Journal of Occupational Health

IntroductionMusculoskeletal injuries (MSKIs) are ubiquitous in the U.S. military, especially among high-performing service members such as Marines. Given that female service members only started to be assigned to ground combat roles since December 2015, evaluation of sex on MSKI risk in ground combat occupations has not been possible until there was an ample population to study. The purpose of this population-level epidemiological study was to assess (1) if female sex was a salient risk factor for MSKI in Marines serving in different military occupations, including combat arms, and (2) the effects of integration period on MSKI risk among female Marines. Materials and MethodsA population-based epidemiological retrospective cohort study of all U.S. Marines was performed assessing female sex, occupation, and integration period on the prevalence of MSKI from 2011 through 2020. The Military Health System Data Repository was utilized to identify initial healthcare encounters for diagnosed ankle-foot, knee, lumbopelvic-hip, thoracocostal, cervicothoracic, shoulder, elbow, or wrist-hand complex injuries. Prevalence was calculated for female and male Marines in each occupational category (combat, combat support, aviators, aviation support, services) during the pre-integration (2011-2015) and post-integration (2016-2020) periods. ResultsDuring the pre-integration period, 520/1,000 female Marines (n=13,985) and 299/1,000 male Marines (n=142,158) incurred MSKIs. In the post-integration period, the prevalence increased to 565/1,000 female Marines (n=17,608) and 348/1,000 male Marines (n=161,429). In the multivariable evaluation of sex, occupation, integration period, and the interaction of sex and occupation on combined MSKIs, only female sex was a significant factor for injury (prevalence ratio [PR]=1.99), with service in ground combat and aviation occupations identified as protective factors when compared with services occupations (PR=0.69). When these same factors were evaluated for specific MSKI outcomes, female sex remained a robust factor in all lower quarter (PR=1.75-2.63) and upper quarter (PR=1.38-2.36) injuries except for shoulder injuries. Service in ground combat and aviation occupations was protective for all lower quarter injuries (PR=0.46-0.71). In the upper quarter, ground combat was protective for all injuries except for elbow injuries (PR=0.67-0.77). Serving as an aviator was a risk factor for cervicothoracic (PR=1.57) and thoracocostal (PR=1.22) injuries and a protective factor for shoulder (PR = 0.73) and wrist-hand (PR = 0.46) injuries. Adjusted risk for lumbopelvic-hip (PR=1.13), ankle-foot (PR=1.53), cervicothoracic (PR=1.19), thoracocostal (PR=1.14), and elbow (PR=1.48) injuries significantly increased during the post-integration period. There was a significant sex-by-period interaction for shoulder injuries alone, with female sex in the post-integration epoch found to be salient (PR=1.26). ConclusionsFemale sex was a salient factor for MSKI, with service in ground combat and aviation occupations identified as protective factors when compared with services occupations. In the evaluation of specific MSKIs, female sex remained a robust and significant factor in all lower quarter injuries and upper quarter injuries except for shoulder injuries. There was only a significant sex-by-period interaction for shoulder conditions, with an increased risk of these injuries in female Marines in the post-integration period.

Compassion fatigue is a well-documented hazard among healthcare and veterinary professionals, yet the psychological toll on informal caregivers of feral cat colonies, likely numbering several tens of thousands in Portugal, remains largely unexplored. This cross-sectional study examines internal and external factors associated with the secondary traumatic stress component of compassion fatigue among 172 informal caregivers in Portugal. Secondary traumatic stress refers to work-related secondary exposure to individuals who have experienced extremely stressful or traumatic events. Structured telephone interviews assessed sociodemographics, colony management, compassion satisfaction, resilience, spiritual well-being, and perceived social support. Univariate and multivariable linear regression identified predictors of compassion fatigue. Results indicate that 47% of participants experienced moderate compassion fatigue, and 10% reported high levels. Multivariable analysis revealed that caring for large colonies (more than 25 cats) and being unemployed were significantly associated with higher fatigue. Conversely, older age, higher perceived family support, and the resilience dimension of serenity served as protective factors. Interestingly, finding meaning in life was positively correlated with fatigue, suggesting that caregivers who perceive their role as central to their life purpose may become more emotionally invested, increasing vulnerability to distress when unable to help animals. Official colony registration and formal institutional support did not significantly alleviate fatigue. These findings highlight that institutional support alone is insufficient to mitigate fatigue among informal caregivers, who experience significant distress driven by both practical burdens and profound emotional involvement. The most frequently reported concern among caregivers was the inability to cover the costs of feeding and veterinary care for the cats. Interventions must address both external needs (e.g., support to cover veterinary and feeding expenses for the cats) and internal coping mechanisms. Implementing psychosocial support alongside trap-neuter-return programs may also improve caregiver well-being and foster sustainable urban feral cat management. This underscores a One Health perspective, demonstrating that animal health is closely interconnected with human well-being and environmental health.

