The Journal of Heart and Lung Transplantation

Background: Bicuspid aortic valve anatomy increases procedural complexity during transcatheter aortic valve implantation, yet outcome-oriented anatomic risk stratification for intraprocedural events remains limited. Aims: We aimed to develop and externally validate an anatomy-driven score to predict a composite intraprocedural endpoint, assessed at exit from the procedure room, in bicuspid transcatheter aortic valve implantation. Methods: Consecutive patients with bicuspid aortic valve undergoing transcatheter aortic valve implantation were analysed in a development cohort (N=793) and a multicentre external validation cohort (N=134). Candidate preprocedural computed tomography and echocardiographic variables were prespecified by expert consensus and refined using penalized regression with bootstrap stability selection within a domain-constrained framework. A five-indicator score (0 to 10 points) was derived from routine imaging metrics spanning the ascending aorta, aortic root, valve complex, annulus-outflow tract unit, and left ventricle, and tested using multivariable logistic regression. Results: The composite intraprocedural endpoint occurred in 101/793 (12.7%) patients in the development cohort, with stepwise increases across risk strata (7.2%, 13.3%, 30.6%; p<0.001). Each 1-point increase was independently associated with higher risk (odds ratio 1.32; 95% confidence interval 1.18-1.47). A similar gradient was observed in external validation (3.1%, 10.8%, 50.0%; p=0.012; odds ratio 1.55 per point), with a C-statistic of 0.725. Higher risk categories were associated with lower early safety and higher 30-day and 1-year mortality. Conclusions: An anatomy-driven score derived from routine preprocedural imaging demonstrates graded discrimination of intraprocedural risk and may inform procedural planning in bicuspid transcatheter aortic valve implantation.

Background: Neighborhood-level social determinants of health influence cardiovascular outcomes; however, their association with post-discharge healthcare utilization in heart failure with preserved ejection fraction (HFpEF) remains incompletely defined. Methods: We conducted a retrospective cohort study of 6,702 adults hospitalized for HFpEF (2014 to 2022). Patients were assigned to one of four neighborhood environments (NEnv-1 to NEnv-4) using a validated clustering framework based on ZIP code-level socioeconomic variables. The primary outcome was time to first HF readmission, evaluated within prespecified post-discharge intervals (0-30 days, >30-90 days, and >90-365 days). Secondary outcomes included HF-related healthcare re-encounters and HF hospitalization burden (0, 1, or [&ge;]2 admissions). Cox proportional hazards and multinomial logistic regression models were used. Results: Neighborhood environment was independently associated with post-discharge outcomes with distinct temporal patterns. Early (0-30 days) HF readmission risk was higher in NEnv-3 (aHR, 1.63) and NEnv-4 (aHR, 1.76), with similar increases in HF-related re-encounters (aHR, 1.72 and 1.84) persisting through the >30-90-day interval. In contrast, NEnv-2 demonstrated a delayed-risk pattern, with the highest risk occurring in the >90-365-day interval (readmission aHR, 3.42; re-encounter aHR, 3.45). All non-reference environments were associated with a higher likelihood of at least one post-index HF admission (aOR range, 1.84-2.24). NEnv-4 uniquely demonstrated higher odds of recurrent hospitalization ([&ge;]2 vs. 1 admission; aOR, 1.64). Conclusions: Neighborhood environment is associated with distinct, time-dependent patterns of HF utilization in HFpEF, including early, delayed, and recurrent risks. Incorporating neighborhood context may help identify when patients with HFpEF are most vulnerable after discharge and guide the timing of post-discharge interventions.

