EClinicalMedicine

Background: The 2024-25 influenza season was the most severe in the United States (US) since 2017-18, with co-circulation of both influenza A virus subtypes (H1N1 and H3N2). Influenza vaccine effectiveness (VE) has varied by season, setting, and patient characteristics. Methods: Using electronic healthcare encounter data from eight US states, we evaluated influenza vaccine effectiveness (VE) against influenza-associated hospitalizations and emergency department or urgent care (ED/UC) encounters from October 2024-April 2025 among children aged 6 months-17 years and adults aged 18+ years. Using a test-negative, case-control design, we compared the odds of influenza vaccination between acute respiratory illness (ARI) encounters with a positive (cases) versus negative (controls) test for influenza by molecular assay, adjusting for confounders. Results: Analyses included 108,618 encounters (5,764 hospitalizations and 102,854 ED/UC encounters) among children and 309,483 encounters (76,072 hospitalizations and 233,411 ED/UC encounters) among adults. Among children across care settings, 17.0% (6,097/35,765) of cases versus 29.4% (21,449/72,853) of controls were vaccinated. Among adults, 28.2% (21,832/77,477) of cases versus 44.2% (102,560/232,006) of controls were vaccinated. VE was 51% (95% confidence interval [95% CI]: 41-60%) against influenza-associated hospitalizations and 54% (95% CI: 52-55%) against influenza-associated ED/UC encounters among children. VE was 43% (95% CI: 41-46%) against influenza-associated hospitalizations and 49% (95% CI: 47-50%) against influenza-associated ED/UC encounters among adults. Conclusions: Influenza vaccination provided protection against influenza-associated hospitalizations and ED/UC encounters among children and adults in the US during the severe 2024-25 influenza season. These findings support influenza vaccination as an important tool to reduce influenza-associated disease.

Background Outcome after stroke varies according to stroke subtype by location, but healthcare systems data studies do not include subtyping information. We linked natural language processing (NLP) of brain imaging reports to routinely collected data to estimate risk of death and other outcomes after stroke subtypes in a nationwide dataset. Methods We applied a previously validated NLP algorithm to all CT and MRI head scan reports in Scotland between 2010 and 2018. We linked the reports to hospital readmissions, prescriptions and death data to identify and characterize people with stroke, and to categorize into deep and cortical ischemic stroke, deep and lobar intracerebral hemorrhage (ICH), subarachnoid hemorrhage, and subdural hemorrhage. We used a matched cohort design, and age- and sex-matched four controls per case who never had a stroke. By subtype, we estimated rehospitalization with stroke, myocardial infarction (MI), cancer, dementia, epilepsy and death, accounting for confounders and competing risk of death. Results From 785,331 people with a head scan, we identified 64,219 with clinical stroke phenotypes (mean age 73.4yrs, 49.5% male), and subtyped 12,616 with deep ischaemic stroke; 14,103 with cortical ischaemic stroke; 1,814 with deep ICH; and 1,456 with lobar ICH. There was higher absolute rate of 1-year hospital readmission for lobar compared with deep ICH (4.9% [95%CI 3.9% - 6.1%] vs 3.4% [2.6% - 4.3%]), higher risk of dementia beyond 6 months after lobar ICH compared to controls than for other stroke subtypes (aHR 3.5 [2.3-5.3]); and higher risk of MI within 6 months of cortical ischemic stroke than for other stroke subtypes (aHR 4.6 [3.4-6.3]). Conclusions NLP of free-text reports linked to coded data successfully subtyped stroke at scale, and we estimated risk of clinically relevant outcomes. Future work should use free text to enable large-scale audit and epidemiology of people with stroke.

Background: Current medical large language model (LLM) evaluations largely rely on small collections of cases, whereas rigorous safety testing requires large-scale, diverse, and complex cases with verifiable ground truth. Multiple Sclerosis (MS) provides an ideal evaluation model, with validated diagnostic criteria and numerous paraclinical tests informing differential diagnosis, investigation, and management. Methods: We generated synthetic MS cases with ground-truth labels for diagnosis, localisation, and management. Four frontier LLMs (Gemini 3 Pro/Flash, GPT 5.2/5 mini) were instructed to analyse cases to provide anatomical localisation, differential diagnoses, investigations, and management plans. An automated evaluator compared these outputs to the ground-truth labels. Blinded subspecialty experts validated 70 cases for realism and automated evaluator accuracy. We then evaluated LLM decision-making across 1,000 cases and scaled to 10,000 to characterise rare, catastrophic failures. Results: Subspecialist expert review confirmed 100% synthetic case realism and 99.8% (95% CI 95.5 to 100) automated evaluation accuracy. Across 1,000 generated MS cases, all LLMs successfully included MS in the differential diagnoses for more than 91% cases. However, diagnostic competence did not associate with treatment safety. Gemini 3 models had low rates of clinically appropriate steroid recommendations (Flash: 7.2% 95% CI 5.6 to 8.8; Pro: 15.8% 95% CI 13.6 to 18.1) compared to GPT 5 mini (23.5% 95% CI 20.8 to 26.1), frequently overlooking contraindications like active infection. OpenAI models inappropriately recommended acute intravenous thrombolysis for MS cases (9.6% GPT 5.2; 6.4% GPT 5 mini) compared to below 1% for Gemini models. Expanded evaluation (to 10,000 cases) probed these errors in detail. Thrombolysis was recommended in 10.1% of cases lacking symptom timing information and paradoxically persisted (2.9%) even when symptoms were explicitly documented as more than 14 days old. Conclusion: Automated expert-level evaluation across 10,000 cases characterised artificial intelligence clinical blind spots hitherto invisible to small-scale testing. Massive-scale simulation and automated interrogation should become standard for uncovering serious failures and implementing safety guardrails before clinical deployment exposes patients to risk.

