Sexually Transmitted Infections

Background Fertility rates in Australia have been declining over recent decades, reaching a record low total fertility rate of 1.48 births per woman in 2024. Concurrently, vasectomy remains widely accessible and increasingly normalised as a permanent contraceptive option. Despite extensive commentary on falling birth rates, no contemporary Australian study has examined vasectomy rates relative to birth rates over time. We aimed to compare population level vasectomy and birth rates across Australian jurisdictions and age groups. Study design Nationwide retrospective time-series study. Retrospective population-based study using Medicare Benefits Schedule item 37623 to identify vasectomy procedures performed between July 2015 and December 2024. Rates were calculated per 100,000 male population using quarterly Australian Bureau of Statistics (ABS) population estimates and summarised as rolling 12-month averages. Birth rates were derived using matched ABS data for women across equivalent age strata (18-24, 25-34, 35-44 years). Results: Vasectomy rates increased nationally from 32 per 100,000 in 2016 to 55 per 100,000 in 2023 before declining modestly in 2024. Birth rates declined from 5,200 to 3,800 per 100,000 over the same period. Trends were consistent across states and age groups, with the greatest vasectomy uptake in men aged 35-44 years. Conclusion: Australia is undergoing a demographic shift characterised by rising vasectomy uptake and declining fertility. While vasectomy rates remain lower than birth rates, their convergence signals changing reproductive intentions and contraceptive behaviours. Ongoing monitoring of permanent and long-acting contraception is essential to understand evolving population dynamics and inform reproductive health policy.

Background: Pre-exposure prophylaxis (PrEP) has demonstrated a significant reduction in HIV infections among men who have sex with men (MSM), however, low medication adherence hinders its preventative effectiveness. Traditional approaches, such as health education and face-to-face inquiry (HEF), have demonstrated certain efficacy in improving PrEP adherence. However, these methods are resource-intensive and often plagued by delays, rendering timely and precise interventions challenging. This randomized controlled trial aims to assess the effectiveness of an intervention comprising AI-chatbot for PrEP (PrEP-bot) and Smart pillbox (SPB) (PrEP-bot-SPB) strategy to improve PrEP adherence among MSM compared to HEF.Methods and analysis: A three-arm, multicenter, open-lable RCT will be conducted with Chinese MSM [≥]18 years. A total of 300 participants will be recruited through three sources, including hospitals, community-based organizations (CBOs) and peer referral in five cities: Shenzhen, Beijing, Qingdao, Hangzhou and Zhengzhou. After completing baseline survey, participants will be randomized evenly into interventions or control groups: the PrEP-bot group, the PrEP-bot-SPB group, and the HEF control group. Participants in the PrEP-bot group will be granted access to an AI-chatbot agent through WeChat. This agent will: 1) generate personalized PrEP medication plans; 2) provide medication reminders and PrEP-related health check-ups notifications; 3) inquire about missed doses to deliver tailored interventions; 4) answer participant questions about PrEP using guideline-based knowledge. Participants in the PrEP-bot-SPB group will receive both the SPB and the PrEP-bot interventions. SPB could delivers medication reminders. Participants in HEF group will receive a health education pamphlet introducing PrEP and knowledge related to PrEP medication adherence at baseline and face-to-face inquiry every three months. Outcomes will be assessed for both short-term and medium-to-long-term effects. The primary objective is the effectiveness in improving PrEP adherence measured by self-report, Eight-Item Morisky medication adherence scale (MMAS-8) and concentration of Tenofovir in dried blood spots (DBS) (PrEP adherence [≥]90%) at 3 months follow-up. Secondary outcomes include: 1) effectiveness in preventing HIV infection measured by HIV-self test (HIVST); 2) effectiveness of PrEP-related health check-ups; 3) the effectiveness, feasibility, acceptability, and user satisfaction with the PrEP-bot; 4) effectiveness in improving PrEP adherence at 6-month, 9-month and 12-month follow-up periods. All participants will receive quarterly follow-up visits during the 12-month study period. Intention-to-treat analysis and per protocol set (PPS) analysis will be used.Results: Recruitment and enrollment of participants began in January 2026 and is currently ongoing.Discussion: This study is expected to establish a novel AI-based intervention model for PrEP, providing innovative strategies for HIV control among MSM populations. If the PrEP-bot is proven non-inferior to HEF, it could offer users real-time, precise, and personalized interventions while simultaneously addressing PrEP-related inquiries and health check-ups reminders. Importantly, this approach would achieve significant reductions in resource requirements for implementation and maintenance and be more cost-effective. With the ongoing advancement of AI technologies, PrEP-bot holds substantial promise for widespread implementation in PrEP adherence, potentially revolutionizing HIV prevention for MSM in China through this innovative intervention modality.Trial registration: ChiCTR2500111280 (Chinese Clinical Trial Registry). Date of registration: 29 October 2025.