Background: Apical sparing of left ventricular longitudinal strain (LS) is an echocardiographic clue to cardiac amyloidosis but may also occur in hypertensive heart disease (HHD). Objectives: To determine whether apical sparing in HHD is associated with regional left ventricular wall stress estimated according to Laplace's law. Methods: We retrospectively studied 1,559 patients with HHD, 47 with light-chain cardiac amyloidosis (ALCA), and 409 normotensive controls. Artificial intelligence-assisted echocardiography quantified segmental LS, wall thickness, and cavity radius at the basal, midventricular, and apical levels. Wall stress was estimated as mean blood pressure (MBP) x radius/(2 x wall thickness). Apical sparing was defined as a relative regional strain ratio (RRSR)[&ge;]1.0. Results: Apical sparing was present in 14 patients with HHD (0.9%), 13 with ALCA (27.7%), and no controls. Among HHD patients with apical sparing, RRSR decreased from 1.11{+/-}0.13 to 0.72{+/-}0.10 after antihypertensive treatment (P<0.001), accompanied by reduced wall stress and improved basal and midventricular LS, with resolution of apical sparing in all 14 patients. In the overall HHD cohort, changes in MBP and left ventricular mass index were independently associated with changes in RRSR. In an exploratory analysis of HHD patients with apical sparing, a reduction in basal wall stress was associated with a reduction in RRSR ({beta}=0.267 for {bigtriangleup}RRSRx100, 95% CI 0.023-0.511; P=0.036). In ALCA, favorable hematologic response was the only determinant of RRSR reduction. Conclusions: Apical sparing in HHD was uncommon but reversible and may represent a load-sensitive deformation pattern associated with regional wall stress, consistent with Laplace's law.

Background: The optimal timing of percutaneous coronary intervention (PCI) in patients undergoing transcatheter aortic valve replacement (TAVR) remains unclear, particularly regarding its impact on renal outcomes. Methods: We conducted systematic review and meta-analysis of studies comparing staged versus concomitant PCI in patients with aortic stenosis and coronary artery disease undergoing TAVR. We searched MEDLINE, Embase, and Cochrane databases comprehensively. Using a random-effects model, we calculated odds ratios (OR) with 95% confidence intervals (CI) to assess the incidence of contrast-induced acute coronary injury (CI-AKI) across different stages. Results: The analysis included 11 studies encompassing 7,119 patients. Overall, staged PCI did not significantly differ from concomitant PCI in reducing CI-AKI (OR 1.02; 95% CI 0.53 to 1.98; p = 0.959; Figure 2A). Subgroup analysis revealed no significant differences in stage 1 (OR 1.99; 95% CI 0.38 to 10.47; p = 0.417; Figure 2B) or stage 2 CI-AKI (OR 1.01; 95% CI 0.39 to 2.64; p = 0.978; Figure 2C). However, a statistically significant difference emerged for stage 3/4 CI-AKI, favoring the staged approach (OR 0.48; 95% CI 0.24 to 0.99; p = 0.046; Figure 2D). Conclusion: While staged PCI does not consistently reduce CI-AKI in patients undergoing TAVR, it may offer potential benefits for more severe kidney injury (stages 3/4). Given the observed heterogeneity, large-scale randomized controlled trials are essential to establish the relationship between procedural timing and renal outcomes.

Population-level data on preclinical heart failure (HF) remain limited because most epidemiological studies focus on symptomatic HF. We therefore developed an administrative-data algorithm to classify HF stages across the national population and describe temporal trends, stage transitions, and mortality across the HF continuum. Methods Using a claims-based staging framework adapted from the Universal Definition of HF, we classified HF stages from ICD-10 codes, prescription records, and medical procedures. We applied this algorithm to the Czech population, linking the National Registry of Reimbursed Health Services to National mortality records from 2015 to 2024. Results In 2024, 27.8% of the Czech population met criteria for Stage A HF and 8.2% for Stage B. Over 10 years, the prevalence of both preclinical stages increased beyond what could be explained by population aging alone, with age-standardized prevalence rising by 9.5% for Stage A and 19.2% for Stage B. Age-standardized 1-year mortality showed a steep stepwise gradient, from 0.69% in Stage A to 1.69% in Stage B, 3.06% in Stage C, and 7.27% in Stage D. Among 52,172 individuals with incident clinical HF in 2024, more than 95% had previously met administrative criteria for Stage A or Stage B. Conclusion Administrative surveillance of the HF continuum using routinely collected healthcare data provides a scalable administrative framework for population-level monitoring of HF burden. In Czechia, both preclinical and clinical HF burdens increased over time beyond population aging alone, underscoring the need for earlier preventive strategies targeting preclinical disease.

