Heart

Background: Bailout cardiac surgery during transcatheter aortic valve replacement (TAVR) is uncommon but remains associated with substantial morbidity and mortality. Although registries have described its incidence and major causes, they often provide limited detail regarding device-related failure mechanisms, attempted transcatheter rescue, and the clinical pathway leading to surgical conversion. We aimed at analyzing post-marketing safety reports from the U.S. Food and Drug Administration (FDA) Manufacturer and User Facility Device Experience (MAUDE) database to characterize the mechanisms, management strategies, and reported outcomes of bailout surgery during or shortly after TAVR. Methods: We retrospectively analyzed FDA MAUDE reports received from July 1, 2016, through June 30, 2026. Eligible reports described unplanned urgent or emergent open cardiac surgery during or immediately after TAVR. Candidate reports were screened, adjudicated, and deduplicated at the clinical-event level. Events were classified by precipitating complication, transcatheter rescue, operative pathway, and reported outcome. Associations were evaluated using permutation tests, Fisher exact tests with Benjamini?Hochberg correction, adjusted regression models, and sensitivity analyses. Results: After screening 43,239 initial reports, we identified 376 bailout-surgery events, with survival status was documented in 254, including 104 deaths and 150 survivors, corresponding to 40.9% reported mortality. Valve embolization, migration, or malposition was the most frequent complication phenotype (32.4%), whereas ventricular perforation or laceration was associated with the highest mortality (74.1%; OR, 4.86; 95% CI, 1.97?11.99). Mortality differed across complication phenotypes (p<0.001) and operative pathways (p<0.001), but not across transcatheter rescue pathways (p=0.355). Valve explantation with SAVR was associated with lower reported mortality (18.9%; OR, 0.29; 95% CI, 0.12?0.69), whereas unspecified surgery or access/support alone was associated with higher mortality (56.9%; OR, 3.04; 95% CI, 1.80?5.12). Ancillary analyses identified potential platform-specific differences in complication and management patterns, while bailout timing was not independently associated with mortality after adjustment. Conclusions: In this MAUDE analysis, bailout cardiac surgery after TAVR was most commonly precipitated by valve embolization, migration, or malposition, whereas ventricular perforation or laceration was associated with the highest reported mortality. Outcomes differed across complication and operative pathways but not across transcatheter rescue strategies or bailout timing after adjustment. These findings identify clinically relevant post-marketing safety signals but should not be interpreted as incidence estimates, comparative device risks, or causal treatment effects.

Background: A dose finding trial evaluated safety and adherence for pre-cardiac surgery administration of sodium valproate. Integrated multi-omics analyses of myocardium were used to characterise mechanisms underlying the treatment effects. Methods: Adults undergoing cardiac surgery were randomised 1:1:1:1 with concealed allocation to no treatment (Controls), sodium valproate 15mg/kg/day for 1-2 weeks, 15mg/kg/day for 4-6 weeks, or 25mg/kg/day for 4-6 weeks pre-surgery. The primary analysis evaluated adherence and toxicity. Myocardial injury was defined by high sensitivity serum troponin at 24 hours post-surgery. Single-nucleus Assay for Transposase-Accessible Chromatin with sequencing (snATACseq) and single nuclei RNA sequencing (snRNAseq) of myocardial biopsies collected at surgery assessed treatment effects on chromatin accessibility and gene expression. Candidate mechanisms were validated in in vitro. Results: The analysis cohort included 42 participants enrolled between January 2020 and August 2024. Non-compliance (38%) was highest with longer and higher dosing. Sodium valproate 15mg/kg/day for 1-2 weeks had the highest levels of complete treatment adherence (70%), with 20% experiencing moderate/severe drug related adverse effects. An as-treated analyses demonstrated reductions in troponin release in participants receiving Valproate[&le;]14 days. Myocardial biopsies from trial participants demonstrated activation of hormetic p53 and Akt-GSK-3{beta} ferroptosis protection pathways. Treatment effects were not attributable to chromatin accessibility. Treatment >14 days resulted in a heart failure phenotype with suppression of ferroptosis protection pathways, endothelial mesenchymal transition, and increased myocardial injury. Conclusions: Sodium valproate 15mg/kg/day for [&le;]14 days pre-surgery is well tolerated in adults awaiting cardiac surgery. This treatment was associated with upregulation of ferroptosis protection pathways and reductions in myocardial injury.

