Journal of Medical Entomology

Elucidating the biological and molecular mechanisms that govern male fertility and mating behavior in mosquitoes is critical for optimizing genetic and sterile insect technique-based vector control strategies. Here, we examined age-related changes in male reproductive capacity in Anopheles culicifacies, using female egg output as an indirect indicator of male fertility. Our results demonstrated that male reproductive age follows a non-linear pattern of fertility. Morphometric analysis from emergence to day 13 post-eclosion revealed a strong correlation between seminal vesicle capacity and female fecundity, suggesting that age-dependent gonadal development directly influences reproductive potential. At the molecular level, we identified AcLITAF6 as a key regulator of male reproductive homeostasis. RNAi-mediated knockdown of AcLITAF6 impaired apoptosis-associated and phagocytic clearance, reduced sperm viability, and decreased female productive outcomes. Conclusively, we reveal a previously unrecognized role of LITAF in sperm quality control and male reproductive fitness, highlighting AcLITAF6 as a potential target for mosquito population suppression strategies.

Circadian clocks enable mosquitoes to anticipate recurring environmental variations and coordinate behaviors critical for survival and disease transmission, such as locomotion, reproduction, host-seeking, and blood-feeding, with times of day when performance is maximal. In Aedes aegypti, locomotor activity follows a robust diurnal rhythm shaped by endogenous circadian clocks and environmental cues, among which light has been shown to be the primary source of temporal information. While early studies established the role of light in regulating locomotor activity, behavior, oviposition and pupation, it remains unclear which features of a light cycle drive changes in circadian rhythms. This question is increasingly relevant as Ae. aegypti is frequently exposed to artificial and dynamic lighting conditions in urban environments. Here, we investigated how transient changes in light schedules influence circadian rhythms in locomotor activity by systematically manipulating the timing, duration, and direction of light exposure. Using a high-throughput assay, we tested over 1900 individuals, including wild-type and timeless knockout mutants, and showed that a single day of al tered lighting is sufficient to induce robust phase shifts, with no evidence of masking effects. A 6-hour light pulse was sufficient to re-entrain mosquitoes regardless of the timing of the pulse, and phase shifts were primarily driven by the offset time of the light pulse, indicating that light-offset acts as a major zeitgeber. Together, these findings challenge conventional assumptions about the timescale of circadian synchronization and highlight the remarkable plasticity of mosquito behavior in response to anthropogenic light. Eventually, these effects could explain the rapid adaptation of the species to urban environments and have potential consequences for disease transmission dynamics.

Background Trypanosoma cruzi, the causative agent of Chagas disease, is subdivided into distinct genetic groups known as Discrete Typing Units (DTUs), each with distinct genetic traits that influence epidemiology and transmission dynamics. Several triatomine species serve as potential vectors of T. cruzi in the United States. However, despite the growing number of Chagas disease cases in the country, little is known about the genetic diversity and population structure of T. cruzi in natural vector populations. Methodology/Principal Findings We applied a multilocus metabarcoding approach to improve DTU resolution and characterize the genetic diversity and structure of T. cruzi in triatomines collected across five states of the southern United States. Five single-copy nuclear markers and one mitochondrial marker were amplified and processed by high-throughput sequencing to assess genetic diversity. We recovered 35 nuclear and 15 mitochondrial haplotypes from 70 infected specimens. Overall, genetic diversity was low ({pi} < 0.01 at all nuclear loci), with DTUs TcI and the North American lineage of TcIV detected, TcI being the most prevalent. Geographic structuring was particularly evident in TcI strains, which exhibited a distinctive haplotype profile in Florida populations, potentially linked to the recently revalidated vector species Triatoma ambigua. Mitochondrial introgression from TcIV into TcI suggests inter-DTU genetic exchange in these populations. Multiple haplotypes within individual insects detected across single-copy nuclear markers, support multiclonal infection as common feature of T. cruzi in natural vectors. Conclusions/Significance These findings provide new insights into the genetic landscape and evolution of T. cruzi in the United States. Evolutionary connectivity through mitochondrial introgression and frequent multiclonality highlights the importance of deep sequencing approaches for resolving T. cruzi genetic diversity, with direct implications for understanding for transmission dynamics, disease monitoring and control.