Food costs are more significantly impacted by climate change as countries grow. It is well known that climate change has an impact on the productivity of most agricultural goods, but it is unclear how specifically it will affect food costs. The present research explores how the North Atlantic Oscillation (NAO) index, a widely used climate indicator, affects food prices around the world. This is achieved by applying a robust bivariate Hurst exponent (robust bHe). The research creates a color map of this coefficient using a window-sliding technique over various intervals of time, displaying an illustration that changes overtime. Additionally, the NAO index and global food prices are examined for causal connections using variable-lag transfer entropy using a window-sliding technique. The results show that notable rises in a number of international food prices for long as well as short periods are associated with significant increases in the NAO index. Furthermore, the causative function of the NAO index in influencing global food costs is confirmed by variable-lag transfer entropy. Is highly recommended as it directly connects the research to actionable outcomes for policymakers and the overarching goal of sustainability and food security. This study provides the first direct evidence of a robust, long-range cross-correlation and causal link between the North Atlantic Oscillation (NAO) index and key global food prices. It introduces a novel, robust methodological framework to visualize this time-varying relationship, offering a critical tool for policymakers and forecasting models.

Purpose: The GIG-OSH cohort was established to investigate the impact of digital platform work on occupational safety and health (OSH), working and employment conditions, and health in seven countries in Europe. Participants: The cohort comprises 3,945 digital platform workers from seven European countries. The sample includes both web-based workers (e.g., micro-tasking, freelance design) and on-location workers (e.g., delivery, transport). Participants were recruited using non-probabilistic sampling strategies tailored to national contexts, including social media advertising, recruitment through micro-task platforms, and on-site field outreach. Multidimensional data have been collected through online surveys (implemented via REDCap) covering sociodemographic characteristics, working and employment conditions, psychosocial risks, algorithmic management, and physical and mental health indicators. Findings to date: Participants had a mean age of 32.6 years at baseline (SD 10.4), and the majority are male (58.8%), with a higher concentration of migrants in on-location tasks (62.2%) compared to web-based tasks (48.8%). Regarding educational attainment, 55.4% of the total cohort holds a tertiary degree, reaching 64.4% among web-based workers. Platform work intensity varies significantly: on-location workers averaged 85.4 hours of work in the last month, while web-based workers averaged 47.0 hours. Mean income from platform work as a percentage of the national median was 20.6% (SD 22.2). The mean WHO-5 Well-Being Index score was 58.7 (SD 20.3), which is notably lower than the European general population average (69.4), indicating poorer mental health outcomes among cohort members. Future plans: The GIG-OSH cohort represents the first large-scale, longitudinal study examining occupational safety and health among digital platform workers across multiple European countries. Future waves will prioritize developing precise tools to measure hourly earnings and unpaid waiting time. Future research should aim to include underrepresented subgroups, such as medical and domestic care workers, and explore potential linkage with administrative records to evaluate long-term health trajectories and the impact of new EU labour regulations.

BackgroundProlonged wakefulness, restricted sleep, and circadian factors can impact driving performance and road safety. Currently, there are no effective objective roadside tests to detect the state of drivers sleepiness during or prior to driving, or predict future driving impairment risk. This paper reports on an extended wakefulness protocol used to determine if a portable virtual reality device to administer vestibular-ocular motor function (VOM) tests can effectively detect 1) drivers state of sleepiness during or just prior to driving, and 2) predict trait sleepiness and future driving risk. MethodsFifty healthy adults with regular sleep within 9pm to 8am were recruited for an experimental laboratory procedure which involved two phases: an initial overnight sleep study, and a subsequent period of extended wakefulness lasting ~29 hours. During the wakefulness phase, participants undertook neurobehavioural testing, a simulated driving test, and repeat assessments of VOM to establish if ocular markers can predict sleepiness state and sleepiness-related performance impairments (Trial registry ACTRN12621001610820). DiscussionThis protocol outlined a study that aimed to establish the sensitivity of VOM test the effects of extended wakefulness and circadian phase on driver state and trait sleepiness and subsequent sleepiness-related driving impairment. Furthermore, the protocol aims to define the best VOM predictors to identify driver sleepiness state (road side testing and pre-drive assessments) and sleepiness trait (predicting future driving risk) to establish proof of concept for its potential application as a roadside, pre-drive and general sleepiness related fitness to drive test.

