bluuebunny/crossref_metadata_2025_split huggingface dataset:
Primary healthcare capacity in Northwest Ethiopia: Insights through the Primary health care progression model
Authors: Tsehay Chalie Tadie , Worku Nigusu , Dellie Endalkachew , Negash Wubshet Debebe , Aschalew Andualem Yalew , Debie Ayal , Haile Tsegaye G. , Fetene Samrawit Mihret , Kebede Adane , Atnafu Asmamaw 
Published: December 2024

AbstractBackgroundPrimary healthcare (PHC) systems are widely recognized as essential foundations for ensuring equitable access to quality medical care for all. Achieving the health-related Sustainable Development Goals (SDGs), including the sub-targets of universal health coverage by 2030 requires resilient PHC systems, supported by scientific evidences to inform better policy. However, there is a lack of evidence regarding the PHC system capacity at the operational level in Ethiopia. Therefore, we assessed the capacity of primary health care at the health facilities level in northwest Ethiopia.MethodsWe used a mixed-method assessment of the PHC capacity guided by the progression model, which includes governance, input, and population health and facility management domains with a total of 33 rubric-based (scaled from 1 to 4) measurement items. We included a total of three primary hospitals and five health centers from Northwest Ethiopia. Key informants interviews, facility observations including guideline and policy reviews and reports, discussion with key stakeholders, were our source of data. Data were independently collected by two groups of assessors (internal and external assessors) and a final score was determined by consensus through panel discussion. Finally, we summarized and synthesized the results over the three domains of PHC capacity assessment and the nine subdomains.ResultsAll the three domains scores were found to be low. We found that the scores were 1.5, 2.2, and 1.3 out of four points for the governance, input, and population health and facility management domains, respectively. While we found a better achievement on health management information system and civil registration and vital statistics, the local priority setting, facility management capability, innovation and learning, community engagement and social accountability measures had lowest capacity score.ConclusionsOur study highlighted that the governance and population health and facility management domains scored lower at the health facilities in central Gondar zone. Therefore, it is crucial to enhance these domains to strengthen PHC though a comprehensive approach, aiming to meet its targets and achieve UHC by 2030 or beyond.
Neurocognitive Outcome after Pediatric Traumatic Brain Injury: Patient Subgroups with Diverging Outcome
Authors: Kooper C.C. , Königs M. , Steenweg M.E. , Hunfeld M. , Scheurer C.D. , Schippers H.M. , Peper W. , Popma A. , van Woensel J.B.M. , Buis D.R. , Bruining H. , Engelen M. , Oosterlaan J. 
Published: December 2024

AbstractBackground and ObjectivesTraumatic brain injury (TBI) is the leading cause of acquired disability in children. Children with TBI are at risk of persistent deficits in neurocognitive functioning that affect daily life. However, neurocognitive outcomes are highly heterogenous and this heterogeneity is poorly understood. This study aims to investigate whether the heterogeneity in neurocognitive outcome can be reduced by distinguishing subgroups of children with distinct profiles of neurocognitive functioning, and to investigate whether these subgroups differ in demographic, premorbid and clinical characteristics.MethodsThis multicenter study included a consecutive cohort of children with mild to severe TBI and demographically matched neurologically healthy (NH) children. Seven neurocognitive domains were assessed six months post-TBI using computerized tests. The TBI and NH group were compared on the neurocognitive domains using t-tests. Results of the TBI group were subjected to cluster analysis to derive subgroups with distinct profiles of neurocognitive functioning. Resulting subgroups were compared on demographic, premorbid and clinical characteristics available at time of hospital visit.ResultsA total of 113 children with TBI and 113 NH children were included. The TBI group had lower performance than NH children on the neurocognitive domains Speed, Stability, Attention & Control, Verbal Working Memory and Visual Working Memory (.009≤ps≤.047, -.42≤ds≤-.29). Cluster analysis revealed four subgroups of patients with diverging neurocognitive outcome profiles. One subgroup was characterized by good outcome, whereas three subgroups had adverse outcome characterized by weak global outcome, weak visual-processing outcome or weak executive functioning outcome. The subgroups did not differ in clinical characteristics but did differ in demographic and premorbid characteristics. The weak global outcome subgroup had more premorbid behavioral problems, while the good outcome subgroup had higher socio-economic status than the other subgroups.DiscussionThis study indicates that children with mild to severe TBI exhibit neurocognitive deficits compared to matched controls at six months post TBI, among which subgroups of children with distinct neurocognitive outcome profiles exist. The neurocognitive outcome subgroups represent children with diverging severity and configuration of neurocognitive weaknesses. The subgroups with the diverging neurocognitive outcome profiles did not differ in clinical characteristics, highlighting the importance to consider other factors for the prognosis of neurocognitive outcome.
Comparing tangible retinal image characteristics with deep learning features reveals their complementarity for gene association and disease prediction
Authors: Beyeler Michael J , Trofimova Olga , Bontempi Dennis , Böttger Leah , Bors Sacha , Iuliani Ilaria , Vela Sofia Ortin , Presby David M , Bergmann Sven 
Published: December 2024

