA.2.86/JN.1 period among older adults in seven European countries: A VEBIS-EHR Network Study
Authors: Nunes Baltazar , Humphreys James , Nicolay Nathalie , Braeye Toon , Van Evercooren Izaak , Hansen Christian Holm , Moustsen-Helms Ida Rask , Sacco Chiara , Fabiani Massimo , Castilla Jesús , Martínez-Baz Iván , Meijerink Hinta , Machado Ausenda , Soares Patricia , Ljung Rickard , Pihlström Nicklas , Nardone Anthony , Bacci Sabrina , Monge Susana 
Published: July 2024

AbstractBackgroundMonovalent XBB.1.5 vaccine was administered among those aged ≥65 years in EU/EEA countries in autumn 2023; soon after SARS-Cov-2 BA.2.86/JN.1 lineages became dominant. We aimed to estimate XBB.1.5 vaccine effectiveness (VE) against COVID-19-related hospitalisations and deaths during a period of BA.2.86/JN.1 predominance using a European multi-country study.MethodsWe linked electronic health record data to create historical cohorts in Belgium, Denmark, Italy, Navarre (Spain), Norway, Portugal and Sweden. We included individuals aged ≥65 years eligible for the autumnal 2023 COVID-19 vaccine with at least a primary series. Follow-up started when ≥80% of country-specific sequenced viruses were BA.2.86/JN.1 lineages (4/12/23 to 08/01/24) and ended 25/02/2024. At study site level, we estimated the overall vaccine confounder-adjusted (for age, sex, country’s region, comorbidities and previous booster doses) hazard ratio (aHR) of COVID-19 hospitalisations and deaths between individuals with ≥14 days after vaccination and individuals unvaccinated in autumn 2023, as well as by time since vaccination and stratified by age groups. VE was estimated as (1-pooled aHR)x100 with a random effects model.ResultsXBB.1.5 VE against COVID-19 hospitalisations was 50% (95%CI: 45 to 55) and 41% (95%CI: 35 to 46) in 65-79-year-olds and in ≥80-year-olds respectively. VE against COVID19-related-death was 58% (95%CI: 42 to 69) and 48% (95%CI: 38 to 57), respectively, in both age groups. VE estimates against each respective outcome declined in all age group over time.ConclusionMonovalent XBB.1.5 vaccine had a moderate protective effect against severe COVID-19 likely caused by BA.2.86/JN.1 during the 2023/2024 winter, among persons aged ≥65.
Identification of a NovelSLC2A9Gene Association with LDL-C levels and Evaluation of Polygenic Scores in a Multi-Ancestry Genome Wide Association Study
Authors: Umlai Umm-Kulthum Ismail , Toor Salman M. , Al-Sarraj Yasser A. , Mohammed Shaban , Al Hail Moza S H , Ullah Ehsan , Kunji Khalid , El-Menyar Ayman , Gomaa Mohammed , Jayyousi Amin , Saad Mohamad , Qureshi Nadeem , Al Suwaidi Jassim M , Albagha Omar M E 
Published: July 2024

AbstractThe genetic determinants of low-density lipoprotein cholesterol (LDL-C) levels in blood have been predominantly explored in European populations and remain poorly understood in Middle Eastern populations. We investigated the genetic architecture of LDL-C variation in the Middle Eastern population of Qatar. Whole genome sequencing data of 13,701 individuals (discovery; n=5939, replication; n=7762) from the population-based Qatar Biobank (QBB) cohort was used to conduct a genome-wide association study (GWAS) on serum LDL-C levels. We replicated 168 previously reported loci from the largest LDL-C GWAS conducted by the Global Lipids Genetics Consortium (GLGC), with high correlation in allele frequencies (R2=0.77) and moderate correlation in effect sizes (Beta; R2=0.53). We also performed a multi-ancestry meta-analysis with the GLGC study using MR-MEGA (Meta-Regression of Multi-Ethnic Genetic Association). The multi-ancestry meta-analysis identified one novel LDL-C-associated locus; rs10939663 (SLC2A9; genomic control-correctedP=1.25×10−8). Lastly, we developed Qatari-specific polygenic score (PGS) panels from our discovery dataset and tested their performance in the replication dataset against PGS derived from other ancestries. The multi-ancestry derived PGS (PGS000889) performed best at predicting LDL-C levels, whilst the Qatari-derived PGS panels also showed comparable performance. Overall, we report one novel gene variant associated with LDL-C levels, which may be explored further to decipher its potential role in the etiopathogenesis of cardiovascular diseases. Our findings also highlight the importance of population-based genetics in developing PGS panels for clinical utilization.
Comparison of excess deaths and laboratory-confirmed COVID-19 deaths during a large Omicron epidemic in 2022 in Hong Kong
Authors: Xin Hualei , Law Alexandra H. T. , Cheung Justin K. , Lin Yun , Wu Peng , Li Zhongjie , Cowling Benjamin J. , Yang Weizhong , Wong Jessica Y. 
Published: July 2024