Introduction: Differentiated service delivery (DSD) models aim to reduce time healthcare providers spend with DSD clients, increasing time available for non-DSD clients. We measured nurses' time allocation and explored their experiences with DSD models in South Africa. Methods: We conducted time and motion observations and surveyed nurses at 24 public primary healthcare facilities across two SENTINEL study rounds (09/2022-07/2023 and 11/2023-07/2024). We report median time nurses spent by activity, model of care, and interaction type. Log binomial regression investigated factors associated with high direct nurse-client interaction (above median minutes) and extended work-days ([&ge;]9 hours), and estimated adjusted risk ratios (aRR). Survey questions were related to client care, additional time availability, and policy changes post DSD implementation, with key themes presented alongside illustrative quotes. Results: 176 nurses (88% female, median age 44) were observed for 344 working days; of these, 60 (34%) participated in the provider survey. Nurses spent a median of 293 minutes (53% of their work-day) on direct nurse-client interaction, 89 minutes (22%) on client-support or facility-related tasks, and the remainder on other activities including personal breaks. Time spent per client was similar across conventional care clients (11 [IQR: 8-15] minutes) but ranged between 9 (7-13) to 11 (8-15) minutes for DSD clients; number of direct nurse-client interactions did not differ meaningfully. Nurses at facilities with 2,000-3,999 total remaining on ART (TROA) (aRR 1.56, 95% CI: 1.02-2.37) and in urban areas (aRR 1.43, [1.08-1.89]) had more direct nurse-client interactions than those at facilities with <1,999 TROA and in rural areas, respectively. Nurses at facilities with 4,000+ TROA (aRR 2.22, [1.36-3.63]) and those observed in SENTINEL 3.0 (aRR 1.53, [1.13-2.07]) were more likely to work standard or longer workdays than those at lower TROA facilities (<1,999), those in SENTINEL 2.0 and urban areas. Nurses reported DSD models improved client care (90%), freed up time (60%), and changed clinic procedures and policies (60%). Conclusions: While DSD models did not significantly reduce direct nurse-client interaction time, nurses reported improved client care and gained additional time. DSD impact may vary by facility context. As DSD implementation expands, effective time reallocation may enhance facility performance and provider productivity.

Introduction Dysmenorrhoea is highly prevalent globally and interferes with engagement in education, work, social participation, and quality of life. Although evidence suggests that sociocultural beliefs influence how menstrual pain is understood and managed, relatively little research has explored dysmenorrhoea-related knowledge and beliefs within South Africa. This study aimed to (1) determine the frequency of dysmenorrhoea, (2) assess dysmenorrhoea-related knowledge and compare knowledge between menstruating and non-menstruating individuals, and (3) explore commonly held generational, cultural, and religious beliefs related to dysmenorrhoea in a South African university cohort. Methods We analysed data collected as part of a cross-sectional survey conducted among staff and students at a South African university. Participants completed demographic questions, items assessing dysmenorrhoea-related knowledge, and an adapted Working Ability, Location, Intensity, Days of Pain, Dysmenorrhoea (WaLIDD) questionnaire. Participants were also invited to provide free-text responses describing generational, cultural, and religious beliefs about dysmenorrhoea. Quantitative data were analysed descriptively and compared between menstruating and non-menstruating participants. Free-text responses were analysed using reflexive thematic analysis. Results A total of 863 participants completed the survey, including 578 current or past menstruators. The frequency (95%CI) of dysmenorrhoea was 75.4% (71.7-78.9). Most participants were classified as having moderate (53%) or severe (31%) dysmenorrhoea on the WaLIDD scale. Awareness of dysmenorrhoea was higher among participants who had menstruated than among those who had never menstruated (80.4% vs 55.3%, p<0.001). Most participants (85.1%) reported wanting more education about dysmenorrhoea and its impact. Reflexive thematic analysis of 246 free-text responses identified five themes: (1) menstrual pain is normalised, dismissed, and expected to endure, (2) reproductive meanings attached to menstrual pain, (3) moral, spiritual, and cultural interpretations of menstrual pain, (4) negotiating competing explanations for menstrual pain, and (5) managing and controlling menstrual pain symptoms. Across themes, dysmenorrhoea was interpreted through social, cultural, reproductive, spiritual, and biomedical frameworks that shaped how pain was understood, communicated, and managed. Conclusion Dysmenorrhoea is common in this South African university cohort, and is rarely understood as a purely biological symptom. Instead, menstrual pain is understood and managed through broader social, cultural, reproductive, moral, and biomedical narratives, which shape how pain is recognised, disclosed, legitimised, and treated. These findings highlight the importance of considering sociocultural beliefs alongside clinical factors when developing menstrual health education, support strategies, and healthcare services.

