Inflammatory Bowel Diseases

Background Unplanned hospital admissions in Inflammatory Bowel Diseases (IBD) account for nearly three-quarters of IBD inpatient stays in the United Kingdom. Although costly to services and distressing for patients, research exploring experiences and potential drivers of admissions is limited. We undertook a qualitative study to explore the healthcare experiences and access needs of people with IBD who had unplanned admissions, along with their caregivers and clinicians. Methods Semi-structured interviews with 25 participants from a single tertiary IBD service in England (17 people with IBD, 3 informal caregivers, 5 clinicians) were conducted. We applied thematic framework analysis, guided by the Candidacy Framework, and worked with 2 patient and public contributors to generate final themes. Results We identified four themes: 1) Difficulties in Identifying flares and asserting severity before admission, summarised the prevailing uncertainty in identifying a flare and access to timely IBD care. 2) Navigating a disjointed healthcare system, highlighted how lack of care plans and systemic barriers can delay access. 2) Emergency care access challenges highlighted the gaps in emergency and inpatient care during flares. Whilst 4) fighting for care and individual advocacy needs, described the persistent assertion for care that may disproportionally impact access to vulnerable groups, also highlighting the importance of positive interpersonal relationships. Conclusions Individual, interpersonal and healthcare factors across the patient pathway were perceived to shape access to care in unplanned IBD admissions. Potentially reducing admissions requires proactive strategies, including the integration of patient education, monitoring tools, establishment of specialist rapid-access pathways, and formal psychological support to address barriers to access.

Objectives: The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet has been associated with the risk of IBD, but its impact on clinical outcomes is uncertain. This study evaluated the association between MIND diet adherence and the risk of IBD-related surgery in a prospective cohort. Methods: This study included 2,288 participants with diagnosis of Crohn's disease (CD, n=777) or ulcerative colitis (UC, n=1,511) who completed valid WebQ 24-hour dietary recall from the UK Biobank. Dietary adherence was derived from a 15-component score based on 24-hour dietary recalls. Associations with IBD-related surgery were evaluated using Cox proportional hazards models, with nonlinear trends and examined via restricted cubic splines. Effect modification was explored in pre-specified subgroups, and multiple sensitivity analyses were conducted to assess robustness. Results: During 10.9 years of follow-up, 166 incident IBD-related surgery cases occurred. Higher MIND diet adherence was associated with reduced surgical risk. Compared with the lowest tertile of adherence, the highest tertile showed a 36% reduction in surgical risk in IBD (HR 0.64, 95% CI: 0.44-0.94, P = 0.024). Notably, this protective effect was pronounced in patients with CD, exhibiting a clear linear inverse association. In contrast, a reverse J-shaped association was observed in UC, with a steep initial decline in surgical risk followed by a plateau emerging at a MIND score of approximately 5, beyond which further adherence conferred minimal additional benefit. At the component level, higher vegetable consumption and lower intake of butter and fried foods were identified as independent protective factors against surgery. Stronger inverse associations were observed among patients with shorter disease duration and those with complicated disease behavior, including stricturing or penetrating phenotypes (all P interaction < 0.05). Conclusion: Greater MIND diet adherence is associated with reduced IBD-related surgery risk among patients with IBD and CD. These findings support the MIND diet as a feasible dietary strategy to improve IBD prognosis.