Between 2017 and 2024, routine diagnostics surveillance in Guinea detected several confirmed viral hemorrhagic fever (VHF) cases among febrile patients. To assess exposure to Lassa virus and other viral pathogens, we conducted a retrospective cross-sectional seroprevalence study in Forest Guinea (Gueckedou and N'Zerekore). Lassa virus seroprevalence was 56.0% in the Gueckedou study group and 29.8% in the N'Zerekore study group. Seropositivity increased with age in both study groups, suggesting cumulative exposure. Samples from Gueckedou laboratory were also tested for other pathogens, and antibodies against Marburg virus (5.8%), Zika virus (5.4%) and Crimean-Congo haemorrhagic fever virus (1.2%) were detected.

Background Dengue is a major public health challenge, and predictive models are crucial for early warning systems. However, many current modeling practices rely exclusively on climatic factors or employ complex algorithms that lack the interpretability needed for informed public health decision-making. To address these shortcomings, we developed and validated a multidimensional, interpretable statistical model to predict monthly dengue incidence. Methodology/Principal Findings We used a Generalized Linear Mixed Model (GLMM) with a Negative Binomial distribution to analyze 14 years (2010-2023) of spatiotemporal data from 37 municipalities in Huila, Colombia, an endemic region. The model integrates non-linear and lagged effects of climatic, demographic, and socioeconomic factors. The final model underwent rigorous external validation on an independent test set (2021-2023). Our model demonstrated high predictive discrimination (R2 = 0.743, Spearman's {rho} = 0.657), accurately capturing the timing of epidemic outbreaks. Key findings include the identification of an optimal thermal window for transmission at 27-28{degrees}C, a threshold effect for precipitation above 800 mm, and a saturation dynamic in outbreak autocorrelation. Conclusions/Significance This mechanistically-informed statistical approach provides a robust and transparent tool for epidemiological surveillance, successfully balancing high predictive performance with the explanatory power needed for effective, data-driven public health interventions.

Introduction Miltefosine is the only approved oral antileishmanial agent, but its use in women of childbearing potential (WOCBP) is restricted due to preclinical teratogenicity. Current labeling recommends contraception during treatment and for at least five months thereafter, based solely on its long terminal elimination half-life. This study re-evaluated the required contraceptive duration using an exposure margin-based approach. Methods Virtual populations were generated from anthropometric data of 382 Indian, 4,462 Eastern African, and 4,019 Brazilian WOCBP with leishmaniasis. Published population pharmacokinetic models were used to simulate miltefosine exposure following 14-42-day regimens for visceral leishmaniasis (VL), post-kala-azar dermal leishmaniasis (PKDL), and cutaneous leishmaniasis (CL). A developmental safety exposure threshold was derived from the rat no-observed-adverse-effect level (0.6 mg/kg/day for 10 days) and adjusted using a 10-fold safety margin. Contraceptive durations resulting in median residual post-contraception exposure (AUCEOC-{infty}) below this threshold were considered supportive of contraceptive discontinuation. Results The developmental safety exposure threshold was estimated at 2.5 mg{middle dot}day/L. Despite pharmacokinetic differences across geographical regions and disease manifestations, required minimum contraceptive durations were consistent: three months from treatment initiation for the 14-day regimen, four months for 21- and 28-day regimens, and five months for the 42-day regimen. For the 14-day regimen, a single dose of a long-acting injectable contraceptive administered at treatment initiation would provide sufficient coverage. Conclusion An exposure margin-based approach supports shorter contraceptive durations than current recommendations. For the 14-day VL regimen, three months of contraception may provide a practical alternative to current labeling.