PURPOSE: As the armamentarium of BPH therapies continues to expand, it remains imperative to maximize patient satisfaction and minimize decisional regret. We sought to determine the impact of time from BPH diagnosis to index treatment on symptom improvement and subsequent procedural events. MATERIALS AND METHODS: We queried the American Urological Association Quality Registry for men [&ge;] 40 years old with BPH, available IPSS data, and no receipt of prior BPH treatment. Index treatment included medication, surgery, or minimally invasive surgical therapy (MIST). Outcomes included IPSS over 3 years of follow-up, change in percentage of mild lower urinary tract symptoms (LUTS) by 3 months, and time to procedural event. Patients were stratified by time from index diagnosis to treatment by <12 months, 1-3 years, and >3 years. Outcomes were compared across time-to-treatment cohorts with appropriate statistical tests with p < 0.05 as significant. RESULTS: 43,919 patients met criteria with 19,642 pursuing treatments. Patients pursued treatment at comparably lower baseline IPSS compared to prior prospective series. Patients undergoing surgery and MIST had significantly higher baseline IPSS, while medical comorbidities were significantly more common among men initiating pharmacotherapy. Early surgery and MIST were associated with significant improvement in IPSS within 6-12 months and an increase in mild LUTS by 3 months. All forms of early treatment were associated with delayed time to procedural events, including catheterization and fulguration. CONCLUSIONS: Early procedural intervention for BPH is associated with early symptom improvement and delayed time to procedural events among real-world, contemporary practice.

Background: In resource-limited settings, a critical bottleneck in cervical cancer prevention is the lack of practical strategies to triage high-risk human papillomavirus (HR-HPV)- positive women. Therefore, this study aimed to develop and internally validate a genotype-specific risk stratification model. Methods: A cross-sectional study enrolled 555 women in Cameroon. Data collection integrated cervical cytology and HPV genotyping using Abbott m2000rt and Sacace multiplex systems. An iterative modeling approach with bootstrap validation was used to develop the model and address model instability. HR-HPV genotypes were transformed into a hierarchical risk variable due to sparsity and integrated with significant predictors. The final model was translated into a scoring system, and the risk gradients and performances were evaluated at two thresholds. Data was analyzed using SPSS 27.0. Results: The mean age was 44.8 years, and the prevalence of HR-HPV was 26.5% (147/555). The final model, incorporating HPV categories, age, and tobacco, demonstrated moderate discriminative ability (AUC=0.702, 0.642-0.762) with a good calibration (Hosmer-Lemeshow {chi}{superscript 2}=4.05, p=0.399). The scoring system assigned women to risk groups based on their total scores which produced a clear monotonic risk gradient; the observed probability of high-grade lesions/cancer ranged from 15% (score 0) to >65% (score [&ge;]4). At a conservative threshold ([&ge;]4 points), 4.7% (26/555) of women were classified as high-risk, concentrating 46% (6/13) of cancers (positive predictive value[PPV]=58%) while a sensitive threshold ([&ge;]3 points) had 16.8% (93/555) high-risk, concentrating 77% (10/13) cancers (PPV=38%). Both thresholds maintained a high negative predictive value (>95%). Conclusion: This bootstrap-validated, risk-stratification tool is a proof-of-concept in resource limited settings that assigns HR-HPV-positive women to distinct management pathways using three variables. After refining through a longitudinal study and external validation, this scoring system can improve the efficiency of cervical cancer screening programs in low-resource settings.

Abstract Introduction Onchocerciasis is targeted for elimination with community-directed treatment with ivermectin (CDTI). Alternative strategies are needed in areas where transmission persists despite long-term CDTI and/or are co-endemic with loiasis. This study assessed the efficacy of 35-day treatment with 100mg doxycycline on Wolbachia density at 6 months and microfilaridermia and palpable nodules at 30 months post-treatment. Methods A treatment follow-up study was conducted in 20 high-transmission onchocerciasis communities in a co-endemic loiasis area of South-West Cameroon. Community-based directly observed treatment with 100mg doxycycline was administered to community members aged [&ge;]9 years. Wolbachia clearance at 6-months and treatment efficacy on microfilaridermia and palpable nodules were assessed at 30-months post treatment. Factors associated with reductions in microfilaridermia post treatment, including adherence to doxycycline treatment were assessed with mixed-effects logistic regression. Results Over 92% (2835/3080) of eligible participants took 35 days of 100mg doxycycline over 5 or 6 weeks. This regimen achieved a 62.8% microfilaridermia reduction and 99% palpable nodule reduction in the 720 participants included at follow-up. Wolbachia depletion was observed in 92% of skin samples at 6 months post treatment. The most important factor associated with microfilaridermia after 30 months was having missed at least 7 doxycycline consecutive doses (OR 3.11, 95%CI: 1.17-8.26). Incomplete treatment to a lesser extent was not associated with reduced efficacy at follow-up. Conclusion This large-scale community intervention shows that a 5-week treatment with 100mg doxycycline is feasible and has high curative efficacy against adult O. volvulus as measured by the dramatic reduction in the proportion of palpable nodules at 30-months post treatment. The high efficacy shows the tremendous potential of anti-Wolbachia drugs as part of the arsenal for onchocerciasis elimination and paves the way for the next generation of anti-Wolbachia drugs with shorter treatment courses, which will facilitate the implementation of alternative strategies to accelerate onchocerciasis elimination.