Background: Hospital incident risk scoring has long relied on two- or three-dimensional frameworks (Severity Assessment Codes or Risk Priority Numbers),even though root cause analysis standards recognize that clinical risk is multi-factorial. The obstacle has been mainly cognitive: human reviewers cannotreliably score many dimensions across high incident volumes, so richer assessmenthas not been operationalized at scale.Objective: To extend the traditional three-dimensional FMEA to an eight-dimensional patient-safety risk feature framework, to establish a multi-modellarge language model (LLM) extraction pipeline that scores these dimensionsautomatically, and to demonstrate a variance-aware integer optimization (mean-variance integer programming, MV-IP) that provides a reproducible tie-breakingrule for incident prioritization under extraction uncertainty, rather than improvedrisk coverage.Methods: An 8-dimensional framework covering harm severity, potential harm,frequency, detectability, systemic impact, vulnerable populations, regulatoryrelevance, and economic impact was applied to 213 synthetic and 196 realcurated incident narratives. Three independent LLMs (GPT-5.4, Gemini 3.1 Pro, Grok-4.1 Fast) from different provider families extracted structured risk scores.Inter-model consistency was assessed via ICC(A,1). Among coverage-equivalentselections, MV-IP minimized inter-model variance to give a reproducible prioriti-zation rule. An English-language sensitivity analysis was conducted on 31 AHRQPSNet WebM&M cases.Results: On real cases, seven of eight dimensions reached Fair or betterinter-model reliability (ICC(A,1) 0.53 to 0.83); D5 (Systemic Impact) was theexception at Poor reliability (0.275), driven by little between-case variation ratherthan by wide model disagreement. Reliability was not uniform: two dimensionswere Excellent (D1 actual harm 0.834, D8 economic impact 0.782), two Good,and three only Fair, so some dimensions are more readily extractable than others.The same anchors gave broadly similar results on English-language narratives.When deterministic top-K selection returned several equal-coverage solutions(11 on real cases, total inter-model variance 0.205 to 1.274), MV-IP selected theminimum-disagreement set, replacing ad hoc tie-breaking with an explicit rulewithout improving coverage. Bootstrap resampling found 74% to 90% of per-casevariance estimates stable despite the three-model panel.Conclusions: The eight-dimensional framework operationalizes patient-safetyrisk features that quality teams have considered only implicitly, and three inde-pendent LLM families produced reproducible scores on most dimensions ofcurated narratives. Inter-model agreement, however, measures reproducibilityrather than clinical correctness, and high agreement does not by itself establishthat a score is right; the dimensions that are reliably extractable today (notablyD6 and D8) differ from those that are not yet (D5, and to a lesser degree D4 andD7), which has direct implications for incident-reporting form design. MV-IP con-tributes a reproducible, variance-aware tie-breaking rule rather than improvedcoverage. Validation against expert-prioritized RCA lists and deployment on rawinstitutional incident reports remain the next steps toward clinical use.

Background: Preparing tumor board patient summaries is time intensive. Large-language-model based systems may automate summarization but require real-world evaluation prior to clinical use. We performed an exploratory retrospective evaluation of the Microsoft Healthcare Agent Orchestrator (HAO), deployed in a Mayo Clinic controlled staged environment, to generate tumor board-style patient summaries from retrospective Electronic Health Record (EHR) notes. Methods: HAO generated summaries for breast, hepatobiliary, and neuro-oncology tumor board cases using up to the most recent 1,000 clinical notes. Clinician reviewers evaluated outputs via REDCap surveys across perceived factuality, completeness, clarity/conciseness, temporal cohesion, comparative performance, safety, and clinical utility (0-4 Likert scale). Reviewers were permitted to query the HAO chat interface to address missing details. Automated factuality was assessed using TBFact (bidirectional entailment), reporting precision and recall against available reference summaries. Results: Among 57 survey responses from 5 different physicians, mean scores exceeded 2.8 across domains, with medians of 3 for most axes. In an exploratory comparison, oncology fellows required less time to review HAO-generated summaries than to manually generate patient summaries (mean difference 13.57 minutes per patient, p<0.001), although this difference may be influenced by prior familiarity with the same cases; 96% of survey responses indicated that HAO would save time. TBFact evaluations showed higher recall than precision across domains, consistent with broad capture of reference content alongside additional content that was not present in gold-standard summaries. Attribution was viewed favorably but showed issues with primary-source specificity and link reliability. Conclusions: In a controlled Mayo environment, HAO demonstrated moderate performance and was associated with reduced review time for tumor board preparation. These findings are promising but preliminary and do not establish clinical safety, noninferiority to manual review, or readiness for routine clinical use. Limitations, including verbosity, specialty-specific content gaps, and inconsistent attribution, highlight the need for iterative refinement and further evaluation.

Pain in pancreatic ductal adenocarcinoma (PDAC) is associated with poor survival, but whether altered pain processing carries prognostic significance is unknown. We analyzed a prospective cohort of 143 patients with PDAC who underwent pancreatic quantitative sensory testing (PQST) after diagnosis. Patients were classified as having normal pain processing (n=84), segmental hyperalgesia (n=30), or widespread hyperalgesia (n=29). Survival was measured from the date of P-QST assessment. During follow-up, 70 deaths occurred. Widespread hyperalgesia was associated with increased mortality in unadjusted Cox analysis (HR 1.96, 95% CI 1.14,3.35) and after adjustment for age, sex, tumor stage, comorbidity, opioid treatment, and body mass index (adjusted HR 2.33, 95% CI 1.30,4.15). Segmental hyperalgesia was not associated with mortality. Kaplan Meier analysis demonstrated lower survival probability in the widespread hyperalgesia group (log rank p=0.025). These findings suggest that widespread hyperalgesia, reflecting altered central pain processing, identifies a subgroup of PDAC patients at increased risk of mortality independent of conventional clinical factors.