Background: Percutaneous mechanical circulatory support (pMCS) is increasingly used in critically ill patients, yet its value in relation to cost and outcomes remains unclear. We evaluated national variation in utilization, outcomes, and cost, and introduced a value of care framework integrating risk-adjusted outcomes and expenditures. Methods: We performed a retrospective cohort study using the National Inpatient Sample to identify non-elective hospitalizations of critically ill patients undergoing intra-aortic balloon pump (IABP) or percutaneous left ventricular assist device (pLVAD) placement using ICD-10 codes. Multivariable logistic regression and generalized linear models were used to estimate expected outcomes and costs. Observed-to-expected (O/E) ratios were calculated, and a value index was derived to compare procedural strategies. Results: A total of 57,910 weighted hospitalizations were included (IABP 78%, pLVAD 22%). In-hospital mortality exceeded 30% across regions. Significant regional variation was observed, with the West demonstrating the highest costs and the Midwest the lowest (p<0.001). Mean hospital charges were higher for pLVAD compared with IABP ($403,731 vs $320,769). Both strategies achieved outcomes better than expected after risk adjustment (O/E 0.92); however, costs were higher than expected for both, with greater relative cost inflation observed for IABP (O/E 1.41) and higher absolute costs for pLVAD. In value-of-care analysis, IABP was associated with lower cost and comparable outcomes, while pLVAD demonstrated higher cost without proportional outcome improvement. Conclusion: Substantial variation exists in the cost, outcomes, and value of pMCS strategies. While both IABP and pLVAD achieve favorable risk-adjusted outcomes, pLVAD is associated with higher costs without commensurate clinical benefit.

Contemporary national-scale electronic health record (EHR) trends in documented acute myocardial infarction (AMI) rates during the high-sensitivity cardiac troponin (hs-cTn) and Type 2 myocardial infarction (T2MI) era are not well characterized. We conducted a serial cross-sectional analysis of U.S. adults aged 18 years in Epic Cosmos from 2016-2024, encompassing 821,859,867 patient-years. Age- and sex-standardized AMI diagnosis rates increased 75.7%, from 343.1 to 602.7 per 100,000 patients. This increase was predominantly driven by T2MI, which increased 133.8% from 99.9 per 100,000 in 2018 to 233.4 per 100,000 in 2024; NSTEMI increased 13.8% while STEMI decreased 4.1%. Annual hs-cTn-tested encounters increased 34.5-fold from 2017 through 2024. The proportion of tested encounters associated with any AMI remained relatively stable after 2021, whereas T2MI continued to increase and surpassed NSTEMI in 2024 as the most frequently diagnosed AMI subtype per hs-cTn-tested encounters. Males had higher absolute AMI rates across all age groups, although relative increases were greater among females. Documented AMI epidemiology shifted substantially toward T2MI during expanding hs-cTn utilization, underscoring the need for evidence-based approaches to the evaluation and management of T2MI.

Background: High-sensitivity cardiac troponin (hs-cTn) assays enable safe early discharge of patients at very low risk for myocardial infarction. We previously developed a single-sample rule-out pathway using the ARCHITECT hs-cTnI assay to risk stratify patients with suspected acute coronary syndrome. In a secondary analysis of the POC-ET (Point of Care Evaluation of High-sensitivity Cardiac Troponin) study, we evaluated performance of risk stratification with the Alinity hs-cTnI assay. Methods: Patients presenting with possible myocardial infarction in the POC-ET (NCT05665127) study were included. The primary outcome was type 1, 4b or 4c myocardial infarction or cardiac death at 30 days. Cardiac troponin I (cTnI) was measured in stored materials using the ARCHITECT and Alinity hs-cTnI assays. The sex-specific 99th percentile upper reference limit (URL) are 34 ng/L in men and 16 ng/L in women for both assays. Agreement was assessed with Bland-and-Altman limit of agreement method, Passing Bablok regression, and Pearson's correlation coefficient. Distributions of presentation measurements were compared with Kolmogorov-Smirnov test. Performance was evaluated in the overall population and prespecified subgroups. The negative predictive value (NPV) and sensitivity were determined and proportion of patients identified as low, intermediate, and high risk were calculated and modelled using ordinal logistic regression. Results: In 986 patients (60 [51-70] years, 38% female), 78 (7.9%) had a primary outcome. Strong agreement was found in the raw cTnI measurements (99% samples within the Bland-Altman limit of agreement; correlation coefficient r: 0.967 (95% CI 0.964-0.969, P<0.001); Passing Bablok regression: slope 1.12 [1.11-1.13], intercept -0.16 [-0.18 to -0.13]). At presentation, distributions of cTnI measurements by the two assays were similar (P=0.810). Both assays showed comparable diagnostic performance using a risk stratification threshold of <5 ng/L and the sex-specific diagnostic threshold, with the same NPV (Alinity 100 [99.7-100]% versus ARCHITECT 100 [99.7-100]%) and sensitivity (Alinity 100 [97.3-100]% versus ARCHITECT 100 [97.3-100]%). Similar proportions of patients stratified as low- (Alinity 67% versus ARCHITECT 67%), intermediate-risk (23% versus 24%) and high-risk (10% versus 9%) at presentation with minor reclassification. Similar efficacy was observed across subgroups stratified by sex, age, history of myocardial infarction, renal function, and symptom duration. Conclusions: The Alinity hs-cTnI and the ARCHITECT hs-cTnI assays can be used interchangeably in the assessment of suspected myocardial infarction with comparable safety and efficacy.