Objective: To characterize pregnancy outcomes and menstrual irregularities in Mexican women with systemic lupus erythematosus (SLE) and identify clinical factors associated with adverse pregnancy outcomes and early-onset menopause. Methods: We conducted a cross-sectional study of women with SLE enrolled in the Mexican Lupus Registry (LupusRGMX) between May 2021 and September 2024. Clinical and reproductive data were collected using standardized questionnaires. Menopause was defined as the absence of menstruation for [&ge;]12 consecutive months, and early menopause as onset before age 40. Univariable and multivariable logistic regression analyses were used to identify factors associated with pregnancy complications and early menopause. Results: A total of 210 women were included. Median age was 38 years (IQR 29-46) and median disease duration was 4 years (IQR 1-10). Among women with a history of pregnancy (47%), full-term delivery predominated (61%), while pregnancy loss occurred in 26% and preterm delivery in 13%. Pregnancy complications were reported in 9.6%, most commonly preeclampsia (6.7%). Younger maternal age was independently associated with pregnancy complications (OR 0.89, 95% CI 0.83-0.95) and adverse outcomes (OR 0.95, 95% CI 0.92-0.98). Higher disease activity was associated with complications in univariable analysis. Most pregnancies (68.3%) occurred before diagnosis. Early menopause was observed in 6.2% and independently associated with longer disease duration and older age. Conclusion: Younger maternal age was independently associated with adverse pregnancy outcomes, whereas disease activity showed an association in univariable analysis. Most pregnancies occurred prior to SLE diagnosis. Early menopause was associated with longer disease duration, suggesting impact of cumulative disease burden on ovarian function.

Background: Qualitative studies have noted that the burden of family planning disproportionately falls on women in India. Our primary objective was to quantify the gender disparity in the uptake of surgical sterilizations. Our secondary objectives were to calculate the costs of tubectomies and vasectomies in India and to estimate the savings of scaling up vasectomy rates. Methods: We conducted a retrospective analysis using data on the total number of tubectomies and vasectomies performed, postoperative failure, and postoperative mortality due to these procedures, obtained from the Health Management Information System (HMIS) for 2019-20. We calculated the vasectomy (tubectomy) operative rates per 10,000 men (women) of reproductive age (15-49 years). The women-to-men ratio of these rates is used as a proxy for sex-based disparities in uptake. State-specific procedure costs and compensation for failures and postoperative deaths at public hospitals were extracted and aggregated from government data and research studies. To estimate the financial benefit of scaling up vasectomies, the cost of increasing the vasectomy rate to 50% of the total sterilization rate was calculated. All costs were adjusted for inflation to 2022 and presented in United States Dollars (USD). Findings: In 2019-20, the national tubectomy rate was 96.5, the vasectomy rate was 1.4, and the resulting women-to-men rate ratio was 67.5. The cost per tubectomy procedure was 3.5 times that of vasectomy (89.1 USD vs. 25.3 USD). Keeping the overall operative rate constant, the net savings from scaling up vasectomies to at least 50% of total operations (replacing excess tubectomies) range from 62,193,487 to 75,355,777 USD. Interpretation: Our pan-India analysis confirms that the use of surgical family planning methods is disproportionately higher among women. Scaling up vasectomies has finacial benefits and can improve gender equity. Funding: None.

Introduction: Brain-predicted age, estimated from structural MRI data, is a machine-learning biomarker of biological brain aging. Greater brain age gap (BAG) indicates advanced brain aging and is associated with cognitive decline and mortality. Cardiometabolic risk factors, including elevated blood glucose, body mass index (BMI), blood pressure, and cholesterol, increase risk of cognitive impairment and dementia in aging. Their relationship with BAG in severe obesity remains poorly characterized despite increased prevalence of cardiometabolic risk factors among this population. Methods: T1-weighted MRI data from 97 adults (BMI 35-73) were used to calculate BAG using ENIGMA and Pyment brain age models. Associations between BAG and HbA1c, BMI, hypertension, and hyperlipidemia were examined using multiple linear regression and MM-estimation robust regression, adjusting for age, sex, and race. Post hoc analyses stratified models by clinical HbA1c cutoffs (normoglycemic, prediabetic, diabetic). Results: Higher HbA1c was associated with greater BAGENIGMA (B = 1.58, p = .014) and BAGPyment (B = 0.93, p = .013) in linear regression models. In robust models, HbA1c remained significantly associated with BAGENIGMA (B = 1.70, p = .002) but not BAGPyment (B = 0.71, p = .13). BMI, hypertension, and hyperlipidemia were not associated with BAG in either linear or robust models. HbA1c was associated with greater BAGENIGMA (B = 2.15, p = .01) and BAGPyment (B =1.21, p = .04) in those at or above prediabetic levels and with BAGENIGMA (B = 2.49, p = .047) in those with diabetes. Conclusions: Elevated HbA1c is associated with accelerated brain aging in individuals with severe obesity. BAG was not associated with BMI, hypertension, and hyperlipidemia, which may reflect the restricted BMI range inherent to the sample with severe obesity.

