bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting intentions towards long-term antidepressant use in the management of people with depression in primary care: A longitudinal survey study
Authors: Dewar-Haggart Rachel , Muller Ingrid , Bishop Felicity , Geraghty Adam W A , Stuart Beth , Kendrick Tony 
Published: December 2024

AbstractBackgroundOver the last two decades, antidepressant prescribing in the UK has increased considerably, due to an increased number of people staying on antidepressants for longer. Even when treatment is no longer clinically indicated, qualitative research suggests many people continue due to a fear of depressive relapse or antidepressant withdrawal symptoms. The quantitative effects of peoples’ beliefs and attitudes towards long-term antidepressant use remain relatively unexplored.ObjectivesTo determine the extent to which beliefs and attitudes towards antidepressant treatment predict intentions to stop or continue long-term use; and whether intentions translate into actual discontinuation.MethodsA questionnaire survey formed the main component of an embedded mixed-methods study. Twenty general practices posted questionnaires to adults aged over 18 receiving continuous antidepressant prescriptions for over two years. Outcomes and predictors were determined using an extended model of the Theory of Planned Behaviour, conducting exploratory descriptive and regression analyses. The primary outcome was participants’ intentions to discontinue antidepressants. The secondary outcome of behaviour change was determined by any change in antidepressant dosage at six months.Results277 people were surveyed from 20 practices, with 10 years median antidepressant duration. Mean questionnaire scores for intention and subjective norms towards starting to come off antidepressants were low, and 85% of participants declared that continuing their antidepressant was necessary. Prescribing outcomes retrieved from 175 participants’ medical records six months after they completed the survey found 86% had not changed their antidepressant, 9% reduced the dose, only 1% discontinued their antidepressant, and 4% increased the dose. More favourable attitudes towards stopping, and normative beliefs about depression, were the strongest predictors of intentions to stop long-term antidepressant treatment.ConclusionGiven few intentions to stop taking antidepressants, patients should be made more aware of the importance of ongoing antidepressant monitoring and review from their primary care practitioners. This would promote discussion to support an attitudinal change and initiation of antidepressant tapering where appropriate.
Combining participatory mapping and route optimization algorithms to inform the delivery of community health interventions at the last mile
Authors: Randriamihaja Mauricianot , Ihantamalala Felana Angella , Rafenoarimalala Feno H. , Finnegan Karen E , Rakotonirina Luc , Razafinjato Benedicte , Bonds Matthew H. , Evans Michelle V , Garchitorena Andres 
Published: December 2024

ABSTRACTCommunity health programs are gaining relevance within national health systems and becoming inherently more complex. To ensure that community health programs lead to equitable geographic access to care, the WHO recommends adapting the target population and workload of community health workers (CHWs) according to the local geographic context and population size of the communities they serve. Geographic optimization could be particularly beneficial for those activities that require CHWs to visit households door-to-door for last mile delivery of care. The goal of this study was to demonstrate the feasibility and utility of geographic optimization in the context of community health programs in rural areas of the developing world. We developed a decision-making tool based on participatory mapping and route optimization algorithms in order to inform the micro-planning and implementation of two kinds of community health interventions requiring door-to-door delivery: mass distribution campaigns and proactive community case management (proCCM) programs. We applied the Vehicle Routing Problem with Time Windows (VRPTW) algorithm to optimize the on-foot routes that CHWs take to visit households in their catchment, using a geographic dataset obtained from participatory mapping onOpenStreetMapcomprising over 100,000 buildings and 20,000 km of footpaths in the rural district of Ifanadiana, Madagascar. We found that personnel-day requirements ranged from less than 15 to over 60 per CHW catchment for mass distribution campaigns, and from less than 5 to over 20 for proCCM programs, assuming 1 visit per month. To facilitate local use of VRPTW algorithms by operational teams, we developed an “e-health” platform to visualize resource requirements, CHW optimal schedules and itineraries according to customizable intervention designs and hypotheses. Further development and scale-up of these tools could help optimize community health programs and other last mile delivery activities, in line with WHO recommendations, linking a new era of big data analytics with the most basic forms of frontline care in resource poor areas.
Effect of and Interventions in Prevention and Management of Maternal Anemia in the Advent of COVID-19
Authors: Muthuka John K. , Fondo Diana , Wambura Francis , Mativo Japheth , Kelly Oluoch J. , Nabaweesi Rosemary 
Published: December 2024