Objectives: In Latin America, up-to-date information to monitor UNAIDS 95-95-95 HIV targets in key populations, such as men who have sex with men, is limited. Elsewhere, structural homophobia restricts access to ART. Conceptual frameworks suggest that intersecting forms of violence and discrimination may negatively influence HIV care outcomes through psychosocial and structural pathways, although empirical evidence remains limited. The study aimed to assess whether sexual orientation outness and recent homophobic violence are associated with not being on ART among Latin American MSM living with HIV. Methods: This cross-sectional study is a secondary analysis of data from LAMIS-2018, including 7,609 MSM aged 18+ with an HIV diagnosis [≥]1 year prior from 18 Latin American countries. Participants self-reported ART status, sociodemographic characteristics, homophobic violence, and sexual orientation outness. Bivariate and multivariate logistic regressions identified those factors associated with not being on ART. Results: Nine percent of MSM with HIV were not on ART, 18% reported low sexual orientation outness, and 27% experienced homophobic violence, especially in Andean and Central American countries. Not being on ART was associated with recent homophobic violence (aPR=1.25), low outness (aPR=1.22), unemployment (aPR=1.27), and residence in the Andean subregion (aPR=1.87), Mexico (aPR=1.28), or the Southern Cone (aPR=1.45) versus Brazil. Protective factors included being older (25-39: aPR=0.72; >39: aPR=0.49), living in large cities (aPR=0.72), having a stable partner (aPR=0.78), and university education (aPR=0.74). Conclusions: Recent homophobic violence and low sexual orientation outness were associated with not being on ART among MSM in Latin America. While access varies across countries, structural factors such as stigma and violence may limit engagement in care. Addressing these barriers alongside strengthening health systems may be key to improving ART uptake and advancing progress toward the 95-95-95 targets.

ObjectiveStudies of nutritional status and host responses during severe and critical illness have focused predominantly on obesity; in contrast, the relationship between undernutrition, host responses, and clinical outcomes in adults hospitalized with severe infection remains poorly defined. We sought to determine whether severe undernutrition is associated with distinct host responses and clinical outcomes in adults hospitalized with severe infection. DesignProspective cohort study. SettingTwo public referral hospitals in Uganda. PatientsNon-pregnant adults ([≥]18 yr) hospitalized with severe, undifferentiated infection. InterventionsNone. Measurements and Main ResultsWe analyzed clinical data and serum Olink proteomic data from 432 participants (median age, 45 yr [IQR, 31-57 yr]; 44% male). Overall, 213 participants (49%) met prespecified criteria for undernutrition, including 52 (12%) with severe undernutrition. Clinically, severe undernutrition was associated with HIV coinfection, microbiologically diagnosed tuberculosis, greater physiological instability, and higher mortality. After adjustment for age, sex, illness duration, study site, and HIV, malaria, and tuberculosis coinfection, severe undernutrition was associated with higher expression of proteins involved in pro-inflammatory immune signaling, endothelial and vascular remodeling, hypoxia and oxidative stress responses, and extracellular matrix remodeling, together with lower expression of proteins linked to growth signaling, anticoagulant regulation, and lipid homeostasis. ConclusionsSevere undernutrition is associated with a distinct high-risk clinical phenotype and biologic signature in adults hospitalized with severe infection. These findings suggest that undernutrition may potentiate key domains of sepsis pathobiology, with implications for strengthening nutritional support and informing host-directed treatment strategies in low- and middle-income countries where malnutrition is common. Key PointsO_ST_ABSQuestionC_ST_ABSHow does undernutrition influence immune, metabolic, and endothelial responses to severe infection in adults? FindingsIn this multicenter cohort study of 432 adults hospitalized with severe infection in Uganda, severe undernutrition was associated with greater physiologic instability, higher mortality, and a distinct proteomic host-response profile. Adults with severe undernutrition exhibited a proteomic signature characterized by pro-inflammatory immune signaling, endothelial and extracellular matrix remodeling, and hypoxia and oxidative stress responses, together with lower expression of proteins involved in growth signaling, anticoagulant regulation, and lipid homeostasis. MeaningSevere undernutrition is associated with a distinct high-risk clinical and biologic phenotype during severe infection, with implications for nutritional support, risk stratification, and host-directed therapeutic strategies, particularly in low- and middle-income countries.

IntroductionThere is increasing interest in the peripheral administration of vasopressors for two main reasons: (1) to expedite vasopressor initiation in patients with refractory shock and (2) to avoid the potential complications associated with central venous catheter placement. The current evidence on the use of peripheral vasopressor administration is primarily based on single-center observational studies. There are inconsistencies in the administration of peripheral vasopressors, including catheter gauge and location, monitoring practices, vasopressor concentrations, and duration of use. This has made it difficult for institutions to develop best practice guidelines. A randomized controlled trial is needed to address this knowledge gap. Methods and analysisThe Peripheral Use of Low-dose Vasopressors for Safety and Efficacy (PULSE) in the intensive care unit is a prospective, unblinded feasibility study. Eligible patients will be 18 years or older, have no existing central venous catheter or peripherally inserted central catheter and have the presence of shock requiring a minimum vasopressor dose of any of the following: norepinephrine 0.0625 mcg/kg/min, phenylephrine 0.625 mcg/kg/min, and epinephrine 0.0625 mcg/kg/min. Fifty patients will be randomized 1:1 into either the peripheral venous catheter or central venous catheter group. The primary outcome is feasibility, defined as (1) a recruitment rate of 4 participants per month, (2) a data capture rate of [&ge;]90%, and (3) a <50% conversion rate from peripheral to central access. The secondary outcomes include the safety of peripheral vasopressor use, alive and central-line-free days, the number of attempts needed to place a catheter, volume status, in-hospital mortality rate, ICU and hospital length of stay, and patient-centred important outcomes. ImplicationsThe data collected from this study will inform the design of a definitive randomized controlled trial to assess the safety and efficacy of protocol-driven peripheral vasopressor administration. Ethics and disseminationThis study received approval (6042888) from the Queens University Health Sciences/Affiliated Teaching Hospitals Research Ethics Boards. Results of this study will be presented at critical care conferences and submitted for publication. Trial registration numberNCT06920173 (https://clinicaltrials.gov/study/NCT06920173).