ABSTRACTBackgroundUsing a local elimination strategy, Hong Kong was able to minimize COVID-19 mortality in 2020 and 2021, but a large epidemic caused by the Omicron variant occurred in 2022. We aimed to estimate the overall, age-, sex-, epidemic period- and cause-specific excess mortality in 2022 in Hong Kong and compared excess mortality to laboratory-confirmed COVID-19 mortality.MethodsNegative binomial regression analysis was used to model time series of weekly all-cause and cause-specific deaths from 2010 to 2021 to predict the weekly number of deaths in 2022 against counterfactual baselines projected from the trends in the absence of a pandemic. The estimated excess deaths were compared with laboratory-confirmed COVID-19 deaths overall and by age and epidemic period.ResultsWe estimated that there were 13,500 (95% CI: 13,400-13,600) excess deaths in 2022, which was slightly higher than the 12,228 deaths recorded with laboratory-confirmed COVID-19, with the majority of the excess deaths and laboratory-confirmed deaths occurring among older adults. The increased number of excess deaths over laboratory-confirmed COVID-19 deaths was most substantial from February to April 2022 (a difference of 847 deaths), when the largest Omicron wave peaked. Most of the excess deaths (78%) were from respiratory causes, while 10% were from cardiovascular causes. A slight reduction in malignant neoplasm mortality was identified among older adults in 2022.ConclusionsA substantial increase in population mortality was identified in 2022 in Hong Kong, slightly larger than the laboratory-confirmed COVID-19 deaths. Apart from the possibility of underdiagnosis, excess deaths might also be attributed to the overload of healthcare resources during the pandemic. Deaths from COVID-19 may have displaced some deaths that would otherwise have occurred due to other causes although we did not find evidence of substantial mortality displacement.
Non-linear genetic regulation of the blood plasma proteome
Authors: Sigurdsson Arnor I. , Gräf Justus F. , Yang Zhiyu , Ravn Kirstine , Meisner Jonas , Thielemann Roman , Webel Henry , Smit Roelof A. J. , Niu Lili , Mann Matthias ,   FinnGen, Vilhjalmsson Bjarni , Neale Benjamin M. , Ganna Andrea , Hansen Torben , Loos Ruth J. F. , Rasmussen Simon 
Published: July 2024

AbstractAlthough thousands of genetic variants are linked to human traits and diseases, the underlying mechanisms influencing these traits remain largely unexplored. One important aspect is to understand how proteins are regulated by the genome by identifying protein quantitative trait loci (pQTLs). Beyond this, there is a need to understand the role of complex genetics effects such as dominance and epistasis that regulate plasma proteins and protein biomarkers. Therefore, we developed EIR-auto-GP, a deep learning-based approach, to identify such effects. Our results complement the additive genetic regulation identified in previous pQTLs screens by adding a nuanced view of the complex genetic regulation of plasma proteins. Applying this method to the UK Biobank proteomics cohort of 48,594 individuals, we identified 138 proteins that were regulated by non-linear effects, including non-linear covariates (123) as well as genetic dominance and epistasis (15). We uncovered a novel epistatic interaction between theABOandFUT3loci, and demonstrated dominance effects of theABOlocus on plasma levels of pathogen recognition receptors CD209 and CLEC4M. Furthermore, we replicated these findings and the methodology across Olink and mass spectrometry-based cohorts and concluded that large sample sizes are needed to discover more complex genetic effects. Our approach presents a systematic, large-scale attempt to identify complex effects of plasma protein levels and can be applied to study other tissues or molecular QTLs.
Single-gene transcripts for subclinical TB: an individual participant data meta-analysis
Authors: Greenan-Barrett James , Mendelsohn Simon C. , Scriba Thomas J. , Noursadeghi Mahdad , Gupta Rishi K. 
Published: July 2024