AbstractBackgroundThere were many unknowns for pregnant women during the COVID-19 pandemic. Most of these could have been silent however lethal and anemic conditions could escalate the worsening of pregnancy outcomes. Existing evidence indicate that, array of factors is associated with the ability of compromising maternal anemia, some directly and others indirectly.ObjectiveThis review aimed at ascertaining the pooled effect of several anemia interventions. Specifically, the aim of this study was to establish if pregnancy status is associated with COVID-19 severity characterized by a cytokine storm.MethodsWe searched the Google Scholar, PubMed, Scopus, Web of Science, and Embase databases to studies suitable for inclusion in this meta-analysis. Studies examining women of reproductive age on any maternal anemia intervention were included. The risk of bias was assessed using the Cochrane risk of bias tool. Review Manager 5.4.1 was used to calculate rate ratios (RRs) with 95% CIs, which were depicted using forest plots. Quantitative variables were summarized in total numbers and percentages. The effect on prevention, control, management and or treatment of anemia was calculated and compared between the intervention and the comparator arms. Heterogeneity was evaluated with the Cochran Q statistic and Higgins test.ResultsA total of 11 articles including data for 6,129 were included. With sensitivity analysis, the interventions had a utility of 39% on maternal anemia prevention and management (random effects model RR 0.61, 95% CI 0.43, 0.87;P= 0.006) (χ26=286.98, P<.00001; I2=97%). All the interventions against maternal anemia showed an effect of 17% (fixed-effect model RR 0.83, 95% CI 0.79-0.88; P<.00001) (χ24=2.93, P=0.57; I2=0%). Education to pregnant women showed a 28% effect (RR 0.72 95% CI 0.58, 0.89), medicinal administration 19% (RR 0.81 95% CI 0.73, 0.90), iron supplementation 17% (RR 0.83 95% CI 0.75, 0.92) and I.V Ferric Carboxy-maltose 15% (RR 0.85 95% CI 0.74, 0.97) (I2= 0%). Interventions in African region had a higher (16%) and significant effect compared to other regions (fixed-effects model RR 0.84, 95% CI 0.79-0.89; P<.001) (χ25=176.53, P<.00001; I2=97%). Multiple center studies had a significant predictive effect (16%) compared to single center studies (fixed-effects model RR 0.84, 95% CI 0.79-0.89; P<.00001)(χ25=176.53, P<.00001; I2=97%). The year 2020 recorded the highest effect of maternal anemia interventions at 28% (random-effects model RR 0.72, 95% CI 0.67-0.78; P<.00001) (χ23=167.34, P<.00001; I2=98%)ConclusionIn the advent of COVID-19, maternal anemia interventions were compromised demonstrated by a low effectiveness trend from the year 2020 to the year 2022. During this period, even the most effective and recommended interventions against maternal anemia were somehow affected.
Trajectories of menstrual symptoms and blood pressure in midlife: A prospective cohort study on Australian women
Authors: Mishra Gita D , Jin Chuyao , Chan Hsiu-Wen , Doust Jenny 
Published: December 2024