AbstractAdvances in computer-aided analyses, including deep learning (DL), are transforming medical imaging by enabling automated disease risk predictions and aiding clinical interpretation. However, DL’s outputs and latent variables (LVs) often lack interpretability, impeding clinical trust and biological insight. In this study, we evaluatedRETFound, a foundation model for retinal images, using a dataset annotated with clinically interpretable tangible image features (TIFs). Our findings revealed that individual LVs poorly represent complex TIFs but achieve higher accuracy when combined linearly. Fine-tuningRETFoundto predict TIFs, providing “deep TIFs” provided better, but far from perfect surrogates, highlighting the limitations of DL approaches to fully characterise retinal images. Yet, our genetic analyses showed that deep TIFs exhibit heritability comparable to or exceeding measured TIFs but highlighted non-genetic variability in LVs. While measured and deep TIFs, as well as LVs, showed overlapping genetic and disease associations, their complementarity enhances prediction models. Notably, deep TIFs excelled in ocular disease prediction, emphasising their potential to refine retinal diagnostics and bridge gaps in conventional assessments of vascular morphology.
Effect of acupuncture on anxious symptoms in healthcare students with generalized anxiety disorder: A protocol for a randomized controlled clinical trial
Authors: da Silva Cláudio Calixto Carlos , Matos Marcos André de , Batista Sandro Rogério Rodrigues 
Published: December 2024

AbstractBackgroundThe present study aimed to investigate the effect of acupuncture on generalized anxiety disorder (GAD) in healthcare students. On the basis of increasing prevalence of anxiety disorders in this population and the research gap regarding the use of acupuncture as a therapeutic intervention, this study aims to fill this gap and provide solid evidence on the effectiveness and safety of this practice.MethodsThe methodology will include a single-center, single-blinded, randomized, placebo-controlled clinical trial. A total of 87 patients diagnosed with generalized anxiety disorder will be enlisted and randomized to either manual acupuncture or sham acupuncture. Participants in both arms will undergo 30 minute-sessions once weekly until 10 sessions are completed over 4 months. The primary outcome measure will be assessed via 3 scales validated for Brazil: Generalized Anxiety Disorder Scale (GAD-7), The Beck Anxiety Inventory (BECK-A), The Penn State Worry Questionnaire (PSWQ) at baseline, 5 weeks and 10 weeks. All adverse events will be meticulously recorded and categorized by their time of onset and resolution, with appropriate clinical assessments provided for each patient.DiscussionAcupuncture is expected to significantly reduce anxiety symptoms in participants. The results of this study will contribute to the evidence on the effectiveness and safety of acupuncture in treating anxiety in healthcare students, providing data that may influence clinical practices and future treatment guidelines.Trial RegistrationThe Brazilian Registry of Clinical Trials:RBR-9stskc6. Registered 4 December 2024
THE DYNAMIC AFFECT RECOGNITION TEST: CONSTRUCTION AND VALIDATION IN NEURODEGENERATIVE SYNDROMES
Authors: Rankin Katherine P. , Ulugut Hulya , Radke Anneliese , Grossman Scott , Poorzand Pardis , Shany-Ur Tal , Kramer Joel H. , Possin Katherine L. , Sturm Virginia E. , Gorno Tempini Maria Luisa , Miller Bruce L. 
Published: December 2024