Background. Durable mitral isthmus (MI) block remains challenging in persistent atrial fibrillation (PeAF) ablation. Recent epicardial vein of Marshall (VoM) recordings have shown incomplete MI transmurality and time-dependent conduction recovery after pulsed field ablation (PFA). Whether systematic VoM ethanol infusion (VoM-EI) followed by focal PFA provides stable acute MI block remains unknown. **Objectives.** To assess the incidence, timing, and procedural implications of early MI conduction recovery after systematic VoM-EI followed by focal Sphere-9 PFA. Methods.In this prospective single-center study, 55 consecutive patients undergoing first ablation for symptomatic PeAF with planned MI ablation were screened. VoM-EI was systematically attempted before left atrial access and successfully performed in 51 (92.7%), who constituted the study cohort. Pulmonary vein isolation, roof-line, and MI ablation were performed with the Sphere-9? lattice-tip catheter. After bidirectional MI block, conduction was systematically reassessed during a standardized 30-minute waiting period. Results.Mean age was 70.3 {+/-} 8.2 years, and 36 patients (70.6%) were men. Initial bidirectional MI block was achieved in 50/51 patients (98.0%). During the waiting period, conduction recovered in 9/50 (18.0%; 95% CI, 9.8%-30.8%), at a median of 16 minutes (IQR, 10-20; range, 8?23). Six of 9 patients with recovery (66.7%) required targeted coronary sinus (CS) ablation. Block was restored in all 9, yielding a final block rate of 50/51 (98.0%). Median procedure duration was 82 minutes (IQR, 73-95), with no major complications. Conclusions. Immediate bidirectional MI block was not synonymous with stable block. Despite systematic VoM-EI followed by focal Sphere-9 PFA, conduction recovered in approximately one in five patients, including beyond 20 minutes, and two thirds required targeted CS ablation. These findings support standardized 30-minute reassessment and targeted CS interrogation rather than reliance on immediate block. Chronic invasive remapping is required to determine whether this strategy improves long-term MI block durability.

Background: Unstructured biomedical data, such as echocardiography reports, are rich in information but time consuming to analyze at scale. Rule-based, regular expression-driven terminology mapping can only extract individual variables while large language models (LLMs) offer scalable and clinically meaningful interpretations of heterogeneous disease processes. Right ventricular dysfunction (RVD) is an example of a multifactorial disease state in which key structural and physiologic features are captured both narratively and in structured fields, making it an ideal test case for evaluating whether LLMs can recover complex phenotypes that rules based methods routinely miss. Purpose: To compare an LLM-based extraction method to a conventional rules-based schema for identifying and phenotyping echocardiographic features associated with RVD in a large TTE dataset. Methods: MIMIC-III NOTE2NUM echocardiography reports (n = 45,794) were analyzed using GPT-4o-based LLM extraction deployed within a secure health system enclave and were benchmarked against echocardiographic measurements defined in the MIMIC-III dictionary schema. In MIMIC-III, PH was recorded qualitatively (mild/moderate/severe) based on tricuspid regurgitant (TR) jet velocity and then re-coded as present vs. absent. LLM based extraction defined RVD as (1) RV structural abnormality (>= 1 of hypertrophy, dilation, or wall hypo-/akinesis) or (2) RV pressure/volume overload (>= 2 of the following: estimated right atrial pressure > 8 mmHg, TR jet velocity > 2.8 m/s, fractional area change < 35%, tricuspid annular planar systolic excursion < 17 mm, S' < 9.5 cm/s, or E/e' > 14), with PH defined as estimated pulmonary artery systolic pressure > 35 mmHg or qualitative documentation of PH. Results: LLM extraction identified PH in 15,394 (33.6%), RV pressure/volume overload in 14,449 (31.6%), and RV structural abnormalities in 11,955 (26.1%). Co-occurrence was common: overload + structural changes in 9,380 (20.5%), overload + PH in 9,756 (21.3%), structural changes + PH in 6,183 (13.5%), and all three in 5,620 (12.3%). Using the MIMIC-III dictionary schema, PH prevalence was similar (15,371; 33.6%), but RV overload fields were captured less often (pressure overload 1,357 [3.0%], volume overload 1,128 [2.5%], pressure + volume overload 1,093 [2.4%]; any overload field 3,578 [7.8%]), and RV pressure/volume overload with PH was identified in only 731 (1.6%). Conclusions: LLM-based extraction outperforms rules-based schemas for identifying complex disease states not defined by any single variable. By synthesizing multifactorial signals, LLMs can phenotype RVD with higher fidelity and support population-level assessment. Further validation using multimodality imaging, invasive hemodynamics, and clinical outcome data is needed.