AbstractAimTo investigate the associations between the trajectories of menstrual symptoms over 18 years and blood pressure in midlife using longitudinal data.MethodsUsing data from the Menarche-to-PreMenopause (M-PreM) study, sampled from the Australian Longitudinal Study on Women’s Health, 494 participants were followed from their early 20s to mid-40s. Distinct trajectories of heavy menstrual bleeding, irregular periods, and severe period pain were identified by group-based trajectory modelling. The associations between menstrual symptom trajectories and blood pressure were examined by linear regression models.ResultsWe identified three distinct heavy menstrual bleeding trajectories and two for irregular periods and severe period pain. After accounting for blood pressure monitors and socio-demographic factors, women in the chronic heavy menstrual bleeding group and late onset heavy menstrual bleeding group exhibited higher systolic (SBP) and diastolic (DBP) blood pressure compared to the normative group. The late onset irregular periods group also had higher DBP than the normative group. When we further adjusted for lifestyle factors, body mass index, and waist-to-hip ratio, the associations were attenuated (chronic heavy bleeding: SBP [B=3.0; 95% CI: −1.1, 7.0] and DBP [B=2.5; 95% CI: −0.3, 5.2]; late onset heavy menstrual bleeding: SBP [B=3.4; 95% CI: 0.3, 6.5] and DBP [B=3.1; 95% CI: 1.0, 5.2]). We found no associations between severe period pain and blood pressure.ConclusionsThe trajectories of heavy menstrual bleeding and irregular periods during the reproductive span were associated with blood pressure in midlife. This suggests that tracking menstrual symptoms in women could help predict their midlife blood pressure.
Generalizable Clinical Note Section Identification with Large Language Models
Authors: Zhou Weipeng , Miller Timothy A. 
Published: December 2024

AbstractObjectiveClinical note section identification helps locate relevant information and could be beneficial for downstream tasks such as named entity recognition. But the traditional supervised methods suffer from transferability issues. This study proposes a new framework for using large language models for section identification to overcome the limitations.Materials and methodsWe framed section identification as question-answering and provided the section definitions in free-text. We evaluated multiple LLMs off-the-shelf without any training. We also fine- tune our LLMs to investigate how the size and the specificity of the fine-tuning dataset impacts model performance.ResultsGPT4 achieved the highest F1 score of 0.77. The best open-source model (Tulu2-70b) achieved 0.64 and is on par with GPT3.5 (ChatGPT). GPT4 is also found to obtain F1 scores greater than 0.9 for 9 out of the 27 (33%) section types and greater than 0.8 for 15 out of 27 (56%) section types. For our fine-tuned models, we found they plateaued with an increasing size of the general domain dataset. We also found that adding a reasonable amount of section identification examples is beneficial.DiscussionThese results indicate that GPT4 is nearly production-ready for section identification, and seemingly contains both knowledge of note structure and the ability to follow complex instructions, and the best current open-source LLM is catching up.ConclusionOur study shows that LLMs are promising for generalizable clinical note section identification. They have the potential to be further improved by adding section identification examples to the fine-tuning dataset.
The burden of patient healthcare activity in the first year of peritoneal dialysis
Authors: Crowe Kirsty , Murray Eleanor C , MacLeod Joan , Traynor Jamie P , Thomson Peter C 
Published: December 2024

AbstractBackgroundThe healthcare-related burden associated with kidney replacement therapy (KRT) has not been characterised as comprehensively in peritoneal dialysis (PD) as in haemodialysis (HD) or kidney transplantation. This study aimed to capture the nature and extent of healthcare activity in the first year of PD therapy.MethodsRetrospective analysis was undertaken on consecutive incident adult patients on PD between 1stJanuary 2015-31stDecember 2019 in the Glasgow Renal and Transplant Unit. Healthcare-related activity was captured up to the first 365 days post-commencement of PD. Data was collected on renal service contact and activity relating to dialysis access, radiological investigation, and relevant infection episodes. Carbon mapping of healthcare activity was estimated using postcode data and previously published carbon footprint estimations.ResultsPD was initiated in 122 patients over the study period. Sixty-three patients (52%) transitioned to another KRT within 365 days of commencing PD. Patients had a mean 36.4 days (SD 22.7) of face-to-face contact days with renal services. This included a mean of 1.5 (SD 1.6) hospital admissions, with a median 5 (IQR 10.8) in-patient days. The estimated carbon footprint was 581kg CO2e/patient over the incident year. This included a median 207kg CO2e/patient for inpatient days and 26kg CO2e/patient for treatment of infections.ConclusionsThere is a significant burden of kidney-associated healthcare on patients commencing their first year of PD despite it being a home-based therapy. Estimates of carbon footprint indicate hotspots include patient travel and hospital admissions, and episodes of peritonitis; a full life cycle analysis is merited.Key Learning PointsWhat was knownThe characterisation of healthcare-related activity to be expected with peritoneal dialysis therapy is not as comprehensive as that for haemodialysis and kidney transplantation.Patient-centred realistic medicine requires knowledge of the patient journey and the cumulative impact of healthcare activity interactions.Healthcare activity burden mapping is required to determine the necessary carbon emission reductions for reducing the contribution to climate change.This study addsAn illustration of the associated health-care activity burden on patients commencing peritoneal dialysis.An indication of the carbon footprint associated with peritoneal dialysis health-care activity in the first year of therapy.Potential impactInformative for service providers of peritoneal dialysis in anticipating care requirements and planning carbon reduction strategies.Data can help inform patient decision making when receiving education of kidney replacement therapies.
AGO2 protein: A Key Enzyme in the miRNA Pathway as a Diagnostic and Prognostic Biomarker in Adrenocortical Carcinoma
Authors: Hashmi Anila , Hutvagner Gyorgy , Sidhu Stan , Papachristos Alexander 
Published: December 2024