Importance: Heart failure readmissions remain common following hospitalization, but accurately identifying which patients will be readmitted after discharge remains challenging. Improved prediction could support targeted transitional care interventions and more efficient allocation of clinical resources. Objective: In this study we attempted to improve readmission prediction after heart failure hospitalization by using variables chosen through a modified Delphi process, and using inpatient Electronic Medical Record (EMR) data, focusing on clinical notes. Design: This prognostic study developed competing risk survival models to predict readmission after heart failure hospitalization. Variables were chosen using a modified Delphi process, and extracted from EMR notes using various natural language processing techniques or from other EMR elements where appropriate. Patients were admitted between 2011 through 2019, and at least one year of follow-up was available for all patients. Models were evaluated using C-statistics, as well as sensitivity, specificity, positive and negative predictive values. Setting: During the study period, all acute-care facilities in Calgary, Alberta used the same EMR system, from which patients were selected. Participants: Patients were 18 years or older, resided in Alberta, and were admitted to a Calgary hospital. All corresponding admissions with a most responsible diagnosis of heart failure were included (n=15,160). Main Outcomes and Measures: The main outcome of interest was readmission within 30 days, though 90- and 365-day time frames were also analyzed. Death was treated as a competing risk and analysed at those time frames as well.

Background: Prior analyses have demonstrated an inverse association between transcatheter aortic valve replacement (TAVR) procedural volume and short-term outcomes. However, less is known regarding the relationship between procedural volume and 1-year outcomes in the contemporary TAVR era. Objectives: To evaluate the association between annual hospital and operator TAVR procedural volumes and 1-year clinical outcomes in a contemporary national cohort. Methods: Clinical records from the Society of Thoracic Surgeons (STS)/American College of Cardiology (ACC) Transcatheter Valve Therapies (TVT) Registry for patients undergoing commercial TAVR between January 2020 and December 2022 were linked to Centers for Medicare & Medicaid Services administrative claims. Annualized hospital and operator TAVR volumes were modeled continuously and categorized into tertiles. Primary outcomes included 1-year all-cause mortality, stroke, the composite of mortality or stroke, and all-cause readmissions. Hierarchical risk-adjusted models accounting for patient clustering within sites were used to evaluate associations between procedural volume and outcomes. Results: Among 215,335 patients undergoing TAVR at 788 hospitals by 3,444 operators between 2020 and 2022, median annual hospital and operator volumes were 74 (IQR: 43-115) and 16 (IQR: 10-32), respectively. Volume was then categorized into tertiles (low, medium and high). Compared with high-volume hospitals ([&ge;]102/year), low-volume hospitals ([&le;]52/year) had higher adjusted rates of 1-year all-cause mortality (Odds Ratio (OR): 1.10 [95% CI: 1.05-1.16]), stroke (OR: 1.10 [95% CI: 1.01-1.19]), mortality or stroke (OR: 1.10 [95% CI: 1.05-1.15]), and all-cause readmissions (OR: 1.05 [95% CI: 1.00-1.09]). Compared with high-volume operators ([&ge;]25/year), low-volume operators ([&le;]11/year) had higher adjusted rates of stroke (OR: 1.16 [95% CI: 1.05-1.28]) and mortality or stroke (OR: 1.09 [95% CI: 1.03-1.15]) but not other endpoints. Conclusions: In a large, contemporary national TAVR registry, lower annual hospital ([&le;] 52/year) and operator ([&le;] 11/year) procedural volumes were independently associated with worse 1-year clinical outcomes. These findings suggest that procedural experience continues to influence outcomes despite maturation of contemporary TAVR practice.