BackgroundDengue outbreaks have become a severe threat to Bangladesh as the infections and mortality numbers are skyrocketing in recent years. Favorable environmental and anthropogenic conditions have established the capital of Bangladesh, Dhaka city as the epicenter of dengue outbreak. Studies have showed that climate change induced extreme weather events are exacerbating Aedes mosquito breeding and dengue virus transmission conditions. Methodology/Principal FindingsIn this study, short-term (0-6 weeks) associations of maximum temperature and heatwave days on dengue cases in Dhaka city were examined through Distributed Lag Non-linear Model (DLNM) methodology for weekly measurement of 2016-2024, taking into account relative humidity, cumulative rainfall, seasonality and hospital closure effect. Two separate negative binomial models were constructed. The maximum temperature model rendered an overall inverted U-shaped association, where the maximum temperature range of 31.5-33.2{degrees}C showed a sustained elevated dengue risk, with highest risk estimate at 33.2{degrees}C [relative risk (RR): 1.186, 95% CI: 1.002, 1.403]. Whereas, results of weekly heatwave days showed an overall protective effect (RR<1) for dengue cases. The lowest risk of infection was found at 3 heatwave days per week, with RR 0.275 (95% CI: 0.178, 0.423). Multiple sensitivity analyses were conducted for both models to evaluate their robustness. Lastly, the optimized models were analyzed under three distinct sub-periods, to capture the association of exposure variables with predominant circulating serotypes. Conclusions/SignificanceThe findings of the study aim to support public health policymakers and healthcare authorities in designing and implementing effective vector control interventions under emerging climatic emergencies. Author SummaryDengue disease is one of the most buringing issue in Bangladesh in recent years. This vector-borne disease is inherently influenced by climatic variables, i.e., temperature, rainfall, humidity, etc. Moreover, these relations are complex and non-linearly associated. Due to shift in climatic conditions, the occurance of extreme weather events are becoming frequent, with increased magnitude and longer duration. In this study, the nonlinear and delayed association of dengue infections due to the exposure of extreme temperature events were assessed in climate-change vulnerable Dhaka city. To do this, a statistical method was used, called distributed lag nonlinear methodology (DLNM). The results showed that dengue infections had an inverted U-shaped (parabolic) relationship with maximum temperature, while compared to mean maximum temperature, and a suppressive association with heatwaves relative to days without heatwaves. The findings aim to work as an early warning system, and support to policymakes and healthcare authorities to tackle the dengue surge in the changing climate.

BackgroundThe COVID-19 pandemic required South African public sector HIV viral load (VL) laboratories to scale up Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) testing while maintaining essential HIV services. This placed additional pressure on diagnostic services. This dual mandate introduced significant occupational and environmental challenges (OEC) for staff that remain underexplored. ObjectiveThis study aimed to investigate the OEC and effects that staff experienced during the implementation of COVID-19 testing at public sector VL laboratories in South Africa. MethodsA quantitative, cross-sectional study utilised a census approach among technical and support staff. Data were collected via a structured REDCap questionnaire using 5-point Likert scales. Pre- and post-implementation challenges were assessed across four domains: workload, environmental conditions (space, ventilation, waste), communication, and PPE availability. Statistical analyses included the Wilcoxon Signed-Rank and Spearmans correlation tests. ResultsPerceived occupational challenges increased significantly across all domains post-implementation. Staff workload saw the highest rise (mean score 3.02 to 3.53). Adverse health effects were pervasive; 80.2% of staff reported burnout/fatigue, and 76.5% reported increased anxiety/stress. A strong positive correlation was observed between post-COVID-19 challenges and adverse mental and physical health outcomes (rho = 0.449, p < 0.001). Furthermore, 35.8% of staff considered resigning due to increased job demands. ConclusionIntegrating COVID-19 testing exacerbated systemic weaknesses, causing measurable psychological injury and threatening workforce retention. Findings suggest that the diagnostic workforce requires formal crisis surge staffing models and institutionalised mental health support to safeguard personnel and maintain essential services during future health emergencies.