AbstractBackgroundTranslation of blood RNA signatures may be accelerated by identifying more parsimonious biomarkers. We tested the hypothesis that single-gene transcripts provide comparable accuracy for detection of subclinical TB to multi-gene signatures and benchmarked their clinical utility to interferon-y release assays (IGRAs).MethodsWe identified datasets where participants underwent RNA sampling and at least 12 months of follow-up for progression to TB. We performed a one-stage individual participant data meta-analysis to compare multi-gene signatures against single-gene transcripts to detect subclinical TB, defined as asymptomatic prevalent or incident TB (diagnosed ≥21 days from enrolment, irrespective of symptoms) over a 12-month interval. We performed decision curve analysis to evaluate the net benefit of using RNA biomarkers and IGRA, alone or in combination, compared to treating all or no individuals with preventative treatment.ResultsWe evaluated 80 single-genes and eight multi-gene signatures in a pooled analysis of four RNAseq and three qPCR datasets, comprising 6544 total samples and including 283 samples from 214 individuals with subclinical TB. Five single-gene transcripts were equivalent to the best-performing multi-gene signature over 12 months, with areas under the receiver operating characteristic curves ranging from 0.75-0.77, but none met the WHO minimum target product profile (TPP) for a TB progression test. IGRA demonstrated much lower specificity in higher burden settings, while sensitivity and specificity of RNA biomarkers were consistent across settings. In higher burden settings, RNA biomarkers had greater net benefit than IGRA, which offered little clinical utility over treating all with preventative therapy. In low burden settings, IGRA approximated the TPP and offered greater clinical utility than RNA biomarkers, but combining both tests provided the highest net benefit for services aiming to treat <50 people to prevent a single case.InterpretationSingle-gene transcripts are equivalent to multi-gene signatures for detection of subclinical TB, with consistent performance across settings. Single transcripts demonstrate potential clinical utility to stratify treatment, particularly when used in combination with IGRA in low burden settings.
Study Protocol: Development and Retrospective Validation of an Artificial Intelligence System for Diagnostic Assessment of Prostate Biopsies
Authors: Mulliqi Nita , Blilie Anders , Ji Xiaoyi , Szolnoky Kelvin , Olsson Henrik , Titus Matteo , Gonzalez Geraldine Martinez , Boman Sol Erika , Valkonen Masi , Gudlaugsson Einar , Kjosavik Svein R. , Asenjo José , Gambacorta Marcello , Libretti Paolo , Braun Marcin , Kordek Radzislaw , Łowicki Roman , Hotakainen Kristina , Väre Päivi , Pedersen Bodil Ginnerup , Sørensen Karina Dalsgaard , Ulhøi Benedicte Parm , Rantalainen Mattias , Ruusuvuori Pekka , Delahunt Brett , Samaratunga Hemamali , Tsuzuki Toyonori , Janssen Emilius A.M. , Egevad Lars , Kartasalo Kimmo , Eklund Martin 
Published: July 2024

AbstractHistopathological evaluation of prostate biopsies using the Gleason scoring system is critical for prostate cancer diagnosis and treatment selection. However, grading variability among pathologists can lead to inconsistent assessments, risking inappropriate treatment. Similar challenges complicate the assessment of other prognostic features like cribriform cancer morphology and perineural invasion. Many pathology departments are also facing an increasingly unsustainable workload due to rising prostate cancer incidence and a decreasing pathologist workforce coinciding with increasing requirements for more complex assessments and reporting.Digital pathology and artificial intelligence (AI) algorithms for analysing whole slide images (WSI) show promise in improving the accuracy and efficiency of histopathological assessments. Studies have demonstrated AI’s capability to diagnose and grade prostate cancer comparably to expert pathologists. However, external validations on diverse data sets have been limited and often show reduced performance. Historically, there have been no well-established guidelines for AI study designs and validation methods. Diagnostic assessments of AI systems often lack pre-registered protocols and rigorous external cohort sampling, essential for reliable evidence of their safety and accuracy.This study protocol covers the retrospective validation of an AI system for prostate biopsy assessment. The primary objective of the study is to develop a high-performing and robust AI model for diagnosis and Gleason scoring of prostate cancer in core needle biopsies, and at scale evaluate whether it can generalise to fully external data from independent patients, pathology laboratories, and digitalisation platforms. The secondary objectives cover AI performance in estimating cancer extent and in detecting cribriform prostate cancer and perineural invasion. This protocol outlines the steps for data collection, predefined partitioning of data cohorts for AI model training and validation, model development, and predetermined statistical analyses, ensuring systematic development and comprehensive validation of the system. The protocol adheres to TRIPOD+AI, PIECES, CLAIM, and other relevant best practices.
Publication trend, impact and performance in mental health during and post COVID-19 pandemic
Authors: Bahar Nurhidayah , Nor Rashid Fadilla ‘Atyka , Ahmad Nor Diana 
Published: July 2024