AbstractContextAdrenocortical carcinoma (ACC) is a rare and aggressive malignancy. Current treatment algorithms are associated with diagnostic limitations, high recurrence rates and poor prognosis. Identifying specific biomarkers that facilitate accurate diagnosis and provide prognostic insights could significantly enhance the patient outcomes in ACC.ObjectiveTo investigate whether microRNA machinery, specifically argonaute 2 (AGO2), a key enzyme in the miRNA pathway, has the potential to be a diagnostic and prognostic biomarker for adrenocortical carcinoma (ACC).DesignThis study analyzed mRNA expression of genes involved in the miRNA biogenesis pathway using RNASeq data from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) dataset, followed by target protein quantification in tissue samples using commercial ELISA kits.SettingPublicly available mRNASeq datasets (TCGA-GTEX) and frozen tissue samples from the tumour bank of the Kolling Institute of Medical Research.ParticipantsWe analyzed data for 79 ACC and 190 normal adrenal cortex (NAC) samples from the TCGA and GTEx datasets, as well as for 31 other cancer types from the TCGA. We then performed protein quantification in 15 NAC, 15 benign adrenal adenoma (AA), and 15 ACC tissue homogenates.Intervention(s)None.Main Outcome MeasuresAGO2 mRNA and protein expression in ACC and its prognostic correlation.ResultsAGO2 was significantly overexpressed in ACC, compared to NAC and AA (p<0.001). Kaplan– Meier survival analysis revealed that higher expression of AGO2 was associated with significantly worse overall survival in ACC (HR 7.07, p<0.001). Among all 32 cancer types in TCGA, AGO2’s prognostic utility was most significant in ACC.ConclusionsAGO2 holds potential as a diagnostic and distinct prognostic biomarker in ACC.
Electrode positioning errors reduce current dose for focal tDCS set-ups: Evidence from individualized electric field mapping
Authors: Niemann Filip , Riemann Steffen , Hubert Ann-Kathrin , Antonenko Daria , Thielscher Axel , Martin Andrew K. , Unger Nina , Flöel Agnes , Meinzer Marcus 
Published: December 2024