Importance: Physicians routinely prognosticate to guide care delivery and shared decision making, particularly when caring for patients with critical illnesses. Yet, these physician estimates are prone to inaccuracy and uncertainty. Artificial intelligence, including large language models (LLMs), show promise in supporting or improving this prognostication. However, the performance of contemporary LLMs in prognosticating for the heterogeneous population of critically ill patients remains poorly understood. Objective: To characterize and compare the performance of LLMs and physicians when predicting 6-month mortality for hospitalized adults who survived critical illness. Design: Embedded mixed methods study with elicitation and comparison of prognostic estimates and reasoning from LLMs and practicing physicians. Setting: The publicly available, deidentified Medical Information Mart for Intensive Care (MIMIC)-IV v2.2 dataset. Participants: We randomly selected 100 hospitalizations of adult survivors of critical illness. Four contemporary LLMs (Open AI GPT-4o, o3- and o4-mini, and DeepSeek-R1) and 7 physicians provided independent prognostic estimates for each case (1,100 total estimates; 400 LLM and 700 physician). Main outcomes and measures: For each case, LLMs and physicians used the hospital discharge summary and demographics to predict 6-month mortality (yes/no) and provide their reasoning (free text). We assessed prognostic performance using accuracy, sensitivity, and specificity, and used inductive, qualitative content analysis to characterize reasonings. Results: Mean physician accuracy for predicting mortality was 70.1% (95% CI 63.7-76.4%), with sensitivity of 59.7% (95% CI 50.6-68.8%) and specificity of 80.6% (95% CI 71.7-88.2%). The top-performing LLM (OpenAI o4-mini) accuracy was 78.0% (95% CI 70.0-86.0%), with sensitivity of 80.0% (95% CI 67.4-90.2%) and specificity of 76.0% (95% CI 63.3-88.0%). The difference between mean physician and top-performing LLM accuracy was not statistically significant (p = 0.5). Qualitative analysis revealed similar patterns in LLM and physician expressed reasoning, except that physicians regularly and explicitly reported uncertainty while LLMs did not. Conclusion and Relevance: In this study, LLMs and physicians achieved comparable, moderate performance in predicting 6-month mortality after critical illness, with similar patterns in expressed reasoning. Our findings suggest LLMs could be used to support prognostication in clinical practice but also raise safety concerns due to the lack of LLM uncertainty expression.

Background: Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy but can cause serious immune-related adverse events (irAEs), with pneumonitis (ICI-P) being among the most severe. Early identification of high-risk patients before ICI initiation is critical for closer monitoring, timely intervention, and improved outcomes. Purpose: To develop and validate a deep learning foundation model to predict ICI-P from baseline CT scans in patients with lung cancer. Methods: We designed the Checkpoint-Inhibitor Pneumonitis Hazard EstimatoR (CIPHER), a deep learning foundation model that combines contrastive learning with a transformer-based masked autoencoder to predict ICI-P from baseline CT scans in patients with lung cancer. Using self-supervised learning, CIPHER was pre-trained on 590,284 CT slices from 2,500 non-small cell lung cancer (NSCLC) patients to capture heterogeneous lung parenchymal patterns. After pre-training, the model was fine-tuned on an internal NSCLC cohort for ICI-P risk prediction, using images from 254 patients for model development and 93 patients for internal validation. We compared CIPHER with classical radiomic models and further evaluated it on an external NSCLC cohort of 116 patients. Results: In the internal immunotherapy cohort, CIPHER consistently distinguished patients at elevated risk of ICI-P from those without the event, with AUCs ranging from 0.77 to 0.85. In head-to-head benchmarking, CIPHER achieved an AUC of 0.83, outperforming the radiomic models. In the external validation cohort, CIPHER maintained strong performance (AUC = 0.83; balanced accuracy = 81.7%), exceeding the radiomic models (DeLong p = 0.0318) and demonstrating higher specificity without sacrificing sensitivity. By contrast, the radiomic model showed high sensitivity (85.0%) but markedly lower specificity (45.8%). Confusion matrix analysis confirmed the robust classification performance of CIPHER, correctly identifying 80 of 96 non-ICI-P cases and 16 of 20 ICI-P cases. Conclusions: We developed and externally validated CIPHER for predicting future risk of ICI-P from pre-treatment CT scans. With prospective validation, CIPHER may be incorporated into routine patient management to improve outcomes.