Background and Aims: Epicardial adipose tissue (EAT) has emerged as an important cardiovascular biomarker that reflects both inflammatory and cardiometabolic risk. EAT volume and density vary significantly across populations, yet there is a lack of multicenter studies investigating the predictive value of population-specific EAT percentiles. Methods: In this multicenter study, we retrospectively analyzed low-dose computed tomography correction scans from 42,842 patients undergoing myocardial perfusion imaging. A derivation cohort of 15,082 patients was used to establish sex- and age-specific nomograms for EAT density and EAT volume indexed to body surface area. Percentile-based thresholds were tested for outcome prediction in a validation cohort of 27,760 patients. For clinical implementation, we developed an online EAT percentile calculator. Results: Percentile curves demonstrated increased BSA-indexed EAT volume and decreasing EAT density with age. Over a median follow-up of 3.6 years (IQR: 1.83 - 5.14), 4,956 patients experienced a nonfatal myocardial infarction or death. In multivariable Cox models, patients above the 95th sex- and age-specific percentile had significantly worse outcomes for BSA- indexed EAT volume [adjusted hazard ratio 1.30, 95% CI: 1.14 - 1.49, p < 0.001] and EAT density [adjusted hazard ratio 1.7, 95% CI: 1.51 - 1.92, p<0.001] when compared to patients below the 50th percentile (p<0.001). Conclusion: Age- and sex-specific EAT percentiles provide a clinically interpretable framework for contextualizing automated EAT measurements and identifying patients at increased cardiovascular risk. EAT density was a stronger prognostic marker and identified elevated risk even among patients with normal BMI, supporting its potential to provide information beyond conventional anthropometric assessment.

BACKGROUND The optimal antiplatelet regimen in patients with acute coronary syndrome (ACS) and multivessel disease undergoing drug-coated balloon (DCB) angioplasty remains unclear. METHODS This was a prespecified subgroup analysis of the REC-CAGEFREE II trial, which was conducted at 41 sites in China and randomized 1948 exclusively DCB-treated participants with ACS to stepwise dual antiplatelet therapy (DAPT) de-escalation or standard DAPT. The primary endpoint was net adverse clinical events (NACE; including all-cause death, stroke, myocardial infarction, revascularization, and BARC type 3 or 5 bleeding) at 12 months. Participants were stratified into multivessel and single-vessel subgroups according to angiographic characteristics. RESULTS Overall, 720/1948 (37.0%) patients had multivessel disease. The multivessel subgroup was associated with a significantly higher risk of NACE compared with the single-vessel subgroup (12.5% versus 6.7%, HR IPTW:1.84, 95%CI:1.35-2.51, P<0.001). No significant interaction was observed between vessel status (multivessel or single-vessel) and treatment allocation with respect to NACE (Pinteraction=0.542). In the multivessel subgroup, NACE occurred in 44/368 (12.1%) and 45/352 (12.9%) in the stepwise de-escalation and standard DAPT groups (HR IPTW:0.95, 95%CI:0.62-1.75, P=0.818), respectively. In the single-vessel subgroup, NACE occurred in 43/607 (7.1%) and 39/621 (6.3%) in the stepwise de-escalation and standard groups (HR IPTW:1.12, 95%CI:0.72-1.70, P=0.611), respectively. For the prespecified hierarchical secondary endpoint, win ratio analyses yielded more wins for stepwise de-escalation in both subgroups. CONCLUSIONS Among patients with ACS undergoing DCB-only angioplasty, those with multivessel disease were associated with a higher risk of NACE than those with single-vessel disease. Stepwise DAPT de-escalation and standard DAPT exhibited similar risk-benefit profiles in both subgroups.