Background: The biological mechanism linking rainfall with leptospirosis transmission is well established, but rigorous quantitative evidence for the insular Caribbean remains scarce, limited mostly to descriptive reports of post-hurricane outbreaks. We aimed to quantify the association between rainfall and leptospirosis incidence in the Dominican Republic, where leptospirosis is endemic, between 2012 and 2026 using a distributed-lag approach. Methods: We conducted an ecological time-series study complemented by a province panel with fixed effects. Case data (5,412 valid cases) were obtained from the national surveillance system (SIP-0276FA51); rainfall data were obtained from 15 INDOMET rain gauge stations across 13 provinces (2000 to 2026). We calculated the cross-correlation function between lagged monthly rainfall (0 to 6 months) and case counts, fitted a negative binomial distributed-lag regression model (lags 0 to 3 months) adjusted for seasonality and trend, triangulated findings with a 13-province fixed-effects panel, compared four rainfall exposure metrics, assessed extreme-rainfall threshold sensitivity, and estimated the population attributable fraction (PAF) with a parametric bootstrap. Results: The rainfall-case association peaked at a 1-month lag (r = 0.551; 95 % CI 0.437-0.647; p < 0.001) and remained significant through 3 months. In the distributed-lag model, all four lags were independently significant, with the 1-month lag showing the strongest effect (incidence rate ratio [IRR] = 1.156 per additional 50mm; 95 % CI 1.090-1.226; p < 0.001). The province panel yielded an almost identical 1-month lag effect (IRR = 1.147; 95 % CI 1.127-1.167). Rainfall above the historical 90th percentile increased case risk the following month (rate ratio = 1.95), with effect magnitude increasing monotonically with threshold stringency. An estimated 28.2 % (95 % CI 19.0-36.6 %) of cases were attributable to rainfall above the recorded historical minimum. Conclusions: Rainfall is a robust, consistent predictor of leptospirosis incidence in the Dominican Republic, with the strongest association observed at a 1-month lag and a lag pattern broadly consistent with findings from distributed-lag studies in Thailand and the Philippines. These findings, which to our knowledge constitute the first formal quantification of this association for the insular Caribbean, provide an evidence base for rainfall-linked early-warning systems, with the strongest signal at approximately one month and elevated risk extending through three months after rainfall.

Background Floods are among the most devastating natural disasters worldwide and are increasingly associated with adverse mental health outcomes, particularly Post-Traumatic Stress Disorder (PTSD). In December 2023, Hanang District in northern Tanzania experienced catastrophic mud floods that resulted in extensive loss of life, destruction of property, displacement of households, and disruption of livelihoods. While emergency humanitarian responses focused primarily on physical needs, limited evidence exists regarding the long-term psychological consequences among survivors. Therefore, this study aimed to determine the patterns of PTSD manifestations and assess cognitive factors associated with PTSD symptoms among flood victims in Hanang District, Tanzania. Methods A community-based cross-sectional study was conducted among 360 flood victims one year after the disaster. PTSD symptoms were assessed using the PTSD Checklist for DSM-5 (PCL-5). Descriptive statistics summarized PTSD severity, while chi-square tests and regression analyses examined associations between socio-demographic characteristics and PTSD manifestations. Cognitive factors were assessed based on participants' exposure to traumatic experiences and perceptions of traumatic events. Results The mean PCL-5 score was 39.2 (SD = 20.6), indicating a high burden of psychological distress. Approximately 45% of respondents had severe PTSD symptoms (PCL-5 [&ge;]45), while another substantial proportion demonstrated moderate symptom severity. PTSD manifestations varied significantly by geographical location (p < 0.001), household income (p = 0.011), and marital status (p = 0.002). Age positively predicted PTSD severity ({beta} = 0.019, p = 0.001), whereas household income negatively predicted symptom severity ({beta} = -0.297, p = 0.001). Exposure to natural disasters constituted the predominant cognitive factor, with 45% directly experiencing the flood and 38.3% witnessing the event. Exposure to secondary traumatic experiences through witnessing or learning about violent events was also common. Cognitive trauma exposure demonstrated a significant association with PTSD symptoms ({chi}2, p < 0.001). Conclusion PTSD remains highly prevalent among flood survivors in Hanang district. Both direct and indirect trauma exposure significantly contributed to PTSD manifestations. Comprehensive disaster recovery programmes should integrate trauma-focused psychological services, cognitive behavioural interventions, routine PTSD screening, and community-based psychosocial support alongside socioeconomic recovery initiatives.