BACKGROUND & AIMS Conventional reusable endoscopes incur significant expenses in the form of purchase, maintenance, reprocessing, and disinfection. Reprocessing is frequently ineffective even following the use of high-level disinfectants (HLDs). Disposable gastroscopy might be a strategy to decrease infectious outbreaks associated with reusable endoscope. The aim of this study was to analyze and evaluate the performance, efficiency and safety in gastroscopy observation and subsequent potential EMR procedure via the disposable gastroscope in a clinical setting. METHODS Patients who required gastroscopies and met the criteria were recruited to this prospective, open-label, non-inferiority study. After obtaining the written informed content, the enrolled subjects selected themselves independently to the disposable group or reusable group. The primary measure was to evaluate the acceptable image quality and whether the disposable endoscope devices could meet the basic clinical demands with a noninferiority margin of -8%. The second measures were to analyze and evaluate the image conditions, accepted endoscopic maneuverability, efficiency and safety of observation and advanced potential EMR procedure. Appropriate statistical methods were conducted via PASS software and SAS 9.4. A two-tailed P value < 0.05 was considered statistically significant. RESULTS A total of 90 individuals (the number of those in disposable group and reusable group was both 45) were recruited to this study. The success rate of acceptable image quality via photographing iconic anatomical sites between two groups was 100.0% (45/45, 95% confidence interval (CI): 0.9213,1.0000) and the lower limit of the 95%CI (-7.8654%, 7.8654%) was larger than the noninferiority margin of -8% (Newcombe-Wilson score method). Significant differences were showed in the measures of image conditions (image acquisition, image quality, brightness, contrast and sharpness) and accepted endoscopic maneuverability (endoscopy body rigidity). No significant differences were observed in the field of knob operation, sharp angle adaptability, and the auxiliary features including air supply, water supply and suction. In terms of efficiency, the total operating time, insertion time and withdrawal time were longer in the disposable group. The En-bloc resection rate of those observed polyps and required to EMR procedure due to relatively larger diameter (5mm-15mm) was the same 100% in both groups (26/26 vs 23/23, 95%CI: 0.8713,1.0000). Nevertheless, the procedure time of EMR for each polyp was significantly longer in the disposable group. This study showed no intraoperative bleeding, delayed bleeding, perforation or other study-related adverse events among 90 patients. No dramatic fluctuations in vital signs were showed in perioperative period. CONCLUSIONS In consideration of the efficiency, efficacy and safety evaluation, the disposable gastroscopes might represent an alternative to conventional reusable gastroscopes in routine examination and endoscopic mucosal resection.

Background: Complicated acute appendicitis carries a higher risk of postoperative morbidity relative to uncomplicated cases. It remains unclear whether surgical timing (night vs. day; weekend vs. weekday) or surgeon seniority influence short-term outcomes in this high-risk population. Methods: This was a retrospective analysis of the RIFT Turkey dataset restricted to histologically confirmed cases of complicated appendicitis who had undergone laparoscopic appendectomy. Primary exposures were surgical timing (day [n=92] vs. night [n=123]; weekday [n=172] vs. weekend [n=43]) and surgeon seniority (trainee [n=89] vs. consultant [n=126]). The primary outcome was unplanned readmission and/or reintervention within 60 days. Secondary outcomes were conversion to open surgery and length of stay (LOS) >3 days. Propensity score matching (PSM) using RIPASA score (caliper 0.05, SMD <0.1) was performed as a pre-specified sensitivity analysis for each comparison. Results: Night-time surgery was associated with higher frequencies of unplanned readmission / reintervention (12.2% vs. 6.5%; OR 1.99 [95% CI 0.74-5.35], p=0.166) and surgical conversion (9.8% vs. 3.3%; OR 3.21 [0.88-11.72], p=0.064) compared with daytime surgery, neither reaching significance. Trainee surgeons had significantly higher readmission/reintervention rates than consultants (15.7% vs. 5.6%; OR 0.32 [0.12-0.82], p=0.013). PSM-adjusted results also showed similar relationships: night vs. day (readmission OR 2.45 [0.85-7.03], p=0.09; conversion OR 2.84 [0.73-11.1], p=0.13), weekend vs. weekday (readmission OR 1.53 [0.24-9.72], p=0.65), and trainee vs. consultant (readmission OR 0.25 [0.08-0.79], p=0.013). Conclusion: Surgical timing was not significantly associated with short-term outcomes in complicated appendicitis, though night-time surgery showed a consistent trend towards higher complication rates. Surgeon seniority was the only factor independently and significantly associated with unplanned readmission and reintervention in both primary and PSM analyses, indicating the need for senior supervision during out-of-hours procedures. Keywords: complicated appendicitis; surgical timing; night surgery; weekend effect; surgeon seniority; propensity score matching; RIFT Turkey