OBJECTIVE: Bladder cancer (BC) is predominantly a disease of older, comorbid adults, and radical cystectomy (RC), which is the gold standard treatment, carries considerable morbidity. We sought to determine the impact of baseline dementia and frailty on the care trajectory beyond the immediate postoperative period. We hypothesized that frail patients and those with dementia undergoing RC for BC will have poorer care trajectories. METHODS AND MATERIALS: We identified Medicare beneficiaries [&ge;] 66 years old who underwent RC for BC in 2017 with 12 months of pre- and post-RC enrollment. Frailty and dementia were characterized using validated, claims-based measures. Associations between baseline frailty and dementia with postoperative care trajectory outcomes were determined using Fine-Gray competing risk models. RESULTS: We identified 3,600 beneficiaries of whom 11.6% were frail and 3.4% met criteria for dementia. Patients with dementia were more likely to be frail, comorbid, and not receive standard-of-care neoadjuvant chemotherapy. Frailty was independently associated with [&ge;] 2 transitions in care level after index discharge from RC and skilled nursing facility (SNF) admissions within 1 year of RC, exposure to intensive post-RC interventions, including dialysis and feeding tube placement, and poorer survival. Dementia remained associated with SNF admissions regardless of frailty level. CONCLUSIONS: Among a contemporary cohort of older adults undergoing RC for BC, preoperative dementia and frailty were independently associated with poorer care trajectory beyond the immediate postoperative period after RC. Our work highlights a role for preoperative geriatric assessment in identifying and optimizing patients at greatest risk.

Background Slow walking in older adults with mild parkinsonian signs (MPS) is a complex, multifactorial phenomenon arising from the cumulative burden of subclinical age-associated pathologies. This decline reflects age-associated neuronal loss in the dopaminergic system. A recent study suggests that levodopa treatment may enhance gait parameters. The goal of this small pilot study is to explore the effect of levodopa treatment on slow walking gait in older adults with MPS. Method This study was a randomized, placebo-controlled clinical pilot trial. Slow walking older adults without clinical evidence of PD were recruited and randomized into 2 groups (active treatment group or placebo control group). Participants in the active group were pre-treated with carbidopa for three days, followed by carbidopa-levodopa for seven days. Spatiotemporal gait parameters were evaluated at baseline and post-intervention. Results Gait factor analysis identified three main factors explaining gait characteristics at baseline, which included gait efficiency, gait rhythmicity, and gait turning.No effect of treatment was observed in the placebo group (p=0.111, p=0.616), no group difference was observed between the placebo and active group at baseline ({beta}=0.310, p=0.547), but a strong trend for a treatment-related increase was observed in the active treatment group ({beta}=0.506, p=0.076). Conclusion Our preliminary data suggest that sustained levodopa treatment (one week) in conjunction with carbidopa pre-treatment and concomitant carbidopa supplementation is feasible in slow walking older adults with MPS. Moreover, the data indicate potential efficacy, showing improvements in cadence, and step durations.

Background. Capillary refill time, an examiner-dependent bedside test of distal microvascular perfusion, has become a resuscitation target in septic shock,1,2,3,4 motivating a continuous surrogate computed from the photoplethysmogram (PPG, the optical waveform the pulse oximeter on every ICU patient already records).5,6,7,8 Objective. We attempted three PPG-derived candidate measures on the MIMIC-IV Waveform Database (MIMIC-IV-WDB v0.1.0) and asked, by inspecting randomly drawn examples, whether each captured its intended physiology before any downstream modeling. Methods. MIMIC-IV-WDB v0.1.09 was linked to MIMIC-IV.10 The signals were a cuff-anchored perfusion-index recovery (reactive hyperemia when the cuff shares an arm with the probe), a slow Mayer-wave-band power ratio of the perfusion index (sympathetic vasomotor tone), and a per-beat diastolic exponential decay time constant (a refill-like recovery time). For each signal we drew 10 random examples at a fixed seed and checked them against a checklist fixed in advance. Each was read by the author and, separately, by MedGemma 1.5, a multimodal medical language model run locally. A synthetic test with a known time constant checked the third signal. Results. The cuff-anchored signal showed the expected occlusion-reperfusion shape on 268 of 6,236 evaluable cuff cycles (4.30%) in 15 of 19 patients, consistent with opposite-limb placement of the probe and cuff. The slow-band ratio returned a stable cohort value, but a clear, stationary peak appeared in only4 of 10 random windows. The per-beat fit met its goodness-of-fit threshold in 10 of 10 beats, yet a cardiac-frequency heuristic flagged a possible fit on the heart-rate oscillation in 7 of 10, and in 5 of 17 patients the time constant lay where an exponential is indistinguishable from a straight line. A 0.5Hz high-pass pre-filter implanted its own approximately 318 ms time constant regardless of truth. The language model tracked the human on clear positives but reported the pattern present on every call it returned, never absent. Conclusions. Two of the three candidate signals did not reflect their intended physiology in most examples, and the third was constrained by sensor placement. Inspecting a few random raw inputs against a checklist written in advance is an inexpensive upstream check before downstream inference on PPG-derived microvascular signals.