Background: Snakebite envenoming is a major cause of preventable death and disability in the Brazilian Amazon, where long distances, sparse roads, and dependence on river transport delay access to antivenom. We developed location-allocation models to identify community health centers that could strategically expand access to antivenom in Amazonas State, Brazil. Methodology/Principal Findings: We conducted an ecological geospatial study using a 2025 WorldPop population surface, locations of existing and candidate health facilities, and a multimodal road-and-river transportation network derived from OpenStreetMap and HydroSHEDS. Population demand was represented by 7,065 populated centroids, including 1,586 within Indigenous territories. We applied a maximize-coverage algorithm with a six-hour travel-time threshold. Two models were developed: one for Amazonas excluding Manaus and one for populations living in Indigenous territories. Both models began with 77 facilities already providing antivenom and progressively added candidate community health centers until coverage gains plateaued. The plateau occurred at 110 facilities, corresponding to 33 additional centers. In the model excluding Manaus, this configuration covered 1,118,831 people, or 75.11% of the target population; 87.61% of those covered could reach care within three hours. In Indigenous territories, coverage increased from 50.55% to 69.50%, reaching 50,434 people, of whom 81.39% were within three hours of care. Validation used 3,595 snakebite notifications from the 30 highest-burden municipalities in the Brazilian Notifiable Diseases Information System during 2023-2025. The median proportion reaching care within six hours was 40.81% in observed data and 72.17% in model estimates. Conclusions/Significance: Strategically equipping 33 additional existing community health centers could substantially expand timely access to antivenom, particularly in rural and Indigenous areas. Location-allocation modeling that incorporates river transportation can support evidence-based decentralization of time-sensitive health services in geographically complex settings.

All primary healthcare centers owned by the Ugandan government in the Western Region of Uganda were submitted to a questionnaire concerning current availability of POCT from the Essential diagnostic List 2 part 1a and 1b, and the African laboratory inventory done by African Society of Laboratory Medicine and AfricaCDC. The data from the questionnaire was then linked to open source geodata provided by TomTom, and population data to calculate and visualize the accessibility of captured POCT. Findings: Availability of POCT Malaria is almost 100%, HIV 68-90%, and >30% for a majority of the POCT in the EDL-2 panel. 90% of the population in Western Region live within 1 hour by car from most of the essential POCT. Figures in the complementary web-based application visualize the accessibility of POCT for Western Uganda. Diagnostic deserts are visualized. Interpretation: Access to POCT at primary health care facilities in western Uganda has expanded substantially over the past decades. The geo-mapping tool presented here could inform policy decisions on strengthening diagnostic capacity at the national, regional, and provincial level. Funding: Swedish Research Council and Infravis All supplementary materials and a preprint of this submission are available on our OSF repository https://osf.io/j7puk/.