Background. Balanced (1:1:1) transfusion of red blood cells (RBCs), plasma, and platelets is the standard of care in trauma-induced massive haemorrhage, where early coagulopathy is a defining feature. In gastrointestinal (GI) haemorrhage this physiology is non-prominent, and whether plasma and platelets provide benefit when [&ge;] 10 RBC units are required within 24 hours is unknown. Objective. To test whether a red-blood-cell-only (RBC-only) transfusion strategy is non-inferior to a balanced (Balanced) strategy for in-hospital mortality in adults meeting massive-transfusion criteria for GI haemorrhage. Design. Single-centre retrospective cohort of 559 adult massive-transfusion encounters (536 patients; 2021-2025) with a primary admitting diagnosis of upper, lower, or unspecified GI haemorrhage. Exposures were RBC-only versus Balanced (RBCs with any plasma and/or platelets). The primary outcome was in-hospital mortality, with a pre-specified 5-percentage-point (pp) non-inferiority margin on the absolute risk difference and a 3-pp sensitivity margin. Analysis used augmented inverse-probability-of-treatment weighting (AIPTW) with bootstrap inference (2,000 resamples by patient). Five pre-specified sensitivity analyses were performed. Results. 505 encounters (90.3%) received RBC-only and 54 (9.7%) received Balanced transfusion. The AIPTW risk difference for in-hospital mortality (RBC-only - Balanced) was -19.8 pp (95% CI -68.1 - -2.2 pp). Non-inferiority was demonstrated at both the primary 5-pp and the more stringent 3-pp margins. Five pre-specified sensitivity analyses, (1) a propensity-score matched cohort, (2) a complete-case model incorporating INR, (3) a broader GI diagnosis set (n = 749), (4) a first encounter per patient restriction, and (5) E-value bound analysis were concordant with the primary estimate. Conclusion. In this propensity-score-weighted cohort of adults with massive GI haemorrhage, an RBC-only transfusion strategy was non-inferior to a balanced strategy for in-hospital mortality at both 5-pp and 3-pp margins. The findings support individualized use of plasma and platelets in GI haemorrhage rather than reflexive application of the 1:1:1 trauma protocol; prospective confirmation is warranted.

Background: Frontotemporal dementia (FTD) lacks widely accessible disease-specific biomarkers. Optical coherence tomography (OCT) and OCT angiography (OCTA) may provide non-invasive measures of retinal changes associated with neurodegeneration. We conducted a systematic review and meta-analysis evaluating retinal biomarkers in FTD compared with Alzheimer disease (AD) and controls. Methods: A systematic search of PubMed and Embase was conducted through April 25, 2026 according to PRISMA guidelines. Studies evaluating OCT/OCTA biomarkers in FTD with comparator groups were included. Inverse weighted random-effects models, publication bias assessments, and meta-regressions were performed. Results: Ten studies involving 139 individuals with FTD, 87 with AD, 29 with mild cognitive impairment, 14 with TDP-43 proteinopathy, 5 with tauopathy, and 255 controls were included in the systematic review; five studies were eligible for meta-analysis. Compared with AD, individuals with FTD demonstrated significantly thinner retinal nerve fiber layer (RNFL) thickness (SMD = -0.61, 95% CI -0.98, -0.24). Compared with controls, individuals with FTD exhibited significantly thinner ganglion cell layer-inner plexiform layer (GCL-IPL) thickness (SMD = -0.55, 95% CI -1.02, -0.08), whereas pooled analyses across multiple retinal biomarkers were non-significant (SMD = -0.19, 95% CI -0.52, 0.14). RNFL thickness correlated negatively with female % in FTD and positively with age in both AD and controls. Conclusions: Individuals with FTD exhibit lower RNFL thickness than AD and lower GCL-IPL thickness than controls, suggesting retinal alterations may reflect neurodegeneration. However, larger longitudinal studies with standardized OCT/OCTA protocols are needed to determine the diagnostic and prognostic utility of retinal biomarkers in FTD