Background Electronic health record documentation patterns may reflect workflow complexity, monitoring intensity, and operational strain in intensive care settings. However, documentation-derived features can be sensitive to local documentation culture, data capture systems, and outcome definitions. Retrospective validation across multiple datasets is therefore needed before these signals are used in workflow intelligence or clinical AI governance tools. Objective To evaluate whether documentation-density and documentation-timing features show reproducible retrospective signal for ICU workflow complexity and long-stay proxy outcomes across de-identified critical care datasets, while distinguishing workflow and long-stay associations from unsupported claims about mortality prediction, burden reduction, or deployment readiness. Methods We synthesized retrospective validation results from de-identified ICU and workflow datasets generated through a prespecified documentation-density validation program. Feature families included Documentation Burden Score style features, Shift-End Documentation Rate style features, documentation reliability style metadata, and all-documentation feature sets where available. Outcomes included long ICU length of stay proxies, mortality where available, and workflow proxy endpoints. Models compared baseline feature sets with enhanced models containing documentation-density or workflow features. Performance was summarized using area under the receiver operating characteristic curve, Brier score where reported, delta AUROC, bootstrap confidence intervals where reported, and label-shuffle controls where available. Results The strongest external long-stay proxy evidence came from the NWICU chartevents analysis, which included 28,612 ICU stays, 20,267 stays with chart events, and 9,619,759 chart events. For ICU length of stay greater than the median, baseline AUROC was 0.5252. Enhanced AUROC was 0.9512 for Documentation Burden Score features, 0.9214 for Shift-End Documentation Rate features, 0.8470 for documentation reliability style features, and 0.9517 for all documentation features. Corresponding label-shuffle enhanced AUROCs were near random, ranging from 0.4897 to 0.5064. For ICU length of stay greater than the 75th percentile, baseline AUROC was 0.5155. Enhanced AUROC was 0.9433 for Documentation Burden Score features, 0.9194 for Shift-End Documentation Rate features, 0.8118 for documentation reliability style features, and 0.9427 for all documentation features, with label-shuffle enhanced AUROCs from 0.4836 to 0.4999. Additional retrospective support was observed in eICU workflow analyses, HiRID first-24-hour documentation-density analyses, MIMIC-IV HF ICU internal analyses, MIMIC-IV-Note metadata extensions, and nursing-chart or lab density proxy analyses. However, cross-institution discrimination transfer was weak without recalibration, and several analyses remained proxy validations rather than final clinical validations. Conclusions Documentation-density and documentation-timing features show promising retrospective signal for ICU workflow complexity and long-stay proxy outcomes, especially in NWICU chartevents and selected internal dataset-specific analyses. These findings support further preregistered, prospective, silent-mode validation of documentation-derived workflow intelligence. They do not establish prospective clinical performance, mortality reduction, clinician burden reduction, autonomous deterioration prediction, or deployment readiness.

Accurate assessment of body composition is important to risk stratification and management of metabolic, musculoskeletal, and aging-related diseases, yet reference modalities such as Dual-energy X-ray absorptiometry (DXA) are costly and impractical for frequent monitoring. Commodity 3D body scans offer a low-cost, radiation-free alternative, but extracting meaningful and predictive shape features from scans remains challenging due to nonuniform point density, variable body size and cross-device differences. We introduce BodyMAE, a self-supervised, surface-area aware masked autoencoder for metric-scale 3D body scans. The pipeline integrates area-adjusted sampling, a long-range focused encoder, and a lightweight decoder regularized to promote locally uniform reconstructions. Trained and evaluated on 917 paired 3D body scans paired with clinical DXA reports, BodyMAE achieves strong accuracy on fat percentage (root-mean-square error (RMSE) 3.825 percentage points, R^2 0.908), fat mass (RMSE 3.694 kg, R^2 0.968), and lean mass (RMSE 3.608 kg, R^2 0.901), with competitive performance on bone mineral content (RMSE 0.284 kg, R^2 0.754).We also assess feature stability across pretrained baselines, finding higher retrieval accuracy for our representations (Top-1 90.131%). These results indicate that combining metric-aware sampling, long-range relational encoding, and local geometric regularization enables accurate body composition estimation from 3D body scans, as validated by comparisons to DXA-derived measurements.