Background. Targeted Universal Tuberculosis Testing (TUTT) may increase tuberculosis (TB) case detection by including people who are not actively seeking TB care but are at high risk of the disease. Non-invasive tongue swab (TS) testing may facilitate TUTT. We evaluated two TS testing protocols in people with HIV (PWH) tested irrespective of TB symptoms. Methods. Study staff collected Copan FLOQSwab and Medline foam swab specimens, alongside urine and sputa, from PWH, most of whom were presenting for antiretroviral therapy initiation at primary healthcare clinics in KwaZulu-Natal, South Africa. FLOQSwabs were tested by sequence-specific magnetic capture (SSMaC) with qPCR (FLOQSwab-SSMaC). Foam swabs were tested by centrifuge-sedimentation and high-volume qPCR (foam-sedimentation). Urine lipoarabinomannan was detected using LF-LAM. The extended microbiological reference standard (eMRS) comprised any positive result on Xpert Ultra and/or liquid culture of sputum. Results. We enrolled 251 participants (median age 34 years, 56% female, 67% with self-reported TB symptoms). Participants had a median CD4 count of 347 cells/ul, and 16% (40/251) had prior TB. FLOQSwab-SSMaC was 43% sensitive (13/30) and 100% specific (131/131) relative to eMRS. Foam-sedimentation was 47% (9/29) sensitive and 100% (176/176) specific. Sensitivity increased to 52% (FLOQSwab-SSMaC) and 50% (foam-sedimentation) when sputum Xpert Ultra Trace positive results were excluded from eMRS. TS was more sensitive than urine LAM, and both sample types were more sensitive when CD4 counts were below 200. Discussion. TS testing detected about half of PWH with TB and outperformed urine LAM within this population, including among PWH with low CD4 counts.

Abstract Importance Stigma and discrimination against transgender and gender-diverse people are prevalent across many settings and may contribute to substantial health disparities. Objective To synthesize global evidence on the prevalence of stigma, discrimination, and resilience among transgender (trans) and gender-diverse adults. Data Sources A systematic search was conducted in PubMed, Embase, CINAHL, Cochrane Central, LILACS, and PsycInfo for articles published between January 1, 2010 and January 2, 2023. This database search was supplemented by grey literature and secondary reference searches. Article Selection Studies were eligible if they presented primary quantitative data on prevalence of stigma, discrimination, and/or resilience among trans and gender-diverse adults (aged 18 and over), with no restrictions on study design, language, or geographic region. Data Extraction and Synthesis Two independent reviewers extracted data using standardized forms, with discrepancies resolved by consensus. The JBI Critical Appraisal Checklist for Prevalence Articles was used to assess risk of bias. Random effects meta-analysis was conducted for dichotomous prevalence measures using inverse variance weighting and logit transformation; non-dichotomous prevalence data were summarized descriptively. Main Outcomes and Measures Outcomes included prevalence estimates for various forms of stigma (anticipated, perceived, internalized, and experienced), discrimination in legal/institutional settings (housing, healthcare, employment, police/prison), and resilience. Results A total of 97 articles, with data from 72,158 unique trans and gender-diverse participants across 26 countries, met inclusion criteria. Studies showed moderate levels of anticipated stigma, perceived stigma, and internalized stigma. Meta-analyses of 36 studies provided pooled estimates of discrimination prevalence across multiple domains: 21.4% in housing (e.g., eviction, rental denial), 24.6% in healthcare (e.g., denial of care, mistreatment), 32.8% in employment (e.g., hiring bias, workplace harassment), and 39.1% in police/prison settings (e.g., profiling, mistreatment). High heterogeneity was observed across studies, reflecting regional and methodological differences. Resilience scores ranged from moderate to high, indicating variation within trans and gender-diverse communities. Conclusions and Relevance This systematic review and meta-analysis found that stigma and discrimination against trans and gender-diverse adults are pervasive globally. Variation in stigma and discrimination across settings and regions underscores the need for targeted interventions and policy reforms. Funding World Health Organization through a grant from the Elton John AIDS Foundation and the Bill and Melinda Gates Foundation.

ObjectiveTo examine whether menopausal women who initiate systemic menopausal hormone therapy (MHT) around menopause (45-60 years old) have a different risk of developing dementia than those not taking MHT. DesignSystematic review and meta-analysis of randomised controlled trials and longitudinal observational studies. Risk of bias was assessed using ROB-2 and ROBINS I-V2. Data sourcesMEDLINE, Web of Science, EMBASE, and Cochrane Library to 27 March 2026. Eligibility criteria for selecting studiesStudies which measured dementia or cognitive decline in women who initiated systemic MHT between ages 45-60 or within 5 years of menopause, compared with placebo or no MHT. Authors contacted for additional details if needed. Main outcome measuresDementia, Alzheimers disease (AD), cognitive decline. Results10 studies totalling 213,678 participants (189,525 in studies with the primary population). There was no significant increased risk in women with a uterus for all cause dementia (pooled hazard ratio (HR): 1.12; 95% CI 0.91-1.31, N=78,613, I2 = 96.9%), but increased AD risk (HR: 1.14; 95% CI 1.02, 1.29, N=134,865, I2 = 35.6%). Results were similar in sensitivity analyses including women with or without a uterus. Results for cognitive decline were variable. ConclusionsMHT initiated around the age of menopause should not be prescribed for cognition or dementia prevention. It is not protective against dementia and may increase risk slightly. The magnitude of risk was similar in AD and dementia, but the latter with larger confidence intervals. Studies which followed up individuals rather than on health records lost people to follow up. This may account for difference in cognitive decline outcomes between studies, as people with cognitive impairment and dementia are more likely not to attend. MHT prescribing should balance benefits against risks, including evidence of a small increased dementia risk. There are few high-quality studies, so further research would inform recommendations. Systematic review registration Prospero CRD420251010663 What is already known on this topic?O_LIMenopausal hormone therapy (MHT) is effective for alleviating vasomotor symptoms. Contemporary guidelines recommend treatment should be initiated for such symptoms under age 60 and or within 10 years of menopause onset. C_LIO_LIA large randomised trial on the topic found increased risk of dementia in women initiating MHT after the age of 65. C_LIO_LIIt is unknown whether initiating MHT around the age of menopause impacts the risk of dementia or cognitive decline. C_LI What this study addsO_LIThere was no evidence that taking MHT around the time of menopause decreases the risk of dementia or cognitive impairment. C_LIO_LIThey should not be prescribed for these indications. C_LIO_LIWe were able to find more studies which examine this question by contacting authors for additional data. C_LIO_LIInitiating MHT in women with a uterus around the age of menopause increased the risk of Alzheimers disease slightly, by over 10%, and there is a similar but not significant effect in the fewer studies of all cause dementia. Women with or without a uterus show similar results. C_LIO_LIWe found no significant difference shown in cognitive decline, possibly due to loss to follow up. This may be because most studies of cognitive decline follow up C_LI