ABSTRACTLearning objectiveTo validate a novel video-based emotion identification measure in persons with neurodegeneration and show correspondence to emotion-relevant brain systemsBackgroundGiven advances in disease-modifying therapies for dementia, the dementia field needs objective, practical behavioral assessment tools for patient trial selection and monitoring. The Dynamic Affect Recognition Test (DART) was designed to remedy limitations of instruments typically used to measure emotion identification deficits in persons with dementia (PWD).MethodParticipants included 372 individuals, including 257 early stage PWD (Clinical Dementia Rating ≤1, Mini-Mental State Examination ≥20; 66 behavioral variant frontotemporal dementia [bvFTD], 27 semantic variant primary progressive aphasia [svPPA], 23 semantic bvFTD [sbvFTD], 33 non-fluent PPA [nfvPPA], 26 progressive supranuclear palsy [PSP], 28 corticobasal syndrome [CBS], 42 Alzheimer’s disease [AD], 12 logopenic variant PPA [lvPPA]), and 115 healthy controls (HC), watched 12 15-second videos of an actor expressing a basic emotion (happy, surprised, sad, angry, fearful, disgusted) via congruent facial/vocal/postural cues, with semantically neutral scripts. Participants selected the emotion from a randomized visual array. Voxel-based morphometry (VBM) analysis was performed to show brain structure correlates of DART, controlling for non-emotional naming ability (Boston Naming Test, BNT).ResultsDART performance was worse in PWD than older HC (p<0.001), with the lowest scores observed in the sbvFTD group. A DART 10 cut-off score differentiates PWD from HC with a 90% sensitivity and 49% specificity (AUC=82%). A DART 9/12 score yielded 93% sensitivity/67% specificity (AUC=87%) for discriminating social cognition disorders from HC, while a 7/12 score differentiated sbvFTD from HC with 100% sensitivity/93% specificity (AUC=97%). VBM showed poorer DART performance significantly predicts focal brain volume loss in right-sided emotion processing areas including insula, temporal pole, caudate, superior frontal gyrus and supplementary motor cortex (pFWE<0.05).ConclusionsThe DART is a brief, psychometrically robust video-based test of emotion reading (i) designed to be practically useful in realistic assessment settings, (ii) effectively reveals emotion identification impairments in PWD, (iii) shows specificity for identifying PWD exhibiting real-life SCDs (i.e. bvFTD, svPPA, sbvFTD), (iv) corresponds to the expected structural anatomy of emotion reading, and (v) is freely available to researchers and clinicians.
The association between enlarged perivascular spaces and muscle sympathetic nerve activity in normotensive and hypertensive humans
Authors: Rim Donggyu , Pham William , Fatouleh Rania , Hennessy Annemarie , Schlaich Markus , Henderson Luke A , Macefield Vaughan G 
Published: December 2024

AbstractBackgroundPerivascular spaces (PVS) are fluid-filled spaces that functions as channels for glymphatic clearance in the brain. Enlarged perivascular spaces (ePVS) have been associated with high blood pressure. Hypertension features abnormal increases in muscle sympathetic nerve activity (MSNA), which constricts blood vessels in the muscle vascular bed, but the underlying mechanisms for this increase are not understood. Moreover, the association between ePVS and the resting sympathetic outflow from the brain has not been studied in normotensive or hypertensive humans. Therefore, we assessed whether ePVS is associated with muscle sympathetic nerve activity (MSNA) in 25 hypertensive patients and 50 healthy normotensive adults.MethodsT1-weighted MRI anatomical brain images were analysed for ePVS using a deep learning-based segmentation algorithm – nnU-Net. ePVS in the white matter (WM), basal ganglia (BG), hippocampus (HP), and midbrain (MB) were analysed. Spontaneous bursts of MSNA were recorded from the right common peroneal nerve via a tungsten microelectrode immediately before the MRI scan.ResultsSignificant associations were found between ePVS and MSNA in the WM, BG, and HP in both the normotensive and hypertensive groups after adjusting for confounding factors (age, sex, mean blood pressure, total intracranial volume). However, the association between MSNA and MB ePVS was only observed in the hypertensive group.ConclusionThis finding provides insights into the pathophysiology of elevated sympathetic drive in hypertension.What is new?• Enlarged perivascular spaces (ePVS) are associated with muscle sympathetic nerve activity (MSNA) in normotensive and hypertensive humans.• Hypertensives and normotensives display differences in the association between the midbrain ePVS and MSNA.What are the clinical implications?• Insights into the centrally driven pathophysiological mechanism of elevated sympathetic nerve outflow in hypertension has been revealed.• ePVS may be used as an imaging biomarker for individuals with high sympathetic nerve activity, allowing identification of risk individuals that require microneurographic assessment of sympathetic nerve activity
The epidemiology and clinical features of HIV andTrypanosoma cruzi(Chagas disease) co-infection: A systematic review and individual patient data analysis
Authors: Elkheir Natalie , Carter Jessica , Dominic Catherine , Lok Pat , Fisayo Temitope , Michelen Melina , De Barros Barbara , Goldsmith Jaimie Wilson , Butler Michael , Price Amy , Mehotra Anushka , Nabarro Laura , Ahmed Nadia , Chiodini Peter , Moore David A.J. 
Published: December 2024