AbstractThis study presents a bibliometric analysis of publications on mental health during and post-COVID-19 pandemic in Malaysia. The dataset comprises 167 documents retrieved from the Scopus database covering the period from 2020 to 2022. Using the open-source tool Bibliometrix for science mapping analysis, we examined various aspects of these publications, including document type, number of articles, total citations, most relevant sources, source impact, most relevant authors, affiliations, globally cited documents, and a word cloud. Our findings reveal a significant and continuous growth in mental health-related publications since the onset of the pandemic in 2020, highlighting an intensified focus on this critical area. This surge in research emphasizes the heightened importance of understanding and addressing mental health issues exacerbated by the pandemic. By providing a comprehensive summary of the bibliometric data, this study enhances our understanding of publication trends and the evolving landscape of mental health research, offering valuable insights for researchers, policymakers, and practitioners aiming to respond to mental health challenges in the post-pandemic era.
The reliability and validity of a non-wearable indoor positioning system to assess mobility in older adults: A cross-sectional study
Authors: Rodrigues Isabel B. , Hewston Patricia , Adachi Jonathan , Borhan Sayem , Ioannidis George , Kouroukis Alexa , Leckie Carolyn , Lee Andrea , Rabinovich Alexander , Siva Parthipan , Swance Rachel , Tariq Suleman , Thabane Lehana , Papaioannou Alexandra 
Published: July 2024

ABSTRACTBackgroundChirp is a privacy-preserving radar sensor developed to continuously monitor older adults’ safety and mobility without the need for cameras or wearable devices. Our study purpose was to evaluate the inter-sensor reliability, intrasession test-retest reliability, and concurrent validity of Chirp in a clinical setting.MethodsWe recruited 35 community-dwelling older adults (mean age 75.5 (standard deviation: 6.6) years, 86% female). All participants lived alone in an urban city in southwestern Ontario and had access to a smart device with wireless internet. Data were collected with a 4-meter ProtoKinetics Zeno™ Walkway (pressure sensors) with the Chirp sensor (radar positioning) at the end of the walkway. Participants walked during normal and adaptive locomotion experimental conditions (walking-while-talking, obstacle, narrow walking, fast walking). Each of the experimental conditions was conducted twice in a randomized order, with fast walking trials performed last. For intra-session reliability testing, we conducted two blocks of walks within a participant session separated by approximately 30 minutes. Intraclass Correlation Coefficient(A,1)(ICC(A,1)) was used to assess the reliability and validity. Linear regression, adjusted for gender, was used to investigate the association between Chirp and cognition and health-related quality of life scores.ResultsThe Chirp inter-sensor reliability ICC(A,1)=0.999[95% Confidence Interval [CI]: 0.997 to 0.999] and intrasession test-retest reliability [ICC(A,1)=0.921, 95% CI: 0.725 to 0.969] were excellent across all experimental conditions. Chirp concurrent validity compared to the ProtoKinetics Zeno™ Walkway was excellent across experimental conditions [ICC(A,1)= 0.993, 95% CI: 0.985 to 0.997]. We found a weak association between Chirp and cognition scores using the Montreal Cognitive Assessment across experimental conditions (estimated β-value= 7.79, 95% CI: 2.79 to 12.80) and no association between the Chirp and health-related quality of life using the 12-item Short Form Survey across experimental conditions (estimated β-value=6.12, 95% CI: -7.12 to 19.36).ConclusionOur results demonstrate that Chirp is a reliable and valid measure to assess gait parameters in clinics among older adults.
Breaking free from references: a consensus-based approach for community profiling with long amplicon nanopore data
Authors: Stock Willem , Rousseau Coralie , Dierickx Glen , D’hondt Sofie , Martínez Luz Amadei , Dittami Simon M , van der Loos Luna , Clerck Olivier De 
Published: July 2024

AbstractThird-generation sequencing platforms, such as Oxford Nanopore Technology (ONT), have made it possible to characterise communities through the sequencing of long amplicons. Whilst this theoretically allows for an increased taxonomic resolution compared to short-read sequencing platforms such as Illumina, the high error rate remains problematic to accurately identify the community members present within a sample. Here we present and validate CONCOMPRA, a tool that allows the detection of closely related strains within a community by drafting and mapping to consensus sequences. We show that CONCOMPRA outperforms several other tools for profiling bacterial communities using full-length 16S rRNA gene sequencing. Since CONCOMPRA does not rely on a sequence database for profiling communities, it is applicable to systems and amplicons for which a reference framework is poorly developed. Our validation test shows that the amplification of long PCR products is likely to produce chimeric byproducts that inflate alpha diversity and skew community structure, stressing the importance of chimera detection. CONCOMPRA is available on GitHub (https://github.com/willem-stock/CONCOMPRA).Key points-We introduce a reference free tool for (long) amplicon Oxford Nanopore sequencing data-We show that it is capable of outperforming achieving a higher accuracy than preexisting tools-Chimera detection and removal is an essential step in the processing of long amplicon Oxford Nanopore sequencing data