Abstract This protocol is reported in accordance with the SPIRIT 2025 guidelines for clinical trial protocols. Introduction: Young children, from birth to age 5 y are particularly vulnerable to indoor air pollutants and respiratory pathogens. Portable air purifiers (or filtration) and upper-room ultraviolet germicidal irradiation (UVGI) are two widely used interventions with the potential to improve indoor air quality (IAQ) and reduce sick-related absences. However, a review of the literature revealed no real-world randomized studies evaluating their effectiveness in reducing young children's sick-related absences in early care and education (ECE) classrooms. Methods and Analysis: The OK-AIR study is a longitudinal, cluster-randomized 2x2 factorial trial conducted in Head Start centers using two implementation cohorts: Cohort 1 (five Head Start centers and 20 classrooms from 2023 to 2024) and Cohort 2 (11 centers and 59 classrooms from 2025 to 2026), with expanded inclusion of rural areas. Cohort 1 enrolled 204 children, 48 teachers and 5 site directors, and Cohort 2 enrolled 462 children, 97 teachers and 11 site directors. Within each center, four classrooms are randomized to: (1) control; (2) portable filtration; (3) upper-room ultraviolet germicidal irradiation (UVGI); or (4) both interventions. Cohort 2 was initially planned as a second factorial trial but was amended to a purifier-only design due to funding changes; details are provided in the protocol amendments section. We collect continuous IAQ data, including particulate matter (PM) with aerodynamic diameters [&le;]1 m (PM1), [&le;]2.5 m (PM2.5), [&le;]4 m (PM4), and [&le;]10 m (PM10); total volatile organic compounds (TVOCs) index; nitrogen oxides (NOx) index; carbon monoxide (CO), noise; temperature; and relative humidity, alongside daily child absences. Seasonal environmental surface swabs (dining tables and toilet flooring) are tested by Reverse-Transcriptase quantitative Polymerase Chain Reaction (RT-qPCR) for Influenza A/B, Respiratory Syncytial Virus (RSV), Human Parainfluenza Virus Type 3 (HPIV3), Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), and Norovirus. IAQ monitoring is structured across Winter, Spring, Summer, and Fall, including designated baseline/off-period weeks to characterize temporal and seasonal variability in environmental measures across classrooms and centers. Multi-informant surveys (Director, Teacher, Parent) capture contextual factors, and children's social-emotional development is assessed using teacher ratings on the Devereux Early Childhood Assessment (DECA). The primary outcome is the sick-related absence rate, analyzed as cumulative absences over the attendance year while accounting for clustering by school and classroom using generalized mixed-effects models. Secondary outcomes include children's social-emotional ratings, IAQ metrics and pathogen detection rates; analyses of IAQ incorporate time/seasonal structure, and season-stratified absenteeism analyses will be treated as secondary/exploratory refinements. An economic evaluation will estimate incremental intervention costs and cost-effectiveness/cost-benefit (such as cost per sick-related absence day averted). Ethics and Dissemination: This study was approved by the Institutional Review Board (IRB) at the University of Oklahoma. Findings will be shared through peer-reviewed publications; presentations at local, state, and national conferences; research briefs developed for lay and policy audiences; and community briefings prioritizing the participating early childhood programs and communities. ISRCTN Trial Registration: ISRCTN78764448 Disclaimer: The views expressed are those of the authors and do not reflect the official views of the Uniformed Services University or the United States Department of War. Strengths and Limitations of This Study: {middle dot} Real-world longitudinal cluster RCT: The study uses a rigorous longitudinal cluster-randomized 2x2 factorial design in real-world ECE settings. {middle dot} Combined interventions: Interventions target both air filtration and disinfection, allowing for combined and comparative evaluation. {middle dot} Objective air quality monitoring: Continuous monitoring of IAQ metrics provides objective and reliable data on environmental change. {middle dot} Environmental pathogen surveillance: qPCR on surface swabs yields an objective biological outcome to triangulate with IAQ and absences. {middle dot} Comprehensive context and child measures: Multi-method and multi-reporter data collection includes Head Start attendance records, continuous air monitoring, pathogen detection, contextual surveys completed by center directors, teachers, and parents, and standardized social-emotional assessments (DECA) completed by classroom teachers. Head Start program records providing children's longer-term health data available through Health Insurance Portability and Accountability Act (HIPAA) authorization. {middle dot} Clustered/temporal complexity: Seasonal design accounts for variation over time but may introduce complexity in modeling temporal effects. {middle dot} Practical Implications: Study findings will have practical implications for Head Start and other ECE programs striving to maximize child attendance with cost effective strategies. Keywords: Early childhood; Head Start; indoor air quality (IAQ); air purifiers; filtration; ultraviolet germicidal irradiation; cluster randomized trial; absenteeism; environmental pathogens; DECA; cost-benefit analysis