AbstractBackgroundNarrative descriptions of HIV andTrypanosoma cruzi,the causative agent of Chagas disease, co-infection exist in the literature but the breadth and depth of the data underlying these descriptions has not been previously thoroughly scrutinised and reactivation is poorly understood. The aim of this systematic review was to identify, synthesise and analyse the published literature on the epidemiology and clinical features ofT. cruziand HIV co-infection.MethodsA systematic review of published literature on HIV andT. cruzico-infection was conducted. Six international databases were searched: Medline, Embase, Global Health, Global Index Medicus, Web of Science and Scopus. Articles reporting on HIV andTrypanosoma cruzico-infection, as defined by the authors, with no restrictions on study type, language or date of publication or reporting were included.Results152 articles (62% case reports or series) were included which reported on 1,603 individuals with co-infection and 225 with presumed reactivation. Reported prevalence of co-infection varied greatly by region and setting of screening, from 0.1 to 1% in unselected populations, and was particularly high when screening inpatients known to have HIV forT. cruziinfection (26-48%). 83% of reactivations were reported in individuals with CD4<200 cells/mm3. CNS reactivation, typically presenting with meningoencephalitis and/or cerebral lesions, accounted for 68% of all published cases of reactivation. Myocarditis (accounting for 9% published reactivation cases) was less well characterised. Mortality of all reactivation cases was 59% (77% in those with CNS reactivation).ConclusionT. cruzireactivation mainly affects those with untreated HIV and lower CD4 counts. CNS reactivation is the most common clinical picture and confers high mortality. Prompt recognition of reactivation and immediate initiation of trypanocidal therapy (with benznidazole or nifurtimox) is recommended. Increased education and better awareness of the risks of co-infection are needed, as is systematic screening of individuals at-risk.
Enhancing Semantic Interoperability in Precision Medicine: Converting OMOP CDM to Beacon v2 in the Spanish IMPaCT-Data Project
Authors: Rueda Manuel , Ramírez-Anguita Juan Manuel , López-Sánchez Victoria , Aguiló-Castillo Sergi , Gas López Maria Eugenia , Labarga Alberto , Mayer Miguel-Ángel , Ripoll Esteve Javier , Gut Ivo G. 
Published: December 2024

AbstractObjectiveTo introduce novel methods to convert OMOP CDM data into GA4GH Beacon v2 format, enhancing semantic interoperability within Spain’s IMPaCT-Data program for personalized medicine.Materials and MethodsWe utilized a file-based approach with the Convert-Pheno tool to transform OMOP CDM exports into Beacon v2 format. Additionally, we developed a direct connection from PostgreSQL OMOP CDM to the Beacon v2 API, enabling real-time data access without intermediary text files.ResultsWe successfully converted OMOP CDM datasets from three research centers (CNAG, IIS La Fe, and HMar) to Beacon v2 format with nearly 100% data completeness. The direct connection approach improved data freshness and adaptability for dynamic environments.Discussion and ConclusionThis study introduces two methodologies for integrating OMOP CDM data with Beacon v2, offering performance optimization or real-time access. These methodologies can be adopted by other centers to enhance interoperability and collaboration in health data sharing.
Refining LLMs Outputs with Iterative Consensus Ensemble (ICE)
Authors: Omar Mahmud , Glicksberg Benjamin S , Nadkarni Girish N , Klang Eyal 
Published: December 2024