Background: Although the hemagglutination inhibition (HAI) titer remains the gold standard correlate of protection against influenza, it does not fully capture the broader antibody responses that contribute to immunity. Methods: We analyzed immune responses in paired pre-infection and convalescent sera from 306 RT-PCR-confirmed A/H3N2 infections from two household studies (2014-18) in Managua, Nicaragua. Antibody responses were measured by HAI and enzyme-linked immunosorbent assays (ELISAs) against full-length hemagglutinin (HA), the HA stalk, and neuraminidase (NA). Participants were classified as HAI responders ([&ge;]4-fold HAI rise), alternate responders (no HAI rise but [&ge;]4-fold boost in [&ge;]1 ELISA), or no-response individuals (no [&ge;]4-fold rise in any assay). We compared demographic, clinical, and pre-infection antibody characteristics across these groups. We also analyzed predictors of an NA response. Results: Overall, 77% of participants had HAI seroconversion or a 4-fold rise. Among the 23% HAI non-responders, 62% had alternate antibody responses. No-response individuals had the highest pre-infection HAI and full-length HA titers (p < 0.0001), the lowest viral loads, and the fewest fever or influenza like illness (ILI) symptoms (p < 0.01). An NA response was more common among symptomatic individuals (p = 0.0483) and those with low or high baseline NA titers. Conclusions: High baseline HAI titers can limit detectable 4-fold rises and are associated with milder illness. Evaluating additional immune responses may capture a more complete picture of the host response to infection, thereby improving surveillance and informing vaccine development. Keywords: Influenza A/H3N2; Hemagglutination inhibition (HAI); Neuraminidase antibodies; symptomatic vs asymptomatic infection; correlates of protection.

BackgroundMicrosatellite stability status determination is important for prognostication and therapeutic decision making in colorectal cancer management, but the conventional methods for this assessment are not readily available, especially in low- and middle-income countries. Deep learning (DL) models have been proposed for addressing this problem; however, potential computational cost due to model complexity and inadequate explainability may limit their adoption in low-resource settings. This study explored the potential of explainable lightweight models for detection of microsatellite instability in colorectal cancer. MethodsDL models were trained using a public dataset of colorectal cancer histology images and then used to classify a set of test images into one of two classes: microsatellite instability or microsatellite stability. The models were compared for efficiency. Gradient-weighted class activation mapping (Grad-CAM) was used to interpret the models decision making. ResultsThe simpler convolutional neural network (CNN) trained from scratch had modest performance (accuracy=0.757, area under receiver-operating characteristic curve [AUROC]=0.840). With an attention mechanism added, these values increased, but specificity and sensitivity reduced. Pretrained models performed better than the ones trained from scratch, and EfficientNet_B0 had the best balance of high performance and low computational requirements (accuracy=0.936, AUROC=0.990, negative predictive value=0.923, specificity=0.953, 4,010,000 trainable parameters, 0.38 gigaFLOPs). However, a simple CNN model with attention mechanism had the best interpretability based on Grad-CAM. ConclusionThis study demonstrated that DL models that are lightweight when compared to previously proposed ones can be useful for colorectal cancer microsatellite instability screening in resource-limited settings while balancing performance and computational efficiency.

Introduction: Modeling when influenza epidemics typically occur can help countries optimize surveillance, time clinical and public health interventions, and reduce the burden of influenza. Methods: We used influenza virus detections reported during 2011-2024 by 180 countries to the Global Influenza Surveillance and Response System, excluding COVID-19 pandemic impacted years (2020-2023). We analyzed data by calendar year (week 1-52) or shifted year (week 30-29) time windows, based on when most influenza detections occurred in each country. For countries with sufficient data, we computed generalized additive models (GAMs) of each country's weekly influenza-positive tests to smooth and impute time series distributions. From these GAMs, we calculated each country's normalized weekly influenza burden. Country-specific normalized time series were grouped using hierarchical k-means clustering reducing the Euclidean distance between time series within clusters. We calculated cluster-specific GAMs to estimate average seasonal timing. Countries without sufficient data were assigned to a cluster based on population-weighted latitudinal distance to a cluster's mean latitude. Results: We identified five clusters, or epidemic zones, from 111 countries with sufficient data. The influenza burden in epidemic zones A and B was consistent with a northern hemisphere pattern, with most influenza detections occurring during October-April (A) and September-March (B), while epidemic zones D and E were characterized by southern hemisphere-like seasonal timing, with most influenza burden occurring during May-November. Epidemic zone C had most influenza burden occurring during September-March; most countries assigned to this cluster were in the tropics. Conclusion: Epidemic zones may serve as a useful tool to strengthen and optimize influenza surveillance for global health decision-making (e.g., during vaccine strain composition discussions) and to guide country preparedness efforts for seasonal influenza epidemics, including the timing of enhanced surveillance, as well as the procurement and delivery of vaccines and antivirals.