ABSTRACT OBJECTIVE: We performed a systematic review and meta-analysis (SRMA) of post-surgical outcomes, comparing chlorhexidine gluconate (CHG) versus povidone iodine (PI) for vaginal antisepsis of major gynecologic procedures. DATA SOURCES: Ovid Medline, Embase, Scopus, Embase, Cochrane, and Clinicaltrials.gov were searched between 1986 and December 2023, for studies comparing CHG with PI for vaginal antisepsis of major gynecologic operations. STUDY ELIGIBILITY CRITERIA: We included Randomized Controlled Trials (RCTs) and non-RCTs comparing CHG to PI for vaginal antisepsis of major gynecologic operations. The primary outcome was surgical site infections (SSIs) and the secondary outcome was urinary tract infections (UTIs) and vaginal irritation. METHODS: Summary estimates were calculated by fixed effects models when I2 [&le;] 25% and by random effects models when I2 > 25%. Statistical analysis was performed using RevMan 5.4.1. The protocol for this systematic review was registered on PROSPERO (ID CRD42022378101). RESULTS: Nine studies met the inclusion criteria, four of which were randomized controlled trials (RCTs). 9538 patients were included, 4300 (45%) of whom were allocated to CHG and 5238 (55%) to PI. No statistically significant difference in SSI incidence was found for vaginal antisepsis with CHG versus PI in pooled analyses (n= 9538 patients; RR 1.20; 95% CI 0.92-1.57; I2 =0%). In contrast, a significantly higher risk of UTIs was observed for vaginal antisepsis with CHG than with PI (n=6061 patients; RR 1.48 95% CI 1.03-2.14; I2 = 0%). CONCLUSION: In our SRMA, there were no significant differences in SSI risk when either CHG or PI was utilized for antiseptic vaginal preparation. Interestingly, vaginal antisepsis with PI was associated with a lower incidence of post-operative UTIs following major gynecologic surgery. Our findings support current guidelines that form of vaginal antisepsis can be used for SSI prevention. They also suggest that PI may result in fewer postoperative UTIs but further randomized studies are needed to support these findings. Key words: surgical site infection, surgical wound infection, urinary tract infection, urogynecologic surgery, Chlorhexidine, Povidone Iodine, surgical antiseptic,

Background Artificial intelligence-enhanced electrocardiography (AI-ECG) enables scalable, low-cost cardiac dysfunction screening, but existing models are annotation-intensive and predominantly adult-derived, leaving paediatric generalizability uncertain. Paediatric cohorts exhibit highly variable cardiac morphology and function compared to adults, which may be useful for learning generalizable AI-ECG models. Methods We pretrained ECG-Fyler on a predominantly paediatric, all-age cohort at Boston Children's Hospital (1992-2023), annotated with a cardiology-specific coding system (Fyler codes), and evaluated it on assessments from echocardiography (echo) and cardiac magnetic resonance (CMR) studies. We validated on an external adult cohort from Columbia University Irving Medical Center. Performance was benchmarked against several AI-ECG foundation models by AUROC across age groups, lesion types, and limited-data scenarios. Findings The pretraining cohort comprised 782,138 ECGs from 255,271 patients (median age: 10.9 years, IQR: [2.8-16.8]). Internal evaluation included 178,495 ECG-echo pairs (median age: 10.9 [3.7-17.0]) and 8,584 ECG-CMR pairs (median age: 20.7 [15.6-29.6]). External validation included 82,543 ECG-echo pairs from adults (median age: 64.0 [52.0-74.0]). ECG-Fyler improved AUROC across biventricular dysfunction and dilation tasks, with the largest gains in low-data settings. In internal validation, ECG-Fyler detected low left ventricular ejection fraction (LVEF [&le;] 40%) from only 100 fine-tuning samples (AUROC: 0.80, 95% CI: [0.78-0.80]), outperforming other models (AUROC < 0.65) and improving with additional fine-tuning (AUROC: 0.94 [0.93-0.94]). Similar improvements were observed for CMR-derived LVEF, RVEF, and ventricular dilation. In external validation on adults, ECG-Fyler exhibited an AUROC of 0.83 (CI: [0.82-0.85]) for LVEF [&le;] 40%. After fine-tuning on less than 10% of external data, LVEF [&le;] 45% performance (AUROC: 0.87 [0.86-0.88]) outperformed a fully trained, site-specific prior model (AUROC: 0.85 [0.84-0.87]). Interpretation Pretraining on richly annotated, paediatric-dominant ECGs yields models that transfer efficiently across institutions and ages, supporting AI-ECG screening and triage when labels or imaging access are limited. Funding National Institutes of Health (R01LM012973); Kostin Innovation Fund, Boston Children's Hospital

The Epic Sepsis Model version 2 (ESMv2) is a prediction model embedded into the electronic medical record used to warn clinicians which hospitalized patients are at risk for sepsis. We conducted a retrospective cohort study of 31,951 hospitalizations of 25,760 patients to compare analyses conducted at the commonly used patient-level (where a maximum prediction prior to the onset of sepsis is used to measure performance) vs novel prediction-level (where each prediction is used to measure performance). Sepsis, defined by the Sepsis 3 criteria occurred during 1,049 hospitalizations (3.3%). Patient-level analyses suggested excellent discrimination AUC 0.86; [IQR 0.85, 0.87], whereas prediction-level analyses demonstrated lower performance AUC 0.62; [IQR 0.57, 0.65]. Low estimates of the positive predictive value (14.5% at the patient level vs 4% at the prediction level) imply a high number of false alerts. Common evaluation approaches may overstate the performance of dynamic prediction models and mislead clinical decision-making.