AbstractLarge language models (LLMs) show promising accuracy on challenging tasks, including medical question answering. Yet, direct gains from model upgrades can plateau, and reliability issues persist. We introduce Iterative Consensus Ensemble (ICE), a proof-of-concept framework that refines answers through iterative reasoning and feedback among multiple LLMs. This ensemble method encourages diverse models to scrutinize each other’s outputs, converging on a consensus solution. We tested ICE on four different datasets. These included over 4,000 multiple-choice questions drawn from a newly curated primary care exam set, established medical benchmarks, and a PhD-level reasoning dataset. Compared to initial single-model attempts, ICE improved final overall accuracy by up to 27%. It reached accuracies 81% in medical subsets and 72% in multi-domain tasks from initial scores of about 72% and 60%, respectively. In a particularly challenging PhD-level reasoning benchmark (GPQA-diamond), ICE raised performance from 46.9% initially to 68.2% at the final consensus, a relative gain exceeding 45%. On a specialized family medicine dataset, ICE’s results were statistically indistinguishable from those of a complex reasoning model (O1-preview), despite O1’s higher cost and computational demands. Additional analyses showed that ICE’s iterative consensus remained effective under different prompting styles. Our proposed framework leverages standard LLMs and repeated prompting, requiring no specialized reward models or intricate token-level fusion. These findings show that iterative collaboration can transform LLM ensembles into more reliable, cost-efficient solvers, advancing performance in medical and general reasoning domains. Future refinements may integrate chain-of-thought steps or specialist models, extending this approach to more complex challenges as LLMs and benchmarks continue to evolve.
Construction and Analysis of Risk Model of Postoperative Stone Recurrence in Patients with Cholelithiasis: A Protocol-Based KAP Questionnaire Approach
Authors: Xie Hui , Hao Fatao , Meng Yong , Du Lin , Wang Xiangyu 
Published: December 2024

AbstractBackgroundPatients who undertake endoscopic stone removal had a chance to have CBDS recurrence, which can lead to many severe complication. Many risk factors cause the recurrence of CBDS, but many factors cannot be controlled by clinical intervention. As for the patients in daily life, healthy lifestyle is important to prevent the recurrence of CBDS. The questionnaire of KAP can collect the real information about patients and guide the clinical work.Methods100 CBDS recurrence patients after surgery in our hospital were enrolled. A pair of self-designed questionnaires on KAP were used to collect data and assess the KAP towards CBDS recurrence.ResultsThe mean score for KAP of CBDS recurrence patients was 30.29±2.87, 26.42±±3.53 and 27.23±±3.48. Pearson correlation analysis showed that knowledge aspect score and attitude score were significantly positively correlated with practice score (r=0.384, 0.309; P<0.001, 0.002). Further Pearson regression analysis revealed that the knowledge and attitude, education, Type 2 diabetes, were significantly associated with the practice of patients.ConclusionThe CBDS recurrence patients had a good command of knowledge, but had negative attitude and poor performance in practice.
“The Metagenomics Days”: a simplified workshop on amplicon sequencing analysis with open cloud bioinformatics for eDNA and Microbiomes
Authors: Belaouni Hadj Ahmed , Stevenson Michael , Rosell Stewart , McClure Andrew 
Published: December 2024

AbstractThe “Metagenomics Days” event was organized to enhance understanding of metagenomics and microbiome analysis among participants new to the field. This paper presents an evaluation of the course’s impact through a comprehensive survey administered before and after the event. We assessed participants’ prior knowledge, experience with bioinformatics tools, and confidence levels regarding key concepts in microbiome analysis. Word clouds generated from open-ended survey responses provided additional insights into participants’ interests and pre-course familiarity with metagenomic tools and concepts. Surveys results showed substantial improvements in participants’ confidence, particularly in building bioinformatics pipelines (+41%), understanding diversity metrics (+44.1%), and applying microbiome analysis concepts (+34.8%). Similarly, understanding of core topics like cloud computing (+28%), bioinformatics workflows (+34%), and 16S rRNA gene variable regions (+27.5%) increased significantly. The course’s impact on knowledge retention was also evaluated, with participants achieving an average of 64.87% correct responses, with 25.76% unsure answers and only 9.35% incorrect responses, highlighting the effectiveness of the course in enhancing comprehension. Overall, the survey results indicate a significant increase in participants’ confidence and knowledge acquisition, particularly in the areas of cloud computing, diversity metrics, and bioinformatics pipelines. These improvements in confidence and knowledge acquisition underscore the effectiveness of the course in bridging knowledge gaps and preparing participants for future research in the complex and rapidly evolving fields of metagenomics and microbiome analysis.