Large language models embedded in autonomous agents process trusted instructions and untrusted data in one context window, leaving them open to direct and indirect prompt injection. In healthcare this is not hypothetical: a 2025 JAMA Network Open study found commercial medical LLMs followed injected instructions in 94.4% of simulated patient encounters, including life threatening recommendations . Yet the clinically decisive problem we quantify here is different. Most real clinical threats protected health information PHI exfiltration, cross patient access, bulk export, out of scope advice are fluent, legitimate looking requests that carry no attack signal, so even a state of the art injection detector passes them. Existing runtime guardrails trade safety against latency: model based auditors are accurate but add hundreds of milliseconds of Python inference, while lexical filters are fast but blind to obfuscated or semantically disguised payloads. We present QFIRE, an inline, provider agnostic prompt firewall implemented as a single self contained Rust toolchain proxy, CLI, and benchmark harness. QFIRE combines three mechanisms: (i) positive security scope constraints, which restrict a model call to a declared natural language purpose and block out of scope drift even when no overt attack token is present; (ii) an asynchronous detector graph that runs N rules and their detector nodes concurrently, cheapest checks first; and (iii) a de obfuscation pass that decodes Base64 hex ROT13, folds homoglyphs and leetspeak, and strips zero width characters before detection. QFIRE ships 106 versioned firewall rules and a dedicated HIPAA Safe Harbor 18 identifier PHI panel, and runs a local DeBERTa v3 injection classifier via embedded ONNX Runtime. On 1968 public prompt injection and jailbreak prompts QFIREs deterministic hybrid attains F1 0.86, statistically tied with Metas state of the art PromptGuard 2 0.86 and above protectai DeBERTa v3 0.83; lexical baselines lag 0.16 to 0.50. Our central result is on QFIRE HealthBench, a new 2000 prompt healthcare benchmark we build and release with real garak and Microsoft PyRIT payloads. There the same PromptGuard-2 recovers only 0.40 recall DeBERTa v3 0.57, because most clinical threats carry no injection signal; QFIREs combined scope plus PHI chain reaches 0.83 recall F1 0.87 at a calibrated 0.08 false positive rate. Generic injection detection, even state of the art, is therefore necessary but not sufficient for healthcare agents. A bare LLM judge also closes most of this static corpus gap F1 0.90; QFIREs contribution beyond static accuracy is auditable determinism, bounded latency, and adaptive robustness, where the bare judge falls to 34 to 59% recall section 5.5. End to end, placing QFIRE in front of a tool using agent over a mock EHR sandbox cuts the agents harmful action rate from 0.38 to 0.00 at a 0.13 benign utility cost. All code, rules, corpora snapshots, and scripts are released, and every table regenerates from a single make paper target against local models with no paid API keys.