Background: Despite the success of combination antiretroviral therapy (cART), vascular comorbidities, including cerebrovascular disease, are more prominent in people living with HIV (PLWH) compared to people without HIV (PWOH). However, quantitative assessments of cerebrovascular morphometry and their associations with cognitive outcomes in the context of HIV are still limited. In this study, we explore this missing link. Methods: Magnetic Resonance Angiography (MRA) data, blood markers, and neurocognitive assessments were collected from 73 PWOH subjects (male: 57, female: 16; age: 53 {+/-} 16) and 99 PLWH subjects (male: 66, female: 30, age: 53 {+/-} 11). Vessel morphometric features were quantified using intraCranial Artery Feature Extraction (iCafe) to investigate associations between vessel morphometry, markers of monocytes, endothelial cell activation, and cognitive performance. Results: HIV status predicted a lower total number of branches ({beta} = -0.224, p = 0.001, d = -0.517) and shorter total distal length ({beta} = -0.173, p = 0.021, d = -0.370) with a moderate effect size. Total branch number was found to be negatively associated with plasma levels of monocyte markers (sCD14: r = -0.167, p = 0.033; sCD163: r = -0.157, p = 0.045) and positively correlated with white matter cerebral blood flow (r = 0.550; p [&le;] 0.05). HIV status was the strongest predictor of overall cognitive performance in ANCOVA model ({beta} = -0.219, p = 0.006, d = -0.453). Conclusions: Our results suggest that cognitive impairment in PLWH is associated with vessel morphology metrics. Monocyte immune activation may contribute to changes in vessel morphology.

Biological aging is heterogeneous across organ systems, yet whether CT-derived abdominal aging provides prognostic value beyond routine clinical data and whether organ decomposition adds beyond a unified estimate remains untested. We developed and evaluated organ-specific and ensemble biological age models from radiomic features across five abdominal organs in 68,675 CT scans from 32,883 subjects, evaluated on alignment with chronological age of healthy subjects (nested cross validation: MAE=3.68 years, R^2=0.90). In sequential analyses restricted to adults aged 20-60 years which is the stratum of strongest BAG-disease association, ensemble biological age gaps provided incremental prognostic value beyond demographic covariates for all-cause disease and mortality (Delta C-index=0.141, 0.051) and beyond routine blood biomarkers (Delta C-index=0.048), confirming CT-derived aging captures structural information beyond laboratory markers. Organ-specific biological age added incremental prognostic value beyond ensemble selectively for focal diseases: cardiovascular (aorta, Delta C-index=0.091) and hepato-pancreatic (pancreas, Delta C-index=0.096). These findings establish a hierarchical organization of CT-derived biological aging, positioning routine CT as a source that adds prognostic value to existing clinical biomarkers.

Background Atrial fibrillation (AF) is a leading cause of stroke, cardiovascular morbidity, and mortality. Atrial myopathy, characterized by progressive metabolic, electrical, and structural changes, creates the arrhythmogenic substrate that drives AF. Defining the key drivers of atrial myopathic processes is essential for targeted therapies that can mitigate AF progression. Here we explore how reduced ERBB4 expression contributes to the development of left atrial myopathy. Methods We analyzed the Cleveland Clinic Biobank to compare left atrial ERBB4 levels in patients grouped by AF diagnosis. To investigate the impact of reduced ERBB4 levels on atrial tissue substrate, we created mouse models of cardiac-specific Erbb4 deficiency using Mlc2a (myosin light chain 2a)-Cre. Comprehensive physiological assessments were performed. Transcriptomic analyses of the left atrium were performed in an Erbb4 haploinsufficient mouse model and compared with human atrial datasets. Molecular validation of key dysregulated pathways was performed. Results We found that left atrial ERBB4 levels are reduced in patients with AF. Adult cardiomyocyte-specific Erbb4 heterozygous (Erbb4fl/+;Mlc2a-Cre) mice exhibited prolonged P-wave duration in the absence of ventricular dysfunction. Left atrial transcriptomic analysis in Erbb4 haploinsufficient mice showed upregulation of pathways related to fibrosis, apoptosis, and coagulation, and downregulation of pathways related to fatty acid metabolism and mitochondrial function, mirroring changes observed in pressure overload mouse models. A cross-species transcriptomic comparison revealed significant overlap between ERBB4-correlated gene expression and functional pathways in adult human atria and mice with Erbb4 haploinsufficiency. Validating the transcriptomic data, protein and functional assays demonstrated increased fibrosis, apoptosis, and oxidative stress in the mutant left atrial tissue. Conclusion Left atrial ERBB4 levels are reduced in AF patients. A mouse model of Erbb4 deficiency and human atrial transcriptomic analyses highlight a role for ERBB4 in supporting normal atrial metabolism while protecting against inflammation, apoptosis, and fibrosis.