BACKGROUND People with type 2 diabetes mellitus (T2DM) are at higher risk of cerebral small vessel disease and left ventricular hypertrophy (LVH), potentially contributing to cognitive decline and dementia. We aimed to describe brain volume and cognitive trajectories over 2 years in a cohort of people with T2DM and to determine whether LVH causes increased brain atrophy and cognitive decline. METHODS Diabetes and Dementia (D2) study is a multicentre observational cohort study in Melbourne, Australia. Participants aged >50 years were recruited via 2 hospital outpatient clinics, 3 private clinics, and study advertisements. Participants with pre-existing cognitive impairment, life-limiting medical illness, and severe chronic renal impairment were excluded. Participants attended study visits for brain MRI, transthoracic echocardiography (TTE), and cognitive testing at baseline and 2 years. The exposure was LVH determined on baseline TTE. Pre-specified outcomes were total brain volume (TBV) change and cognitive decline (z-score change?-1 in any cognitive domain) over 2 years. Regression analyses examined associations between baseline variables and outcomes. A causal inference approach was utilized using inverse probability of treatment weighting to standardize for confounding covariates, excluding participants for non-positivity on age and baseline TBV. RESULTS Participants were recruited 20May2016 to 20March2020: 2378 screened, 702 eligible, 196 consented, 150 baseline and 123 2-year assessments with complete MRI, TTE, and cognitive data (17.4% attrition). At baseline, LVH was associated with female sex, older age, lower educational attainment, lower mood, hypertension, obesity, beta-blocker use, and smaller TBV. Participants with baseline cognitive impairment exhibited greater brain atrophy. Lower educational attainment, hypertension, and lower baseline cognitive scores were associated with cognitive decline. Causal inference analysis included 62 participants with no LVH (20(32%) women; mean [SD]=66.9[5.9] years), and 31 with LVH (17(55%) women, 67.4[5.4] years). LVH caused lower TBV change: standardized mean difference (95% CI) 6.3 (0.1, 12.5) cm3, P=.048. LVH had no effect on cognitive decline. CONCLUSIONS Brain atrophy and cognitive decline were associated with baseline cognitive impairment. LVH caused less brain atrophy and cognitive decline in people with T2DM. We conclude that guideline-directed LVH therapies such as beta-blockers have both cardioprotective (remodelling) and neuroprotective effects. TRIAL REGISTRATION ACTRN12616000546459 UTN: U1111-1181-6659

Background: Primary malignant cardiac tumors (PMCTs) are rare and histologically heterogeneous. Objective: To compare demographics, specific ICD-O-3 morphologies, first-course treatment patterns, annual registered case counts, and unadjusted overall survival between soft-tissue and hematologic PMCTs. Methods: We identified 730 PMCT cases diagnosed from 2000 to 2021 in SEER 18 (ICD-O-3 topography C38.0). Histologic lineage was assigned from ICD-O-3 morphology. Comparative analyses included soft-tissue (n=458) and hematologic (n=212) tumors. First-course variables were primary-site surgery, chemotherapy (yes versus no/unknown), and radiotherapy (radiation versus none/unknown). Groups were compared with chi-square tests. Overall survival was estimated with Kaplan-Meier methods; follow-up was truncated at 120 months. Results: Soft-tissue PMCTs occurred predominantly at ages 45-64 years (67.9%), whereas hematologic PMCTs occurred predominantly at age [&ge;]65 years (63.2%; p<0.001). Men comprised 59.9% of hematologic and 49.3% of soft-tissue cases (p=0.014). The leading soft-tissue morphology was hemangiosarcoma/angiosarcoma (ICD-O-3 9120/3; 201/458, 43.9%); synovial sarcoma accounted for 20/458 cases (4.4%). Diffuse large B-cell lymphoma, NOS, accounted for 131/212 hematologic tumors (61.8%). Any primary-site surgery was recorded in 66.6% of soft-tissue versus 15.6% of hematologic cases (p<0.001). Chemotherapy was recorded in 67.5% versus 51.1% (p<0.001), and radiotherapy in 9.0% versus 20.5% (p<0.001). In exploratory Kaplan-Meier analyses, hematologic patients with recorded chemotherapy had higher unadjusted 120-month overall survival than those without recorded chemotherapy (42.0% versus 12.2%; log-rank p=7.5x10-). Radiation-associated survival differences were not statistically significant in either lineage. Conclusions: Soft-tissue and hematologic PMCTs have distinct age distributions, named histologies, and first-course treatment patterns in SEER. These findings describe registry coding and do not establish treatment effectiveness or population incidence.