IntroductionTraditional bone-setting remains a culturally significant healthcare practice in low- and middle-income countries, particularly in regions like Sudan where modern orthopedic services are often inaccessible or unaffordable .This study examines the role of traditional healing practices in orthopedic care in White Nile State, Sudan, assessing patient perceptions, treatment effectiveness, and sociocultural factors influencing healthcare choices. MethodsA cross-sectional analytical study was conducted among 147 patients, 7 traditional healers, and 4 orthopedic practitioners in urban and rural areas of White Nile State. Data were collected using structured questionnaires and interviews, focusing on treatment preferences, perceived effectiveness, and barriers to integration. Descriptive and inferential statistics were used to analyze quantitative data, while thematic analysis was applied to qualitative responses from healers and practitioners. ResultsFractures (45.6%) and arthritis (23.1%) were the most common orthopedic conditions. 30.6% of patients initially sought traditional treatment, all eventually utilized modern care (medication 71.4%, surgery 42.9%). Traditional healing was perceived as somewhat effective by 40% of users, whereas 59.9% rated modern care as very effective. Key factors influencing treatment choices included cultural beliefs (29.9%), accessibility (18.4%), and cost (16.3%). No significant demographic associations were found with treatment preference or effectiveness (p > 0.05). Traditional healers predominantly treated dislocations (100%) and fractures (71.4%) using manual techniques, with 57.1% referring complex cases to modern practitioners. Barriers to collaboration included lack of communication (85.7% of healers) and differing treatment philosophies (50% of practitioners). ConclusionThis study highlights the persistent dual reliance on traditional and modern orthopedic care in Sudan, with modern treatments perceived as more effective yet traditional methods remaining culturally entrenched especially in rural areas. The path forward requires bridging these systems through mutual respect, shared protocols, and community engagement to ensure safe, equitable, and effective musculoskeletal care for all Sudanese patients.

ObjectiveThe study aimed to analyze factors associated with cotinine levels as an early risk indicator for chronic diseases and students readiness to quit smoking in Praya Barat District. MethodsThis study used a cross-sectional design involving 563 high school students in Praya Barat District. Data analysis was performed using the Chi-square test and multiple logistic regression to identify determinants of high cotinine levels. ResultsA total of 67% of subjects had high cotinine levels, indicating high levels of nicotine exposure among students. The results of the analysis showed that the main determinants of high cotinine levels were cigarette consumption of [&ge;]5 cigarettes/day (AOR=2.426; 95% CI=1.534-3.838; p<0.001), male gender (AOR=2.100; 95% CI=1.358-3.250; p=0.001), family members who smoke (AOR=2.149; 95% CI=1.359-3.399; p=0.001), rarely of exercise (AOR=2.155; 95% CI=1.350-3.440; p=0.001), and personal history of chronic disease (AOR=2.646; 95% CI=1.653-4.234; p<0.001). Meanwhile, willingness to participate in a smoking cessation program did not show a significant relationship (p=0.093). ConclusionsMost students showed high cotinine levels, indicating significant exposure to nicotine and a potential risk of chronic disease in the future. The most influential factors were active smoking behavior, a family environment of smokers, and low levels of physical activity.

Background: Nursing interns are at high risk of psychological distress due to academic and clinical stressors. While poor sleep quality is linked to anxiety and depression, the buffering role of social support remains underexplored in this population. Aims: To explore the role of social support in regulating the relationship between sleep and mental health among nursing interns. Methods: A total of 396 nursing interns completed self-administered questionnaires including the Pittsburgh Sleep Quality Index (PSQI), Social Support Rate Scale (SSRS), Generalized Anxiety Disorder-7 (GAD-7), and Patient Health Questionnaire-9 (PHQ-9). Hierarchical regression and simple slope analyses were used to test moderation effects. Results: Poor sleep quality was significantly associated with higher anxiety ({beta}=0.449, P<0.001) and depression ({beta}=0.535, P<0.001). Social support significantly moderated these relationships. Under low social support, the effects of sleep quality on anxiety ({beta} = 0.602) and depression ({beta} = 0.779) were stronger than under high support (anxiety: {beta} = 0.396; depression: {beta} = 0.515). Conclusions: Social support buffers the adverse psychological effects of poor sleep among nursing interns. Interventions should integrate sleep hygiene education with strategies to enhance social support.

The co-occurrence of per- and polyfluoroalkyl substances (PFAS) and volatile organic compounds (VOCs) in industrial environments poses complex toxicological risks that standard additive models fail to capture. This study elucidates a novel "metabolic blockade" mechanism wherein PFAS competitively inhibits the renal excretion of VOC metabolites, thereby amplifying neurotoxic burdens. Utilizing a Double Machine Learning (DML) framework on data from National Health and Nutrition Examination Survey (2005-2020), we analyzed a final intersectional cohort of 1,975 participants. We identified a robust inhibition of VOC metabolite clearance by serum PFAS. Specifically, PFNA significantly suppressed the excretion of the benzene metabolite URXPMA (Causal {beta}TMLE = -0.219, p < 0.001), with efficacy dependent on perfluorinated chain length. Molecular docking simulations revealed the biophysical basis of this antagonism: long-chain PFNA exhibited superior binding affinity to the Organic Anion Transporter 1 (OAT1) ({Delta}G = -6.333 kcal/mol) compared to native VOC metabolites ({Delta}G = -4.957 kcal/mol), confirming high-affinity competitive inhibition at the renal interface. In a neurocognitive sub-cohort (N = 1,200), this interference translated into functional synergism; high-PFNA exposure magnified VOC-associated cognitive impairment by 1.5-fold and significantly exacerbated the negative association between VOC burden and processing speed ({beta}int = -0.263, p = 0.004). These findings define PFAS as a "metabolic amplifier" of co-contaminant toxicity, necessitating a paradigm shift toward mixture-based hazardous material regulations that account for transporter-level interactions.