Background: Ebola virus disease is a life-threatening illness caused by the Ebolavirus, with symptoms manifesting two to twenty-one days after infection. Although Uganda has faced multiple Ebola outbreaks, many patients survive only to encounter persistent challenges. Therefore, this study explored the post-discharge experiences of survivors following the 2022 Ebola Virus Disease outbreak in Uganda. Methods: An exploratory qualitative study comprising of in-depth participant interviews was conducted at Mubende Regional Referral Hospital in central Uganda. Interviews were face-to-face and data were analyzed manually by inductive content analysis. Ten male and female participants were Ebola Virus Disease survivors in Mubende district who had lived in the community for at least six months post-discharge from the Ebola Treatment Unit. Results: Four themes emerged: (i) Psychosocial Burdens and Social Exclusion, (ii) Economic Hardship and Loss of Financial Stability, (iii) Chronic Physical and Health Burdens Post-Recovery and (iv) Rebuilding Lives: Psychological, Social, and Medical Pathways to Recovery. Survivors faced significant emotional burdens such as survivor guilt, grief, trauma from loss, and anxiety about transmission risks. They experienced social isolation, stigma, and discrimination, which often led to their exclusion from community activities. Financially, they struggled with debt and the loss of livelihoods, compounded by ongoing health issues. Additionally, survivors endured chronic physical complications, including pain and fatigue, which hindered their recovery. Despite these challenges, survivors sought psychological, social, and medical pathways to recovery, including confirmation of their recovery, support from family and organizations, and health maintenance practices. Supportive medical care and community assistance were crucial in their physical and emotional rehabilitation. Conclusion: Ebola Virus Disease survivors in Uganda face significant psychosocial, health, social, and economic challenges post-discharge. The findings highlight the critical need for comprehensive medical and community-based support systems to aid survivors' recovery and well-being. Further research on long-term neurological effects and community reintegration programmes is needed to inform targeted interventions that support Ebola survivors and reduce stigma and discrimination.

The 17th Ebola outbreak in the Democratic Republic of the Congo, announced on 15 May 2026, was attributed to Bundibugyo ebolavirus (BDBV). Although case isolation is the main control strategy, its effectiveness is compromised when patients escape isolation facilities before recovery. Between 14 May and 17 June 2026, 175 individuals reportedly left isolation facilities without formal discharge across Ituri Province. We assessed how this "isolation leakage" affects community transmission. We refined the SEIHFR framework to distinguish undetected community infections, detected but not-yet-isolated cases, isolated individuals, leakage, funeral-associated transmission, and removals. Using Bayesian inference, we fitted the model to daily Ituri surveillance data, escapee counts, and isolation census records. We estimated the leakage rate, reporting and detection probabilities, and the transmission rate, while fixing other parameters based on the BDBV literature. The model reproduced confirmed cases, deaths, discharges, and escapees. We estimated R_0=3.67 (95% HDI: 2.0-5.7), a leakage rate of {rho} {approx} 0.034 day^-1 (0.022-0.051), and high contact-tracing-driven detection (p_d {approx} 0.91-0.99). Leakage increased the detection-dependent reproduction number [R](p_d) from approximately 3.2 to above 5. Eliminating leakage reduced cumulative infections by about one-third, from 1,120 to 764, while the minimum detection level required for control increased from p_d [&ge;] 0.73 without leakage to p_d [&ge;] 0.87 at the fitted leakage rate. Shortening time to isolation prevented the most infections (73.4%; 59-84), followed by reducing leakage (29.7%; 14-52) and re-isolating escapees (12.6%; 6-24). Delaying leakage reduction until week 4 reduced its benefit from about 27% to below 2%. Isolation leakage represents a major transmission pathway that has until now gone largely unmeasured. While rapid initiation of isolation is highly beneficial, it cannot compensate for permeable isolation; therefore, early, community-driven efforts to control leakage, embedded within a multilayered response, are critical.