ObjectivesTo estimate current, and 5- and 10-year projected, number of cases of cancer per year in transgender and gender diverse (TGD) people in England, overall and by tumour type, accounting for uptake of gender affirming care (GAC). DesignPopulation-based epidemiological modelling study using an age-stratified Monte Carlo simulations approach and the NORDPRED method for predictions. SettingModels estimating cancer case numbers for TGD people in England based on publicly available 2023 cancer surveillance data and survey-based 2025 GAC access, and predicted at 5 and 10 years hence. ParticipantsTGD people aged 15 years and above. Main outcome measuresPrimary cancer cases per year overall, by gender, age group, tumour type, and current and planned GAC. ResultsThe estimated TGD population size in England is 441547 (95% uncertainty interval (UI) 429207- 452890). Total cases per year of cancer in TGD people is expected to be 966 (95% UI 882-1069) excluding non-melanoma skin. Most cases are expected to occur in people aged 60-64. The top 5 expected cancers in TGD people are breast (19%, n = 187, 95% UI 149-241), colorectal (12%, n = 117, 95% UI 106-129), lung (11%, n = 108, 95% UI 96-122), melanoma (7.1%, n = 69, 95% UI 64-74) and urinary (6.2%, n = 60, 95% UI 54-67). Total cases of cancer in TGD people are estimated to be 1740 (95% UI 1584-1934) in 5 years and 2258 (95% UI 2066-2507) in 10 years (excluding non-melanoma skin). If TGD people were able to access their planned level of GAC, this would reduce these figures to 1555 (95% CI 1386-1766) and 2012 (95% CI 1797-2282) respectively. ConclusionsThis study provides prediction of cancer cases in TGD people in England, supporting the planning of service provision and training. This is vital, as with increasing disclosure, and long wait times for GAC, cancer cases in TGD people are predicted to increase. Summary BoxesO_ST_ABSWhat is already known on this topicC_ST_ABSThe annual number of cases of cancer in transgender and gender diverse (TGD) people in England is currently unknown as gender incongruence is not collected as part of the National Cancer Registration and Analysis Service. Some gender-affirming care (GAC) interventions are known to modulate cancer risk. Use of testosterone and chest reconstruction for transmasculine people is known to reduce their incidence of breast cancer compared to cisgender women. Use of oestradiol alongside medical or surgical androgen suppression has been shown to reduce the incidence of prostate cancer in transfeminine people while increasing their risk of breast cancer, compared to cisgender men. What this study addsThis study found that there are likely to be approximately 966 cases of cancer (excluding non-melanoma skin) in TGD people per year in the UK. Though total annual cases of cancer in TGD people are expected to be 2258 in 10 years, improved access to gender-affirming care could reduce total cases to 2012 (a 11% reduction). These figures provide additional justification for funding to improve access to GAC via the National Health Service (NHS), as well as for training on the oncological needs of this population.

BackgroundLynch syndrome (LS) is a cancer susceptibility syndrome caused by germline pathogenic variants in DNA mismatch repair (MMR) genes. Due to increased risk of colorectal cancer (CRC), enhanced colonoscopic surveillance is recommended for heterozygote MMR-carriers. ObjectiveUsing a registry of English LS patients linked to digital National Health Service records, we aimed to assess adherence of MMR-carriers to national surveillance guidelines, and to determine the impact of surveillance on CRC incidence and mortality. DesignWe described the frequency of colonoscopies in 4,732 MMR-carriers and used logistic regression to determine predictors of surveillance adherence. For MMR-carriers with a record of surveillance and those without, we: estimated age-specific annual CRC incidence rates (AS-AIRs) and cumulative lifetime risks, assessed for stage-shift by comparing CRC stage distributions and stage-specific AS-AIRs, and estimated risks of death from CRC and any cause using Kaplan-Meier methods and Cox Proportional Hazards regression. ResultsSurveillance at a mean interval of [&le;] 3 years (n=3028) was associated with a decrease in CRC-specific and all-cause mortality, without an associated change in total CRC incidence, even after multivariate adjustment. No strong evidence of stage-shift was observed. Colonoscopic surveillance at a mean interval of [&le;] 2 years (n=1569) was associated with an increase in total CRC incidence. Incidence of early-stage cancers was also higher, with no corresponding decrease in late-stage cancers, which may reflect the short follow-up period or the impact of overdiagnosis. ConclusionThe observed reduction in all-cause mortality amongst regularly-surveilled MMR-carriers may indicate an impact of surveillance on CRC-specific mortality, though in the context of a non-randomised study likely reflects the influence of selection bias. KEY MESSAGES OF ARTICLEO_ST_ABSWhat is already known on this topicC_ST_ABSRegular surveillance colonoscopy is recommended in Lynch syndrome, though evidence to support this remains mixed. We searched PubMed for articles published from inception to 01/05/2024 using the terms "Lynch syndrome", "HNPCC", "colonoscopy", "sigmoidoscopy", "surveillance", and "screening". We found one controlled trial and several small analytical studies dating from the early 2000s which compared surveilled and non-surveilled populations and found surveillance to be associated with reduced colorectal cancer (CRC) incidence and improved survival. More recent longitudinal observational studies, most without comparator groups, found a high incidence of CRC in LS populations despite being resident in countries where surveillance was recommended. A small number of studies directly assessed time since last colonoscopy against CRC incidence and stage with mixed findings. Finally, cross-sectional comparisons between countries of CRC incidence rates and surveillance interval recommendations found no relationship between the two1,2. What this study addsHere, we conduct an observational cohort study on a large national cohort of MMR germline pathogenic variant (GPV) carriers (MMR-carriers) in England (n=4,732), comparing CRC incidence and mortality in individuals with a record of regular surveillance to those without. Through linkage of the English National Lynch Syndrome Registry to Hospital Episodes Statistics data, we are uniquely able to study a comprehensive national population of MMR-carriers and identify the dates on which colonoscopies were undertaken over time, allowing assessment of adherence to national surveillance guidelines and the impact this has on CRC outcomes. Notably, receipt of regular colonoscopy was strongly associated with deprivation as well as ethnicity. The results show that regular surveillance at an average interval of 3 years (or less) is not associated with a reduction in CRC incidence when compared to less frequent surveillance, but an apparent decrease in both CRC-specific and overall mortality is observed, even after adjustment for confounding variables. Conversely, regular surveillance at an average interval of 2 years (or less) is associated with an increase in CRC incidence when compared to less frequent surveillance, which may suggest increased diagnosis of early-stage cancers or, due to the absence of a reduction in late-stage cancers, overdiagnosis. The observed impact of surveillance on overall mortality may demonstrate the impact of surveillance on CRC-specific mortality, or, in the context of an observational (non-randomised) study, indicate that the results are subject to selection bias. How this study might affect research, practice, or policyEvidence for the benefit of surveillance colonoscopy remains mixed. Whilst polypectomy would be anticipated to prevent CRC development (thus reducing CRC incidence), several studies have observed increased frequency of CRCs in MMR-carriers undergoing frequent surveillance colonoscopy, which may reflect overdiagnosis. The selection bias inherent to observational studies of surveillance renders mortality outcomes challenging to interpret. Randomised controlled trials of colonoscopic surveillance in MMR-carriers are required for effectiveness of this intervention to be accurately assessed. Given ethical and feasibility challenges, randomised controlled trials might be complemented by quasi-experimental designs using advanced observational methods for assessing effectiveness.