Background: Severe aortic stenosis is associated with systemic and splanchnic hemodynamic disturbances that may alter gut microbial metabolism and host inflammatory responses. Objectives: We aimed to determine whether TAVI remodels the gut microbiome-derived metabolome and whether post-procedural SCFA dynamics are associated with the inflammatory cytokine response. Methods: We conducted a prospective paired single-center study of patients undergoing elective TAVI at Bern University Hospital. Stool and blood samples were collected before and three months after the procedure. Gut microbial composition was profiled by full-length 16S rRNA sequencing, circulating short-chain fatty acids (SCFAs) by targeted metabolomics, and inflammatory mediators by multiplex cytokine analysis, and integrated with hemodynamic and clinical data. Results: Forty patients were enrolled. Following TAVI, microbial richness declined without significant restructuring of overall community composition. In contrast, circulating SCFA profiles were significantly remodeled, driven by selective reductions in butyrate and isovalerate. A greater decline in circulating butyrate was inversely associated with IL-18 elevation (rho=0.668, p<0.001, n=36), independent of aortic valve calcification burden, hemodynamic improvement, and cardiovascular medications. Baseline isovalerate was nominally associated with 1-month adjudicated adverse events (AUC 0.77; exploratory). Conclusions: TAVI is associated with selective changes in gut microbiome-derived metabolic output rather than broad alterations in microbial community structure. Declining circulating butyrate identifies a gut-metabolite-immune axis linked to IL-18 dynamics and represents a potential biomarker of inflammatory recovery following valve intervention.

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.

Background: Systematic reviews of clinical prediction models increasingly include studies using artificial intelligence (AI) and machine learning (ML) methods alongside traditional multivariable regression approaches. A previously published Excel tool enabled standardised data extraction using the CHARMS checklist and risk of bias assessment using PROBAST. The recent publication of the PROBAST+AI framework, which distinguishes the assessment of model development quality from the assessment of model evaluation risk of bias and assesses applicability in both parts, necessitates an updated digital instrument applicable across prediction modelling methods. Methods: We updated an open-access Excel tool to incorporate the full PROBAST+AI framework. The updated template incorporates structural separation between assessment of model development quality and model evaluation risk of bias, with applicability assessed in both parts. It also incorporates updated signalling questions, including those addressing methodological issues particularly relevant to AI/ML, and automates the generation of summary tables and graphical displays. Results: The updated tool (CHARMS & PROBAST+AI Template) contains 11 worksheets and supports data extraction and appraisal for up to 30 prediction models. Dedicated, linked worksheets enable separate assessment of model development and model evaluation, with Domain 4 distinguishing among Apparent, Internal, and External evaluation settings. Key updates include dedicated assessments for predictor pre-processing, class imbalance handling and recalibration, data leakage prevention, and replication of the full model development pipeline within resampling procedures. Automated sheets dynamically format tables and summary charts covering PROBAST+AI parts. Conclusions: The CHARMS & PROBAST+AI Excel template provides a standardised, user-friendly, and rigorous digital framework for systematic reviewers appraising traditional statistical and AI-driven clinical prediction models.

Background: Fibrosis, characterised by excessive accumulation of collagen type I (COL1), is a common feature of chronic diseases, including liver diseases (LDs), chronic kidney disease (CKD) and heart failure (HF). COL1 degradation products can be detected in urine by proteomics/ peptidomics analyses and may serve as non-invasive biomarkers of fibrosis. We aimed to identify a common molecular signature of fibrosis across these diseases that may ultimately guide interventions to slow disease progression and prevent organ damage. Methods: Using capillary electrophoresis coupled to mass spectrometry (CE-MS), naturally occurring COL1 degradation products (peptides) in the urine of patients with fibrotic disease, LDs (n=127), CKD (n=263) or HF (n=187), were investigated and compared with the same number of matched controls. Disease-associated COL1 peptides were identified separately for each condition, and peptides showing consistent associations across the three diseases were selected to define a common fibrosis signature. A support vector machine model based on the selected peptides was developed and validated in independent cohorts of patients with LDs (n=110), CKD (n=93), HF (n=32) and controls (n=643). Results: We identified a common fibrotic signature consisting of 50 COL1 degradation products, mainly downregulated in fibrosis. A model based on these peptides achieved a strong performance, with an area under the receiver operating characteristic curve (AUC) of 0.935 (95% confidence interval (CI) 0.917-0.953, p<0.0001) in an external validation cohort comprising pooled disease groups (LDs, CKD, and HF) and controls. Performance was maintained in LDs, CKD and HF, with AUCs of 0.917 (95% CI 0.890-0.944, p<0.0001), 0.951 (95% CI 0.931-0.971, p<0.0001) and 0.950 (95% CI 0.903-0.997, p<0.0001), respectively. The model scores were significantly associated with fibrosis stage in LDs (p=0.0097) and with interstitial fibrosis and tubular atrophy in CKD (p=0.045). Conclusion: A model of urinary COL1 peptides captures a shared collagen degradation signature across organs and diseases, enabling the non-invasive assessment of fibrosis irrespective of its origin. As these peptides exclusively reflect collagen degradation, the findings suggest impaired collagen degradation as a driver in fibrosis. Future clinical studies are warranted to evaluate the utility of this model for early fibrosis detection and earlier implementation of anti-fibrotic interventions.