RationaleIdiopathic pulmonary fibrosis (IPF) is a rare, chronic, progressive lung disease with high mortality and few treatment options. Using an additive genetic model, genome-wide association studies (GWAS) have identified multiple risk loci highlighting new genes and pathways of interest. Since IPF risk could also be influenced by non-additive effects, we hypothesised that association analyses using alternative genetic models may provide additional mechanistic insight. ObjectivesTo perform GWAS of IPF susceptibility to detect associations where the underlying effects are consistent with recessive or dominant genetic models. MethodsWe performed GWAS of IPF susceptibility, with logistic regression assuming dominant or recessive genetic models, including 5,159 IPF cases, from clinically-curated sources, and 27,459 controls. We functionally annotated independent signals and performed variant-to-gene mapping, applying fine-mapping to define potentially causal variants and genes. We assessed differential expression levels of genes of interest in publicly available single cell RNAseq data and in primary cells derived from IPF donors and controls. Main ResultsWe identified five genome-wide significant signals, under a recessive model, that had not been reported previously. These included exonic variants in the cell-cycle gene Polyamine-Modulated Factor 1 (PMF1) and in Epsin 3 (EPN3) genes. We also observed evidence of increased PMF1 expression in airway basal cells of IPF patients compared to controls. ConclusionsUsing alternative genetic models in IPF susceptibility GWAS identified new signals and genes, providing new insights into IPF pathogenesis and potential future therapies.

BackgroundVariation in the HLA loci, located on human chromosome 6p, has been associated with hundreds of diseases and conditions. However, high levels of polymorphism that characterize the HLA system, coupled with generally modest effect sizes for most phenotypes, necessitate relatively large sample sizes to power association studies; meanwhile, high resolution HLA genotyping remains relatively resource intensive. These constraints limit identification of novel associations. While phenome-wide association studies (PheWAS) in the context of large registries with available electronic health records (EHR) have revealed new insights into the role of HLA in disease, many common health conditions are poorly represented in EHR due to the temporal nature of their occurrence or general underreporting. Further, these studies have generally been conducted with HLA genotyping data imputed from microarrays, rather than direct measurement of high-resolution genotypes. ObjectiveTo overcome these limitations and reveal novel HLA associations we undertook a PheWAS in many previously understudied health conditions. MethodsWe queried over 300 hundred conditions, diseases and traits from 70,724 subjects registered with NMDP with available high-resolution HLA genotyping (HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1). After stratifying according to ancestry, we performed a logistic regression analysis adjusting for sex and age for HLA-phenotype association. ResultsWe identified 48 significant HLA associations across ancestry groups, confirming several known associations and uncovered fifteen novel associations. Most novel associations pertained to common infectious or allergic phenotypes that often go under-reported in the EHR. Of particular translational importance, we identified a previously undetected yet very strong association between HLA-DRB1*04:01 and sensitivity to cefaclor, a specific class of cephalosporin (OR = 3.74, p-value 5.10E-28). Molecular docking simulations predict cefaclor binding in the P4 pocket of HLA-DRB1*04:01, with substantially greater affinity than non-associated antibiotics, including other cephalosporins. This pharmacogenomic signal highlights an opportunity for risk stratification and targeted prevention of adverse drug reactions. Other novel associations found, such as susceptibility to genital warts (HPV) and allergic rhinitis, reveals new insights into the role of specific HLA alleles in immune-mediated disease. The vast majority of these novel associations were replicated in the independent All of Us cohort, confirming the validity of this approach. ConclusionCollectively, our findings demonstrate the value of integrating population-scale, high-resolution HLA genotypes with phenotyping beyond the EHR to reveal immunogenetic influences on common health outcomes. They also point to immediate translational avenues - particularly for drug hypersensitivity - while motivating future functional studies and prospective clinical validation to refine mechanistic understanding and clinical utility.