Background: Community case management has been scaled up nationally in Zambia over the last decade. However, there is limited evidence on how this nationwide implementation has affected febrile patients' access to malaria diagnosis and treatment in Zambia. Methodology: This study analyzed four rounds of Malaria Indicator Survey (MIS) data (2012-2021) to evaluate: 1) proportion of all-ages individuals with fever who sought treatment from a formal provider, 2) proportion of individuals going to CHWs over time, among those who sought treatment at a formal provider, 3) time duration between fever onset and treatment seeking at a formal provider, and 4) proportion of children <5 with malaria that received Artemether-Lumefantrine (AL) treatment. Mixed-effect logit models were employed to examine determinants of treatment-seeking behavior and factors affecting AL receipt among children <5 with malaria cases. Results: The proportion of febrile patients seeking treatment remained below 60% throughout 2012-2021, and AL receipt among children with malaria cases consistently stayed below 50%. The mean interval between fever onset and initial treatment-seeking encounter decreased from 2.42 days in 2012 to 1.71 days in 2021. Among formal care seekers, CHW utilization increased from 1.5% in 2012 to 10.0% in 2018 before declining to 3.2% in 2021. Longer walking time to the nearest health facility was associated with lower odds of treatment seeking, whereas CHW density was not associated with treatment seeking or AL receipt. Children who did not went to formal providers had lower odds of AL receipt than those who sought treatment from CHWs. Conclusion: Despite nationwide CCM scale-up over the last decade, significant barriers persist in malaria patients' access to diagnosis and treatment in Zambia. Our results indicate that while CCM coverage should be maintained and further expanded, additional complementary interventions are also needed to overcome remaining access barriers.

Eastern and southern Africa are highly affected by drought, and projections indicate that droughts will become more common in the coming decades. Whilst there has been research on the impact of drought on HIV, attributable to its effect on food insecurity and increased risky sexual behaviour, the link between drought and other sexually transmitted infections (STIs), particularly syphilis, remains largely unexplored. This study therefore assesses the association between drought and active syphilis, history of syphilis, and recovery from syphilis in Zambia, Uganda, and Tanzania, while examining disparities between urban and rural settings. It uses data on 75,225 people from Population-based HIV Impact Assessment surveys (2016-17), which include biomarker information, combined with rainfall data from the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) dataset to define drought in the two years prior to the survey. Multivariate logistic regression models with country-level fixed effects show that in urban areas, drought was associated with a significant increase in the probability of having active syphilis (average marginal effects (AME) = 0.5%, 95% confidence interval (CI): 0.2%-1.0%) and of having ever had syphilis (AME = 2%, 95% CI: 0.8%-4%). No significant association was found in rural areas. Exposure to drought was not associated with recovery from syphilis in either setting, though confidence intervals were wide. Our results underscore the importance of strengthening healthcare systems to make them more resilient to drought shocks in urban areas, and the need to reinforce syphilis prevention and treatment programmes in those areas when such shocks occur.

Mosquito-borne diseases pose a growing public health challenge as climate change reshapes vector population dynamics. West Nile virus (WNV), transmitted between birds and Culex mosquitoes, disproportionately affects Maricopa County, Arizona, one of the nation's highest-burden counties, yet whether models that include weather and avian dynamics improve forecast accuracy remains unclear. Using a 15-year weekly time series of mosquito abundance, mosquito infection prevalence, and human cases, we developed four mechanistic model configurations of varying complexity, from mosquito-human dynamics alone to full models incorporating avian dynamics and weather forcing. We fitted each model to the weekly-observed data, generated probabilistic 1- and 2-week-ahead forecast horizons, and evaluated forecasts against a historical baseline. All configurations fit the data equally regardless of weather or avian dynamics. However, models incorporating both birds and weather created more accurate forecasts of mosquito abundance and mosquito infection prevalence, and all configurations outperformed the baseline for forecasting human cases. Forecast accuracy was highest in summer and fall, and ensemble aggregation sometimes outperformed every individual model, stabilizing predictions across the 15-year record. These findings indicate that avian and weather dynamics are most critical for predicting mosquito-specific data, positioning this framework as a scalable tool for public health planning for WNV surveillance under climate change.