Objectives Concerns about COVID-19 were a key driver of infection-prevention behaviour during the pandemic. The aim of this study was to gain an in-depth longitudinal understanding of the type and frequency of concerns experienced throughout the first two years of the COVID-19 pandemic. Design Content analysis of qualitative descriptions provided in a prospective longitudinal online survey as part of the COVID-19 UK Public Experiences (COPE) Study. Method At baseline (March/April 2020), when the UK entered its first national lockdown, 11,113 adults completed the COPE survey. Follow-up surveys were conducted at 3, 12, 18 and 24 months. Participants were recruited via the HealthWise Wales research registry and social media. Baseline surveys collected demographic and health data, and all waves included an open-ended question about COVID-19 concerns. Content analysis was used to identify the type and frequency of concerns at each time point. Results A total of 41,564 open-text responses were coded into six categories: personal harm (n=16,353), harm to others (n=11,464), social/economic impact (n=6,433), preventing transmission (n=4,843), government/media (n=1,048), and general concerns (n=1,423). The proportion of respondents reporting any concern declined from 75.3% at baseline to 65.8% at 24 months. Over time, concerns about personal harm increased (baseline 41.8% vs. 24-months 52.7%) whereas concerns about harm to others decreased (baseline 48.5% vs. 24-months 28.6%). Concerns about harm were also expressed in relation to clinical vulnerability, lack of trust in government/media, and perceived lack of adherence by others. These were balanced against concerns about wider social and economic impacts of restrictions. Conclusions Public concerns about COVID-19 evolved substantially over the first two years of the pandemic, reflecting changing perceptions of risk and responsibility. Monitoring concerns longitudinally is vital to help guide effective communication and behavioural interventions during future pandemics.

BackgroundChlamydia trachomatis, Neisseria gonorrhoeae, and Trichomonas vaginalis are curable sexually transmitted infections (STIs) associated with adverse birth outcomes. Most infections are asymptomatic. Whether antenatal STI screening improves birth outcomes remains uncertain. MethodsIn a randomized three-group trial in South Africa, pregnant women aged 18 years or older were assigned before 27 weeks gestation to: (1) screening and treatment for Chlamydia trachomatis, Neisseria gonorrhoeae, and Trichomonas vaginalis at enrollment, with tests-of-cure (One-Time Screening); (2) screening and treatment at enrollment, repeated at 30 to 34 weeks (Two-Time Screening); or (3) Standard-of-Care (Syndromic management). The primary outcome was a composite of preterm birth (<37 weeks gestation) or low birthweight (<2500 g), analyzed in the modified intention-to-treat population of participants with live births. Components of the composite outcome were evaluated individually as the main secondary outcomes. The study was registered with ClinicalTrials.gov, NCT04446611. FindingsOf 2247 enrolled participants, 1910 had live births. The composite outcome occurred in 22{middle dot}9% of the One-Time Screening group (risk ratio [RR] 0{middle dot}99; 95% confidence interval [CI] 0{middle dot}81-1{middle dot}21), 20{middle dot}6% of the Two-Time Screening group (RR 0{middle dot}89; 95% CI 0{middle dot}72-1{middle dot}09), compared with 23{middle dot}2% of the Standard-of-Care group. Preterm birth occurred in 18{middle dot}9% of the One-Time Screening group (RR 1{middle dot}00; 95% CI 0{middle dot}80-1{middle dot}26), 14{middle dot}5% of the Two-Time Screening group (RR 0{middle dot}77; 95% CI 0{middle dot}60-0{middle dot}99), and 18{middle dot}8% of the Standard-of-Care group. Low birthweight occurred in 14{middle dot}1% of the One-Time Screening group (RR 1{middle dot}10; 95% CI 0{middle dot}83-1{middle dot}46), 12{middle dot}9% of the Two-Time Screening group (RR 1{middle dot}01; 95% CI 0{middle dot}76-1{middle dot}35), and 12{middle dot}8% of the Standard-of-Care group. InterpretationNeither screening strategy for Chlamydia trachomatis, Neisseria gonorrhoeae, and Trichomonas vaginalis reduced the primary composite outcome of preterm birth or low birthweight, or low birthweight alone. The Two-Time antenatal STI screening strategy, however, reduced preterm birth by 23%.