Background Excess sodium intake is a major contributor to the global burden of disease, but its role in infection susceptibility remains largely unexplored. Although sodium has been considered antimicrobial, high sodium intake may impair immune responses and host defense. We therefore examined whether habitual addition of salt to foods was associated with the long-term risk of incident infections. Methods We included 360,314 UK Biobank participants without prior hospital-treated infections. Frequency of adding salt to foods was self-reported at baseline. Incident infections were identified using ICD-10 codes from hospital and death records. Associations were assessed using multivariable Cox regression. Results Over a median follow-up of 14.3 years, 84?146 participants developed hospital-treated infections. Compared with those who never or rarely added salt, participants who sometimes, usually, and always added salt had progressively higher risks of incident infections (adjusted hazard ratios 1.04 [95% CI 1.03?1.06], 1.08 [1.06?1.11], and 1.29 [1.26?1.33], respectively; p for trend <0.001). The association remained robust across models and broadly consistent across pathogen types and infection sites. The association appeared stronger among participants with normal weight (P for interaction <0.001). Conclusions Habitual addition of salt to foods was associated with a dose-dependent higher risk of hospital-treated infections in this large prospective cohort. These findings extend the potential health relevance of excess sodium intake beyond cardiometabolic disease and suggest that lower habitual salt intake may have implications for infection risk. Further studies are needed to replicate these findings and clarify the underlying immunological mechanisms.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and a major cause of cardioembolic stroke. Although polygenic risk scores (PRS) are well characterized to quantify inherited susceptibility for AF, they provide limited insight into the pathways and tissues underlying genetic risk, which are critical to uncover for individual risk prediction. In this study, we develop a pathway-level multi-omics representation learning framework that converts individual genetic profiles into interpretable biological features by integrating GWAS-derived pathway burden scores with tissue-specific transcriptomic pathway signals. We constructed machine learning models to assess population-level AF risk prediction performance across genomic and transcriptomic tissue contexts; the pathway-based global attention models substantially improved risk prediction performance over PRS and other baselines (AUROC improved from 0.601 to 0.738). Transformer and graph neural network frameworks then assessed individual-level pathway interpretability, revealing heterogeneous contributions from electrical signaling, cardiac development, and DNA repair pathways to AF risk. This added interpretability highlights the potential of this pathway approach to enable more mechanistically informed risk stratification than static PRS by capturing underlying heterogeneity. To independently assess whether prioritized pathways reflected cardiac regulatory biology, we compared pathway rankings with transcriptional effects predicted by the AlphaGenome foundation model. Variants in highly ranked pathways showed significantly greater predicted effects on expression in atrial and ventricular tissues (FDR = 0.032) relative to controls, providing orthogonal evidence that the model identifies biologically relevant mechanisms. Overall, this work reframes polygenic risk from a single measure of susceptibility to tissue-informed pathway mechanisms, providing a framework for interpretable genomic stratification in complex diseases.

Background. Cardiovascular-outcomes trials are lengthy, costly, and associated with substantial uncertainty prior to readout. In-silico trial simulation using real-world data (RWD) has emerged as a potential tool to support earlier decision-making; however, evidence of prospective predictive validity, generated prior to trial result disclosure, remains limited. Methods. We applied a semi-mechanistic machine learning framework integrating real-world patient data with biologically informed drug representations to prospectively simulate the VESALIUS-CV trial evaluating evolocumab versus placebo. The simulation model was trained on a combination of patient-level real-world data and a drug-centric knowledge graph and validated for both patient-level and trial-level retrospective predictive performance. The model was then used to simulate VESALIUS-CV before public disclosure of trial results, using a locked model and prespecified eligibility criteria and primary endpoint aligned with the clinical protocol. A patient-level time-to-event model was used to generate virtual trial arms, from which cumulative incidence curves, hazard ratios, confidence intervals, and p-values for major adverse cardiovascular events (MACE) were estimated. Results. In retrospective validation, the model demonstrated strong patient-level discrimination, with time-dependent ROC-AUC values ranging from 0.80 to 0.90 across follow-up horizons. For trial-level validation, 22 randomized cardiovascular-outcomes trials were simulated, and hazard ratios for 3-point MACE across 24 between-arm comparisons showed consistent directional agreement and quantitative correlation with published results such that the model accurately predicted trial success, achieving an F1 score of 0.83, with precision of 0.79 and sensitivity of 0.89. In a fully prospective application, the simulation predicted a statistically significant reduction in 3-point MACE with evolocumab versus placebo, estimating a hazard ratio of 0.78 (95% CI, 0.70-0.87) at 54 months. These predictions were consistent with the subsequently reported VESALIUS-CV results, which demonstrated a hazard ratio of 0.75 (95% CI, 0.65-0.86) at 55 months of median follow-up. Conclusions. In a fully prospective setting, a RWD-driven, AI-based simulation accurately predicted the direction, magnitude, and temporal dynamics of treatment effects observed in the VESALIUS-CV trial. These results demonstrate that in-silico trial simulation can anticipate clinical outcomes in the prospective setting, supporting its use as a complementary tool for early decision-making, trial design optimization, and de-risking in cardiovascular drug development.