**Abstract** **Background:** Transcatheter edge-to-edge repair (TEER) is an established treatment for mitral regurgitation but remains highly dependent on operator experience and complex transesophageal echocardiography (TEE)-guided intraprocedural imaging. Artificial intelligence (AI)-based semantic segmentation may improve procedural reproducibility and intraprocedural guidance; however, no TEER-specific segmentation framework has been reported. **Objectives:** To develop and evaluate AutoClip, a clinician-driven AI-guided TEE semantic segmentation model designed for simultaneous delineation of mitral valve anatomy and in-vivo TEER device components. **Methods:** A retrospective proof-of-concept study was conducted using 987 intraprocedural TEE frames derived from 10 video clips in 3 patients undergoing MitraClip G4 implantation. Seven semantic labels, including mitral leaflets and device components, were manually annotated using ITK-SNAP. Following standardized preprocessing and region-of-interest extraction, an Attention U-Net architecture was trained frame-wise on bicommissural and corresponding X-plane TEE views. Model performance was assessed using mean intersection-over-union (IoU) and Dice coefficient on an independent test set. **Results:** The Attention U-Net demonstrated improved sensitivity to small device structures compared with conventional U-Net architectures. Preliminary training performance achieved a mean IoU of approximately 0.93, while independent test performance reached a mean IoU of 0.46 across foreground classes. Qualitative assessment demonstrated feasible simultaneous segmentation of mitral leaflets, clip arms, grippers, and delivery shaft during TEER procedures. **Conclusions:** AutoClip represents a proof-of-concept TEER-specific TEE semantic segmentation framework initiated through a clinician-oriented workflow without formal computer science expertise. Although preliminary accuracy remains modest due to limited sample size, this study establishes a reproducible pathway for future AI-assisted intraprocedural guidance systems and larger multicenter development efforts in structural heart interventions.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is rapidly increasing worldwide, yet effective targeted therapies remain limited. To better understand the molecular mechanisms underlying MASLD, we performed an integrated proteogenomic analysis of human liver tissue. Using mass spectrometry, we quantified 2,744 proteins in 504 liver biopsies from the Quebec Obesity Biobank and examined changes across disease stages. To investigate causality, we integrated liver proteomics with RNA sequencing and genome-wide genotyping to map thousands of protein quantitative trait loci (pQTLs) and expression quantitative trait loci (eQTLs). These molecular data were combined with summary statistics from a meta-analysis of genome-wide association studies including 16,532 MASLD cases and 1,240,188 controls. Mendelian randomization and genetic colocalization analyses revealed that most proteins differentially expressed across MASLD stages were not causally implicated in disease risk, whereas several genetically predicted liver proteins showed evidence of causal effects. Among these, higher hepatic levels of the MTARC1 protein were causally associated with MASLD and hepatic fat accumulation. Phenome-wide analyses suggested that MTARC1 inhibition may reduce the risk of cirrhosis, hepatocellular carcinoma, and cholelithiasis while improving lipid profiles. Notably, the causal MTARC1 variant influenced liver protein levels but not gene expression. Genetic analyses also identified ERLIN1 and HSD17B13 as potential therapeutic targets. In contrast, eQTLs and pQTLs at other loci such as GCKR showed opposite effects on MASLD risk. These findings highlight the importance of integrating tissue proteomics with human genetics to distinguish biomarkers from causal drivers and to identify promising therapeutic targets for MASLD.

Background: Chronic diseases and symptom syndromes often develop after prolonged biological changes that may precede formal diagnosis. RNA-based metatranscriptomics captures active microbial and human gene expression and may provide a functional layer for disease risk evaluation. To address this translational gap, we developed and validated a Disease Risk Score (DRS) framework that integrates metatranscriptome-derived pathway activity scores from stool, saliva, and blood samples, and evaluated its potential clinical utility as an adjunct risk-evaluation tool. Methods: DRS uses disease-specific sets of pathway activity scores derived from stool and saliva microbial functions, stool and saliva microbial taxa, and blood human gene expression. For each disease, 'not optimal' pathway scores are aggregated into a normalized cumulative odds ratio, or cOR, using score-level odds ratios, statistical significance, and literature-supported biological relevance derived from a Development Cohort of 22,369 individuals. A cOR [&ge;] 5 is defined as high risk. Performance is evaluated in an independent Validation Cohort of 15,908 individuals using self-reported diseases as the reference. Disease support requires both significant cOR separation between self-reported and not-reported (Cohen's d [&ge;] 0.2) and risk ratio enrichment of self-reported disease among individuals classified as high risk (95% CI of Risk Ratio > 1). Results: Of 20 initially evaluated diseases, 15 meet the prespecified validation criteria on the independent validation cohort: ADHD, anxiety, chronic fatigue syndrome, depression, GERD, hypertension, inflammatory bowel disease, IBS-C, IBS-D, insomnia, MASLD, obesity, obstructive sleep apnea, Sjogren's syndrome, and type 2 diabetes. Five selected clinical scenarios illustrate how DRS can support clinician-mediated decision making, including IBS subtype reclassification, improved diagnostic acceptance in IBS-D, personalized lifestyle counseling in MASLD and early type 2 diabetes, and diagnostic uncertainty in atypical GERD. Conclusions: DRS is a metatranscriptomics-based risk-stratification framework that aggregates active microbial and human pathway signals into interpretable disease-specific risk estimates across a wide range of disease conditions. Validation against self-reported disease labels in an independent cohort shows significant risk enrichment for each of 15 diseases. DRS is intended as an adjunct to clinical evaluation: a decision support tool in situations where routine care encounters uncertainty, delay, or low patient engagement. Future prospective studies using clinically adjudicated endpoints are needed to assess calibration and clinical outcomes.

Vaccines to prevent infant group B streptococcus (GBS) disease are advancing, with licensure likely based on safety and immunologic endpoints rather than clinical efficacy data. This approach requires robust, generalisable serological thresholds of risk reduction (SToRRs). We combined data from six case-control studies in Europe and Africa to define SToRRs for early-onset (EOD) and late-onset (LOD) GBS disease. Across diverse epidemiological and healthcare settings, anti-capsular polysaccharide IgG concentrations were consistently higher in infants who remained disease free than in those who developed disease. Higher antibody concentrations were required to reduce the risk of EOD than LOD, and higher concentrations were required for serotype Ia than for serotype III. This study provides a quantitative framework to support correlates-based evaluation and potential licensure of maternal GBS vaccines.