Introduction: Polyendocrine metabolic ovarian syndrome (PMOS), formerly known as polycystic ovary syndrome (PCOS), is a common endocrine disorder affecting women of reproductive age. Besides reproductive and metabolic disturbances, PMOS negatively impacts psychological well-being and quality of life. Despite available treatment options, there remains a need for safe and effective therapies that improve both clinical symptoms and fertility outcomes. Aim: To compare the efficacy of VAMHA and MYRHA tablet combination therapy with standard non-hormonal therapy in restoring regular menstruation. Secondary objectives included assessment of ovulation, menstrual symptoms, polycystic ovarian morphology, hormonal and metabolic parameters, anthropometric measures, and skin manifestations. Study Design: Open-label, randomized, multicentre, prospective comparative clinical study. Methods: Seventy-one women with PMOS were randomized to Group A (n=37) or Group B (n=34). Group A received VAMHA and MYRHA tablets (2 tablets each), while Group B received Metformin 500 mg plus Myoinositol 600 mg (1 tablet), twice daily for 180 days. Data were recorded in Case Report Forms. Statistical Analysis: Continuous variables were summarized using mean and standard deviation, while categorical variables were expressed as frequencies and percentages. Appropriate statistical tests, including Chi-square, were used. A p-value [&le;]0.05 was considered significant. Results: Significantly more participants in Group A achieved regular menstrual cycles than Group B (31 vs. 22; p<0.05). Ovulation occurred in 16 participants in Group A compared with 6 in Group B (p<0.05). Both groups showed significant improvement in menstrual irregularity and related symptoms. Significant reductions in Anti-Mullerian Hormone (AMH), fasting insulin, and body mass index (BMI) were observed in both groups (p<0.05). Resolution of polycystic ovarian morphology occurred in 13 participants (38.23%) in Group A and 10 (33.33%) in Group B. Both treatments were well tolerated with no major safety concerns. Conclusions: VAMHA and MYRHA combination therapy was superior to standard non-hormonal therapy in improving menstrual regularity and ovulation. It also produced favourable metabolic, hormonal, and ultrasonographic outcomes, suggesting its potential as a safe and effective option for comprehensive PMOS management and fertility enhancement.

Background: Despite several trials on the hematological outcomes of intravenous (IV) iron in pregnancy, only few have examined its effect on birth outcomes. We estimated the causal effect of IV-iron on moderate or severe anaemia and birth outcomes. Methods: Women presenting to routine antenatal care in Pakistan with haemoglobin <10 g/dL were eligible for treatment. We used target trial emulation (TTE) methodology to estimate the effect of IV-iron treatment within 14 days of anaemia identification, compared to no treatment, on anaemia status at follow-up. A modified TTE analysis examined birth outcomes at delivery for singleton pregnancies, including birthweight, size-for-gestational-age, and mortality. We conducted a separate TTE for each of five gestational-age periods and pooled the results of each TTE. Results: We screened 3115 pregnancies of which 1715 were eligible for IV-iron; 1043 participants were treated during pregnancy. Those who received IV-iron had half the risk of moderate or severe anaemia in pregnancy compared with no treatment (pooled relative risk (RR) 0.40; 95% confidence interval (CI): 0.27, 0.59). The pooled effect of IV-iron on stillbirth suggested an 83% risk reduction (95% CI 55-94%), and trends were similar for perinatal and neonatal mortality. Conclusion: IV-iron treatment improved haematological status in pregnant women and was associated with a large reduction in stillbirth. Given limited data from randomised trials regarding fetal death and treatment earlier in pregnancy, this study contributes important information to the potential benefit of IV-iron in contexts where anaemia and its sequelae are a major public health problem.

Artificial intelligence applied to routine electrocardiograms (ECGs) has largely focused on detecting existing disease or predicting individual cardiovascular outcomes. Whether ECGs can support prediction of multiple future diseases across organ systems remains unclear. We developed ECG-RISK, a multitask survival model for 67 incident three-character ICD-10 endpoints using ECG waveforms, demographic characteristics and routinely collected laboratory data from 86,673 MIMIC-IV patients. Discrimination was highest for heart, brain, kidney and lung endpoints, with organ-level C-indices ranging from 0.796 to 0.825, whereas liver and pancreatic endpoints showed lower discrimination. The ECG-only model achieved strong discrimination across most endpoints, whereas the incremental improvement gained by incorporating ECG and laboratory inputs beyond demographic information varied substantially across endpoints. Across the nine exploratory aggregated outcomes, Kaplan Meier curves showed clear separation among model-score tertiles. Discrimination was highest for dementia (C-index, 0.891) and heart failure (C-index, 0.857). These findings support the feasibility of ECG-based longitudinal risk prediction across multiple diseases. External validation and competing-risk analyses are required to assess generalisability and clinical utility.