Objectives To analyse the long-term effects of a cruciate ligament (CL) injury on health and socioeconomic outcomes. Methods We used a comprehensive national injury insurance database to identify CL injuries occurring in New Zealand between 2009 and 2022, and employed a doubly robust staggered difference-in-differences research design to identify the effects of these injuries on outcomes up to 10 years after injury. The outcomes of interest were healthcare use (hospitalisations, emergency department visits, medications, knee replacement surgery for osteoarthritis), associated healthcare costs, and labour market outcomes (employment rates, income, and government benefit payments). Results We identified 61 344 CL injuries for inclusion in the analysis. Over 10-year follow-up, a CL injury resulted in increased healthcare use (0.6 more hospitalizations [95%CI 0.4 to 0.7], 1.7 more days spent in hospital [95%CI 1.3 to 2.1], 0.4 more emergency department visits [95%CI 0.3 to 0.6], 2.5 more outpatient visits [95%CI 1.8 to 3.2], and 4.7 more medications dispensed [95%CI -1.8 to 11.2]) and public healthcare costs ($7 537; 95%CI 5 888 to 9 186), reduced income (-$6 060; 95%CI -11 644 to -475), and increased benefit payments ($1 152; 95%CI 542 to 1 761). Conclusion CL injuries have long-term impacts on healthcare use and socioeconomic outcomes. Strategies to reduce the incidence of CL injuries have the potential to realise large health and economic benefits.

Background: Inequalities exist for many health outcomes, but there is limited evidence regarding menstrual symptoms despite their importance for health and wellbeing. We aimed to investigate inequalities in menstrual symptoms according to socioeconomic position and childhood adversity. Methods: In two generations (G0 mothers and G1 offspring) from the Avon Longitudinal Study of Parents and Children (ALSPAC), a UK prospective cohort study, we examined associations of multiple indicators of socioeconomic position (SEP) and adverse childhood experiences (ACEs) with menstrual symptoms (pain, abnormal uterine bleeding, and premenstrual syndrome (PMS) measured 3-8-years post-birth in G0 and 17-21-years-old in G1), using multivariable logistic regression. Samples ranged from 4,828 to 9,335 G0 participants and 1,288 to 2,757 G1 participants depending on the exposure-outcome association. Missing data were addressed using multiple imputation and inverse probability weighting. Results: Financial difficulties were associated with greater odds of menstrual pain (G1 OR 1.41; 95% CI 1.07, 1.86: G0 OR 1.55; 95% CI 1.36, 1.76) and irregular cycles (G1 OR 1.60; 95% CI 1.12, 2.29: G0 OR 1.48; 95% CI 1.27, 1.72) in both generations, as well as with short/long cycle lengths in G0 only. Lower education and manual social class were also associated with these three menstrual symptoms in at least one generation. Conversely, higher SEP was associated with PMS in both generations. Higher cumulative ACEs were consistently associated with menstrual pain (4+ compared to none: G1 OR 2.15; 95% CI 1.48, 3.11: G0 OR 1.52; 95% CI 1.29, 1.80) and irregular cycles (G1 OR 1.92; 95% CI 1.20, 3.09: G0 OR 1.54; 95% CI 1.26, 1.87) but not cycle length. Lower parental education, financial difficulties, and cumulative ACEs were associated with heavy bleeding in G1 offspring only, whereas financial difficulties, own manual social class, and cumulative ACEs were associated with prolonged bleeding in G0 mothers only. Higher cumulative ACEs were also associated with PMS in G1 offspring only. Conclusions: We found evidence of inequalities according to socioeconomic disadvantage and childhood adversity for multiple menstrual symptoms, although some associations were only observed in one generation. Findings suggest that menstrual symptoms are disproportionately experienced by socially and socioeconomically disadvantaged women.