IntroductionFibrosis can affect organs throughout the body and is present in a wide range of diseases. Recent research has suggested that there could be shared biological mechanisms that lead to fibrosis in different organs. MethodsWe performed genome-wide association studies using UK Biobank for fibrosis in 12 different organ-systems and meta-analysed results with previously published studies of fibrotic diseases. We considered genetic associations that colocalised across [&ge;]3 organs as those likely to be involved in general fibrotic mechanisms and also identified novel genetic variants not previously reported as associated with fibrosis. Genetic correlation of fibrosis between organs was calculated using linkage disequilibrium score regression (LDSC). Discovery analyses were performed using European ancestry individuals and results were tested further in African, South Asian and East Asian ancestry groups. ResultsWe identified eight genetic loci that colocalised across three or more organs. One of these signals, located near the SH2B3 and ATXN2 genes, showed evidence of a shared causal variant for fibrosis across five organs. We also identified two novel fibrotic associations, one implicating alternative splicing of TFCP2L1 for urinary fibrosis and another implicating a missense variant in FAM180A for intestinal-pancreatic fibrosis. We observed significant genetic correlations for all organs, particularly for liver and skeletal fibrosis. ConclusionWe found evidence of shared genetic associations for fibrosis across organs, both at individual genetic loci and genome-wide. This highlights specific genes that may contribute to fibrosis across organs and diseases, which may facilitate the development of new therapies.

IntroductionHealthcare organizations have begun incorporating screening procedures for social determinants of health (SDOH) into care, recognizing the impact these factors can have on health outcomes. We aimed to present methods for evaluating redundancy in the risk information gained across SDOH questions and for evaluating whether demographic biases are present in whether patients were asked SDOH questions and whether they declined to answer them. MethodsSDOH question data were analyzed for 1.8 million UNC Health patients. To evaluate risk information redundancy, response agreement was analyzed for pairs of questions. Demographic biases were evaluated using logistic regression models. ResultsRisk information redundancy was identified, particularly across food and financial insecurity questions. Furthermore, female and White patients were more likely to be asked some questions than other groups, and American Indian or Alaska Native and Hispanic or Latino patients were less likely to decline to answer questions. ConclusionsWe demonstrated methods healthcare organizations can use to evaluate their SDOH screening procedures. These methods yielded insights for (1) reducing burden in clinical workflows by identifying where redundancy could be eliminated and (2) reducing bias in SDOH data collection through more systematic screening protocols.

BackgroundRetrieval-augmented generation (RAG) frameworks such as RAPID [1] have demonstrated that staged planning and retrieval grounding improve long-form text generation. However, most implementations remain similarity-driven and open-domain, lacking the epistemic safeguards required for biomedical synthesis, where mechanistic completeness, temporal governance, traceability, and explicit gap classification are essential. ObjectiveTo develop and evaluate a topology-aware, graph-augmented retrieval framework for structured biomedical narrative synthesis, and to position it as a domain-constrained evolution of staged RAG aligned with structural principles of digital evidence-based medicine (dEBM). MethodsWe implemented a two-layer architecture operating on a closed, version-controlled corpus of 11,861 peer-reviewed text chunks on iron deficiency. A metadata-constrained vector retriever (RAG01) was extended with a Graph-RAG (RAG02) overlay (RAG02) constructed from chunk-level entity extraction and weighted co-occurrence networks (30 nodes; 118 directed edges). Topic planning was organized through predefined mechanistic axes functioning as structured hypothesis probes. Retrieval was performed under identical deterministic constraints (top-k = 5; cosine threshold = 0.50; publication year [&ge;] 2023), and graph diagnostics--including local connectivity, induced subgraph density, modular overlap, and multi-hop stability--were used to distinguish retrieval insufficiency from corpus-level evidentiary scarcity. ResultsIn a case study of obesity-associated iron deficiency, the entity network exhibited a centralized regulatory topology with hepcidin as a high-connectivity hub. Axis-based retrieval combined with graph auditing consistently reinforced an inflammation-mediated hepcidin pathway linking obesity to iron deficiency, while alternative mechanisms lacked stable multi-hop embedding. Compared with vector-only retrieval, graph augmentation preserved semantic alignment and increased mean cosine similarity from 0.673 to 0.694 while reducing similarity dispersion (SD 0.056 to 0.035) under identical constraints. Graph activity ratio was 1.00 in the temporally filtered corpus. ConclusionsBy integrating mechanistic axis decomposition, topology-aware auditing, causal scaffolding, and expert-driven iterative refinement, the proposed framework implements selected structural constraints inspired by evidence-based medicine within a controlled digital synthesis environment. The approach advances retrieval-augmented generation beyond similarity-based summarization toward a reproducible model of topology-aware biomedical evidence interrogation with implications for AI-assisted systematic reviews.