Introduction Improved diagnostics are needed for people at risk of tuberculosis, especially adolescents. Tongue swab (TS) molecular testing has emerged as a promising strategy for tuberculosis diagnosis. We evaluated diagnostic accuracy and acceptability of Xpert MTB/RIF Ultra (Xpert) using TS samples for tuberculosis detection among adolescents. Methods We conducted a cross-sectional diagnostic accuracy study with consecutive recruitment in Vietnam. Adolescents aged 10-19 who were recommended to undergo investigation for tuberculosis and had not received tuberculosis treatment in the past years were eligible. Participants provided TS and sputum samples and completed a structured survey regarding sampling experiences. TS was tested on Xpert, with sputum tested on Xpert and liquid culture. We utilised a composite reference standard of a positive result on sputum Xpert or sputum culture to define disease status. Sensitivity, specificity, and diagnostic yield were calculated for TS Xpert. Results From July to December 2025, we enrolled 225 adolescents from Can Tho and An Giang provinces in southern Vietnam. Fewer than half (96/225, 43%) the participants exhibited a tuberculosis -like symptom, and the majority (157/225, 70%) were close contacts of a person recently diagnosed with tuberculosis. TS were collected from all adolescents, while 116 (52%) could provide mucopurulent sputum. Tuberculosis prevalence was relatively low (12/225, 5.3%). TS Xpert sensitivity (90% CI) and specificity (90% CI) were 58.3% (35.6, 78.0) and 99.5% (97.9, 99.9), respectively. Diagnostic yield among all diagnosed was 58.3% (7/12). TS sampling was highly acceptable to adolescents; the short time and simplicity of collecting TS were considered favourably. Conclusions The sensitivity and diagnostic yield of TS Xpert was relatively low among adolescents recommended for tuberculosis investigation, which includes asymptomatic individuals who may not provide high quality sputum. Specificity was excellent, and everyone could provide a TS. TS high acceptability indicates it remains a promising sample for diagnostic algorithms.

BackgroundIn England, the burden of respiratory infections varies by ethnicity, contributing to health inequalities, but the role of additional demographic factors remains underexplored. We quantified how differences in social mixing and demographic characteristics between ethnic groups cause inequalities in transmission dynamics. MethodsWe analysed the association between the ethnicity and the number of contacts of 12,484 participants in the 2024-2025 Reconnect social contact survey, using a negative binomial regression model. We simulated respiratory pathogen epidemics using a compartmental model stratified by age, ethnicity, and contact levels, at a national level and in major cities in England. FindingsAfter adjusting for demographic variables, participants of Black and Mixed ethnicities had more contacts than those of White ethnicity (rate ratios (RR): 1.18 [95% Credible Interval (CI): 1.11-1.26], and 1.31 [95% CI: 1.14-1.52]). Participants of Asian ethnicity had fewer contacts (RR: 0.85 [95% CI: 0.79-0.91]). In national-level simulations, individuals of White ethnicity had the lowest attack rates due to demographic differences and mixing patterns. Local demographic structures changed simulated dynamics: attack rates in individuals of Black and Mixed ethnicities were approximately double those of White ethnicity in Birmingham, but less than 60% higher in Liverpool. InterpretationDemographic characteristics and mixing patterns create inequalities in transmission dynamics between ethnicities, while local demographic characteristics and pathogen infectiousness change the expected relative burden. To ensure mitigation strategies are effective and equitable, their evaluation must explicitly account for inequalities arising from local context. FundingMedical Research Council, National Institute for Health and Care Research, Wellcome Trust Research in context Evidence before this studyWe searched PubMed for population-based studies quantifying differences in respiratory infections between ethnic groups, up to 1 April 2026, with no language restrictions. Keywords included: (respiratory pathogens OR influenza OR COVID-19) AND (ethnic* OR race) AND (inequ*) AND (compartmental model OR incidence rate ratio OR hazard ratio). We excluded studies that focused on non-respiratory pathogens (e.g. looking at consequences of COVID-19 on incidence of other pathogens). A population-based cohort study showed that influenza infection risk was higher in South Asian, Black, and Mixed ethnic groups compared to White ethnicity in England. Another population-based cohort study highlighted that during the first wave of COVID-19 in England, the South Asian, Black, and Mixed ethnic groups were more likely to test positive and to be hospitalised than the White ethnic group. Census data in England showed that the distributions of age, household size, household income and employment status differed between ethnic groups, and the recent Reconnect social contact surveys highlighted the impact of each demographic factor on the participants number of contacts. Added value of this studyOur study shows that social contact patterns, mixing, and demographic structure all lead to unequal infection risk between ethnic groups in respiratory pathogen epidemics. Using the largest available social contact survey in England, we show that both the average number of contacts and the proportion of high-contact individuals varied by ethnic group, even after adjusting for participants demographics. These differences, together with mixing patterns and age structure, led to lower expected incidence among individuals of White ethnicity than in all other ethnic groups in simulated outbreaks. The level of inequality between ethnic groups changed when we used different values of pathogen transmissibility. Finally, as ethnic composition and population structure differ between cities in England, our results show differences in expected inequalities at a local level. Implications of all the available evidenceInequalities in infection risk between ethnic groups are context- and pathogen-dependent. They arise from both local population structure and contact patterns. Detailed information on mixing between groups and population structure is needed to accurately measure group-specific infection risk. These findings indicate that public health interventions based only on national-level estimates conceal regional variation in risk and may ultimately increase inequalities. Public health interventions need to be tailored to local contexts to be equitable and effective. Finally, our findings provide a foundation for understanding the progression from infection-risk inequalities to disparities in disease presentation and clinical outcomes.