Background: Adult congenital heart disease (ACHD) patients are prone to HLA-antibody formation from multiple surgeries, transfusions, and prosthetic surgical material. Females with ACHD may accrue additional, non-surgical alloantigen exposure. Whether sex modifies the impact of allosensitization on heart transplant (HT) access and outcomes in ACHD remains unknown. Methods: We retrospectively analyzed the OPTN/UNOS registry of adults with ACHD listed for first-time HT (2018-2025). Sensitization was defined by calculated panel reactive antibodies (cPRA) at listing. We tested the sex x sensitization (highly sensitized, cPRA >50%) interaction on transplant access using Fine-Gray competing-risks regression, treating transplantation as the event of interest and death or removal from the waitlist as competing events, and on post-transplant survival using multivariable Cox proportional-hazards regression, both adjusted for age at listing, mechanical support at listing, and the number of distinct prior cardiac surgery categories. Results: Among 856 candidates (38% female), females were more often highly sensitized than males (23% vs 14%; age-adjusted OR 1.81, 95% CI 1.26-2.61), even after adjusting for surgical burden. Sensitization reduced transplant access in females (84% to 71%; median wait 60 to 110 days, p < 0.001) but not males (79% vs 79%, median wait 88 vs 98 days). In adjusted Fine-Gray models, the subdistribution hazard for transplant was reduced in sensitized females (sHR 0.54, 95% CI 0.41-0.72) with no effect in males (sHR 0.96, 95% CI 0.73-1.26), and the sex x sensitization interaction was significant (interaction sHR 0.64, 95% CI 0.44-0.94, p = 0.02). Post-transplant mortality was numerically higher in sensitized than non-sensitized candidates in both sexes and the sex x sensitization interaction on 1-year mortality was not significant. The sex-asymmetric effect persisted and was more pronounced in the multiorgan candidates. Conclusions: Allosensitization is not a sex-neutral barrier to transplant in HT candidates with ACHD. Females are more sensitized and have reduced transplant access without differences in 1-year mortality. The female excess in sensitization is not accounted for by surgical burden, and the exposures responsible remain to be defined. These findings warrant a sex-aware listing strategy and further studies.

Objectives To evaluate whether access to a certified large language model (LLM)-based clinical decision support system improves physician diagnostic performance in rheumatology compared with conventional diagnostic resources alone. Methods In this multicentre, open-label, randomised controlled trial, 82 physicians from seven hospitals in two countries were randomised 1:1 to conventional diagnostic resources plus Prof. Valmed or conventional resources alone. Participants assessed three rheumatology vignettes before and after assistance. The primary outcome was top-1 diagnostic accuracy. Secondary outcomes included top-3 accuracy, diagnostic reasoning, confidence, case-processing time and perceived support quality. Results Top-1 accuracy increased from 22.2% to 33.3% in the intervention group and from 23.3% to 35.0% in the control group, with no between-group difference in improvement (adjusted OR 0.99, 95% CI 0.45 to 2.19; p=0.979). Differences in top-3 accuracy, diagnostic reasoning and confidence were also not significant. Assisted case-processing time was substantially shorter with LLM support (94 vs 206 s; adjusted mean difference -112 s, 95% CI -141 to -83; p<0.001). Information timeliness and perceived diagnostic support quality were rated significantly higher in the intervention group. Exploratory analyses showed persistent overconfidence and substantial AI over-reliance. Conclusions Certified LLM-based diagnostic support did not improve diagnostic accuracy compared with conventional resources, but substantially reduced case-processing time and improved perceived support quality. These findings suggest potential workflow benefits while highlighting overconfidence and over-reliance as important safety considerations.