BackgroundA Hospital Medicine Advanced Practice Provider (HMAPP)-led care model developed in response to the high acuity and increased patient volumes associated with the Covid-19 pandemic. Although anecdotally perceived as a successful model, questions remained if there was adequate pre-planning and formal implementation strategy for stakeholder buy-in. ObjectiveTo elicit HM physicians and APPs perceptions of the HMAPP-led care model implementation and consider necessary steps for optimal future APP care model development and operation. Design, Setting and ParticipantsThis qualitative study used 10 (5 physicians and 5 APPs involved in the care model pre- and post-implementation) individual semi-structured, virtual interviews based on the Consolidated Framework for Implementation Research (CFIR). Deductive and inductive rapid analysis was utilized to analyze the data. ResultsTwo themes emerged as strengths: 1) Experienced APPs delivered the care model, 2) Acceptance of the care model evolved over time. Four themes suggested opportunities for future development: 1) Guidelines should expand from patient distribution to include minimal collaboration and escalation expectations, 2) Culture change was a barrier to model implementation and acceptance, 3) Intentional collaboration between APPs and Physicians is necessary, 4) Investment in standardized onboarding enhances buy-in of the care model. ConclusionThe impact of an APP care model can be elevated if implemented with key principles and strategies. This is critical in an evolving health care landscape where all providers need to collaborate and practice with their full expertise to maximize safe, efficient and quality patient care.

ObjectiveTo quantify trends in annual mean healthcare costs per person living with HIV from 2003 to 2018 from a publicly funded healthcare system perspective. DesignWe conducted a retrospective population-based study using administrative health data in Ontario, Canada, including 25,842 people living with HIV diagnosed and entering care between 1992 and 2018. A nested cohort from the Ontario HIV Treatment Network Cohort Study (n=3,516) provided additional HIV-related characteristics. MethodsAnnual mean healthcare costs per person were estimated using a validated costing algorithm and inflated to 2025 Canadian dollars. Trends were examined overall and stratified by sociodemographic factors (age, sex, rurality, neighbourhood income, immigration status) and year of entry into HIV care. Within the nested cohort, trends were stratified by nadir CD4 count and any antiretroviral therapy use since diagnosis. ResultsAnnual mean cost per person increased from $11,963 in 2003 to $16,721 in 2018. Medication costs remained the largest cost component throughout (47.4-61.7%) and closely mirrored overall trends. Higher annual mean costs were consistently observed among individuals diagnosed at older ages, lower-income neighbourhood residents, long-term Ontario residents (Canadian-born or immigrated before 1985), and individuals with nadir CD4<200cells/{micro}L. ConclusionMedication expenditures continue to drive healthcare costs for people living with HIV. Cost containing strategies, including expanded generic substitution and strengthened price negotiation, may reduce costs without compromising outcomes. Persistent cost disparities highlight the need to address delayed treatment initiation and broader social determinants shaping HIV treatment access and sustained engagement in care.

BackgroundTuberculosis (TB) incidence peaks in women during their reproductive years and is a leading cause of maternal mortality. Pregnant women with TB have a high risk of failure to initiate TB treatment and poor TB treatment and pregnancy outcomes. We determined the time to treatment initiation in pregnant women diagnosed with TB in a routine programmatic setting. MethodsUsing routine linked electronic data, we identified women 15-45 years of age with laboratory-confirmed and/or clinically diagnosed TB, October 2018-December 2020, in two high-burden sub-districts in Cape Town, South Africa. We compared demographic and clinical characteristics in women with TB by pregnancy status, used time-to-event analysis to determine the time from TB diagnosis to initiation of antituberculosis treatment and Cox regression to assess determinants of treatment initiation. ResultsOf 5,459 women diagnosed with TB, 292 (5.3%) were pregnant. The median age for pregnant women was 28.6 years (interquartile range [IQR]: 23.7-33.7) and non-pregnant women 31 years (IQR:25.2-36.5). HIV prevalence was similar in pregnant (177/292; 60.6%) vs non-pregnant (3200/5167; 61.9%) women. Median time to treatment initiation was two days for pregnant and non-pregnant women. Most women initiated treatment within the first month after their TB diagnosis, after which the rate plateaued in both groups. Time to treatment initiation over 6 months was statistically different (Kaplan Meier Log-rank test, p = 0.0064) with pregnant women lagging behind non-pregnant women. ConclusionsMore than 5% of women diagnosed with TB were pregnant at the time of TB diagnosis. While pregnant women with TB were appropriately initiated on treatment, almost 15% were never started on treatment and there were delays in treatment initiation. While strategic interventions to prioritise early treatment initiation are needed, there should be a specific focus on pregnant women who have not initiated treatment within one month after TB diagnosis.