Intro: Characteristics of the pulse wave transmitted through the carotid arteries are predictive of cognitive decline and cerebrovascular health in humans. This study aimed to identify risk factor trajectories in childhood, adolescence and early adulthood that are associated with forward compression wave intensity (FCWI) in the common carotid artery in adults aged 28 years. Methods: Systolic blood pressure (SBP), body mass index (BMI) and fasting blood glucose (FBG) measured at multiple time-points when participants were aged between 8-20 years were included in a trajectory analysis. At age 28 years, FCWI was measured in 402 (M=206, F=196) participants who underwent a Duplex ultrasound assessment of the common carotid artery. Statistical analysis assessed differences in FCWI between each trajectory group for males and females separately. Results: In males, four trajectory groups were identified for BMI, three for SBP, and two for FBG. In females, three trajectory groups were identified for BMI, SBP, and FG. In males, having higher BMI (P=0.006), SBP (P=0.021) and FBG (P=0.002) from ages 8-20 years was associated with greater FCWI at age 28 years. In females, no associations were found between FCWI at age 28-years and trajectory groups for BMI (P=0.185), SBP (P=0.289) or FBG (P=0.070). Conclusion: Having high BMI, SBP and FBG throughout childhood, adolescence and early adulthood was associated with higher FCWI in the carotid artery at age 28 years in males, but not females. This may have a direct impact on the etiology of cognitive decline and cerebrovascular disease in later life.

Lead is a toxic metal ubiquitous in our environment. While dramatic reductions in lead sources have paralleled equivalent decreases in lead-poisoning rates, chronic lead exposure remains a critical public health concern. Childhood lead exposure (at its lowest levels) is liked to changes in cognitive development but less is known about lead's effects on children's brain structure, especially as a result of in utero exposure. We measured prenatal and early-postnatal lead exposure in shed deciduous teeth of 448 9- and 10-year-old children (from 20 United States cities) and linked those lead levels to childhood brain structure, cognition/behavior, and neighborhood- and family-level socioeconomic characteristics. Here we show negative associations between tooth-lead levels and the thickness of the brain's cortex, particularly in regions linked to language processing. With increasing tooth-lead levels, children of lower-income (versus higher-income) families showed steeper declines in receptive vocabulary. Caregiver-reported behavioral problems exhibited similar associations. With in utero exposure linked to adverse neurodevelopmental outcomes (well before lead exposure and its risks are evaluated by healthcare professionals), prenatal screening of maternal lead levels/exposure, coupled with recommended strategies to reduce its placental transmission, may help reduce lead's effects on future generations.

Background: Conventional psychiatric screening instruments summarize symptoms within individual scales and prioritize cases with high single-instrument additive score severity. This design treats items as independent within instruments and ignores cross-instrument covariance structure, making it insensitive to respondents whose responses are distributed across multiple domains in unusual combinations that remain below threshold on every individual scale. Methods: We analyzed two cohorts spanning older and younger adults. Item prompts from depression, stress, anxiety, and sleep instruments were embedded into a shared semantic space using a pretrained sentence encoder. Principal component analysis of the item-prompt embeddings alone---with no use of respondent data at this stage---was used to construct a low-dimensional subspace retaining 80\% of variance in the item embedding matrix. Normalized participant responses were then projected into this subspace, with Jaccard-based stability analysis used as a check on dimensional robustness. Multivariate deviation from the cohort norm was quantified with Mahalanobis distance using Ledoit-Wolf covariance regularization. Candidate outliers were defined by the empirical 95th percentile of the cohort-specific distance distribution. To isolate response configurations not already captured by conventional single-instrument extreme-value logic, we excluded all outlier respondents who had endorsed any individual item at the maximum value of its Likert scale on any instrument. For the remaining outliers, anomalous components were backtracked to their original item loadings for interpretation. Results: In the older-adult Health and Retirement Study (HRS) cohort, principal component analysis of 27 item-prompt embeddings showed that a 10-dimensional subspace provided a stable representation of cross-instrument semantic structure. In the younger-adult Xinxiang cohort the corresponding stable solution was 16-dimensional. In each cohort, seven respondents remained as multivariate outliers despite falling below every single-instrument extreme-value threshold. These cases were not characterized by uniformly severe symptom scores but by unusual cross-domain response configurations that became visible only in the shared semantic covariance subspace. The response structure of the retained configurations differed across cohorts: older-adult cases more often involved weak endorsement of mood-labeled items alongside nonzero body- and sleep-related responses, whereas younger-adult cases more often involved incomplete response configurations spanning mood, sleep, stress, and self-harm-related items. Conclusions: A semantically aligned, auditable covariance subspace provides a practical tool for flagging unusual multivariate response configurations that single-instrument additive screening may not flag. The method is interpretable at the level of original item contributions. It should be understood as a hypothesis-generating screen for unusual response configurations requiring further clinical assessment, not as a diagnostic instrument. Outcome validity remains to be established by prospective study.