AbstractObjectiveElectrode positioning errors contribute to variability of transcranial direct current stimulation (tDCS) effects. We investigated the impact of electrode positioning errors on current flow for tDCS set-ups with different focality.MethodsDeviations from planned electrode positions were determined using data acquired in an experimental study (N=240 datasets) that administered conventional and focal tDCS during magnetic resonance imaging (MRI). Comparison of individualized electric field modeling for planned and empirically derived “actual” electrode positions was conducted to quantify the impact of positioning errors on the electric field dose in target regions for tDCS.ResultsPlanned electrode positions resulted in higher current dose in the target regions for focal compared to conventional montages (7-12%). Deviations from planned positions significantly reduced current flow in the target regions, selectively for focal set-ups (26-30%). Dose reductions were significantly larger for focal compared to conventional set-ups (29-43%).ConclusionsPrecise positioning is crucial when using focal tDCS set-ups to avoid significant reductions of current dose in the intended target regions.SignificanceOur results highlight the urgent need to routinely implement methods for improving electrode positioning, minimization of electrode drift, verification of electrode positions before and/or after tDCS and also to consider positioning errors when investigating dose-response relationships, especially for focal set-ups.
Long-read sequencing of an advanced cancer cohort resolves rearrangements, unravels haplotypes, and reveals methylation landscapes
Authors: O’Neill Kieran , Pleasance Erin , Fan Jeremy , Akbari Vahid , Chang Glenn , Dixon Katherine , Csizmok Veronika , MacLennan Signe , Porter Vanessa , Galbraith Andrew , Grisdale Cameron J. , Culibrk Luka , Dupuis John H. , Corbett Richard , Hopkins James , Bowlby Reanne , Pandoh Pawan , Smailus Duane E. , Cheng Dean , Wong Tina , Frey Connor , Shen Yaoqing , Paulin Luis F. , Sedlazeck Fritz J. , Nelson Jessica M.T. , Chuah Eric , Mungall Karen L. , Moore Richard A. , Coope Robin , Mungall Andrew J. , McConechy Melissa K. , Williamson Laura M. , Schrader Kasmintan A. , Yip Stephen , Marra Marco A. , Laskin Janessa , Jones Steven J.M. 
Published: December 2024

AbstractThe Long-read POG dataset comprises a cohort of 189 patient tumours and 41 matched normal samples sequenced using the Oxford Nanopore Technologies PromethION platform. This dataset from the Personalized Oncogenomics (POG) program and the Marathon of Hope Cancer Centres Network includes accompanying DNA and RNA short-read sequence data, analytics, and clinical information. We show the potential of long-read sequencing for resolving complex cancer-related structural variants, viral integrations, and extrachromosomal circular DNA. Long-range phasing of variants facilitates the discovery of allelically differentially methylated regions (aDMRs) and allele-specific expression, including recurrent aDMRs in the cancer genesRETandCDKN2A. Germline promoter methylation inMLH1can be directly observed in Lynch syndrome. Promoter methylation inBRCA1andRAD51Cis a likely driver behind patterns of homologous recombination deficiency where no driver mutation was found. This dataset demonstrates applications for long-read sequencing in precision medicine, and is available as a resource for developing analytical approaches using this technology.
CHIP disrupts monocyte-endothelial interactions across multiple tissues to promote vascular inflammation in humans
Authors: Parker Alyssa C. , Heimlich J. Brett , Ahmad Ayesha , Bailin Samuel S. , Van Amburg Joseph C. , Vlasschaert Caitlyn , Koethe John R. , Wanjalla Celestine N. , Bick Alexander G. 
Published: December 2024

AbstractBackgroundClonal hematopoiesis of indeterminate potential (CHIP) occurs when hematopoietic stem cells acquire mutations that confer a proliferative advantage. CHIP is associated with increased risk of multiple vascular diseases. Mouse models have identified CHIP monocytes as highly proinflammatory. Here we seek to build on these earlier studies by characterizing adipose tissue macrophages and vascular cells in patients with CHIP.MethodsWe performed single-cell RNA sequencing on paired peripheral blood mononuclear cells and subcutaneous adipose tissue from 6 CHIP patients and 6 matched controls. We analyzed cell type specific gene expression profiles and intercellular interactions.ResultsWe found that macrophages had an exaggerated proinflammatory profile compared to circulating monocytes. We also found increased interaction between circulating CD14+ monocytes and endothelial cells. Specifically, cells from patients with CHIP showed enhanced signaling related to leukocyte transendothelial migration. These differences were tissue specific. We recapitulated monocyte-endothelial cell interactions in single cell RNA sequencing data from a mouse model of CHIP.ConclusionsMonocytes from patients with CHIP have increased endothelial interaction compared to controls and macrophages from patients with CHIP are highly proinflammatory. Alterations in the monocyte-endothelial interaction in CHIP likely contribute to cardiovascular disease risk.Graphical abstract