Hybrid mechanistic-statistical models offer interpretability and adaptability for short-term seasonal epidemic forecasting, but it remains unclear whether their accuracy depends more on increased biological complexity or on the assimilation of richer data. Using eight retrospective influenza seasons in North Carolina, we evaluate whether training on historical data and assimilating auxiliary emergency department (ED) visit data improves four-week-ahead hospital admission forecasts more than adding biological complexity (multi-subtype structure and cross-season immunity). Hierarchical Bayesian training on historical data improves accuracy by 22.4 % (95 % CI: 16.4-28.1 %), and inclusion of ED visit data yields a further 5.3 % (95 % CI: 3.0-7.6 %) improvement, whereas added biological complexity produces diminishing or null gains. We further observe a substitution effect in which ED visit data partially compensates for omitted biological structure. We deployed a simplified model variant in the 2025-2026 CDC FluSight Challenge and ranked among the top ensemble performers, supporting the robustness of Bayesian hierarchical training in real time. Together, these findings indicate that short-term forecast accuracy is driven more by historical learning and assimilating auxiliary signals than by biological fidelity, with implications for how forecasting systems should balance mechanistic complexity.

Background: Non-communicable diseases (NCDs) represent a critical public health challenge in Kenya, responsible for over 50% of inpatient admissions and 40% of deaths. While digital health tools and artificial intelligence offer promising ways to improve prevention, diagnosis, and management, little is known about how these tools are perceived and used in practice. There is limited research exploring the views and lived experiences of young people in Kenya, who are a strategic priority for NCD prevention because behavioral risk factors are established in this window, and for Community Health Providers (CHPs) who provide health services within the community. This study aims to address this gap by examining the perspectives of the burden of non-communicable diseases and the potential role of digital health technologies, including artificial intelligence, for preventing and managing these conditions in these specific populations. Methods: A qualitative research design using focus group discussions (FGDs) was employed in Nairobi (urban) and Busia (rural) counties between March and July 2024. Eight FGDs were conducted with 60 participants purposively sampled from three stakeholder groups: community health promoters (CHPs), healthcare workers (HCWs), and youth aged 18-35 years. A semi-structured guide, co-developed with a Community Advisory Board, explored beliefs about NCDs, health-seeking behaviors, lifestyle practices, and attitudes toward digital health and AI. Audio recordings were transcribed verbatim, translated where necessary, and analyzed thematically using grounded theory principles on NVivo software (v12). Results: Six consolidated themes emerged: (1) understanding of NCDs and perceived risk; (2) barriers to NCD prevention and care; (3) the role of CHPs; (4) adoption of AI tools for NCD management; (5) trust, ethics and access concerns; and (6) community-driven recommendations for AI integration. Significant barriers including stigma, economic constraints, and barriers to care were documented alongside enthusiasm for AI tools among youth and CHPs in both urban and rural areas. Conclusion: This study shows that AI tools are being used for NCD prevention and management through spontaneous community adoption. However, it emphasizes the need for culturally relevant, equitable, and community-driven solutions. Effective scaling requires the identification and bridging of digital literacy gaps, the establishment of affordable infrastructure, the protection of data privacy, and the integration of artificial intelligence tools into existing community health frameworks. This process should involve the collaboration of trusted intermediaries, such as CHPs and community leaders, to ensure successful outcomes. Future initiatives should prioritize participatory design, policy frameworks for ethical governance, and targeted capacity building to enhance acceptance and sustainability of digital health innovations in low- and middle-income country settings.