Background: Increased public access to data from disparate sources provides opportunities to study and validate predictive and subphenotype models in heterogeneous disease conditions using aggregated individual patient data. Robust, explicit, and transparent harmonization of data elements is critical to ensure interpretability, reproducibility, and generalizability of secondary and retrospective analyses. Methods & Results: We designed and implemented ADAPT (Aggregating Data to Accelerate Personalized Therapy), a scalable framework using multiple software packages (R, SQL, BigQuery) that enables rapid, explicit harmonization of structured data elements from randomized trials and observational studies using a standard spreadsheet interface. User-specified criteria are applied to primary study data to produce harmonized longitudinal datasets comprised of demographics, medical history, quantitative observations, repeated measures, and clinical outcomes. We demonstrate this functionality using 26 clinical studies found in the National Heart, Lung, and Blood Institute BioLINCC resource. We illustrate the scalability of ADAPT to the order of billions of datapoints using administrative clinical data in a cloud-computing platform. We also present examples of collaborators using ADAPT for independent harmonization tasks for secondary analyses and democratization of publicly available data. Conclusion: ADAPT is a disease-agnostic, extensible, and scalable platform to support robust, transparent harmonization of structured research data using interfaces accessible to a variety of researchers regardless of programming ability. It extends FAIR principles beyond research data to also represent harmonization analyses by improving Findability of harmonization decisions, Accessibility of methods to other stakeholders, Interoperability with independent analyses and datasets, and Reusability through efficient implementation in a variety of analysis environments.

Background: The clinical benefit and safety of drug-coated devices in chronic limb-threatening ischemia remain debated, particularly after recent randomized evidence questioning paclitaxel-coated technologies. We evaluated wound healing, limb outcomes, and mortality after infrainguinal endovascular therapy with uncoated, paclitaxel-coated, and sirolimus-coated devices. Methods: Consecutive patients with chronic limb-threatening ischemia undergoing successful infrainguinal endovascular therapy in a prospective single-center service evaluation were analyzed. The primary exposure was use of any drug-coated device during the index procedure. Inverse probability of treatment weighting and multivariable Cox models were used to adjust for baseline differences. Exploratory analyses compared paclitaxel-coated, sirolimus-coated, and uncoated devices. Results: Among 341 patients, 244 (71.6%) received at least one drug-coated device. After weighting, drug-coated device use was associated with more frequent wound healing, whereas major amputation, clinically driven target lesion revascularization, major adverse limb events, and death did not differ significantly between groups. In weighted multivariable models, drug-coated device use remained associated with wound healing (HR, 1.86; 95% CI, 1.14?3.02), but not with mortality or major limb events. Exploratory drug-specific analyses suggested the highest wound-healing rates among patients treated with sirolimus-coated devices, while mortality was comparable between paclitaxel-coated and uncoated devices. Conclusion: In this real-world cohort of patients with chronic limb-threatening ischemia undergoing infrainguinal endovascular therapy, drug-coated device use was not associated with increased adjusted 1-year mortality and was associated with improved wound healing. Exploratory analyses suggested favourable wound-healing outcomes with sirolimus-coated balloons, with a lower observed mortality signal that warrants confirmation in larger comparative studies.

Background: Unplanned emergency readmissions remain common following hospitalisation for heart failure (HF). Residual congestion, atrial fibrillation, frailty, and other comorbidities contribute to adverse outcomes after discharge. Identifying patients at high risk of readmission or death may help target post-discharge management. Methods: We conducted a retrospective cohort study of patients hospitalised with HF in selected New South Wales hospitals who were discharged alive and not documented as receiving end-of-life care. Clinical, laboratory, medication, and text-derived variables extracted from electronic health records were used to develop predictive models and corresponding risk scores for emergency readmission and all-cause mortality within 180 days of discharge. Feature importance methods were used to identify key predictors and explain individual risk estimates. To illustrate model predictions while preserving patient privacy, we generated representative synthetic patient profiles by summarising the characteristics of groups of patients with similar predicted risk patterns and visualised the major contributors to their predicted risks using Shapley values. Results: The study included 5,202 hospitalisations among 3,933 patients. Within 180 days of discharge, 45.2% of patients experienced at least one emergency readmission and 12.4% died. The most common causes of emergency readmission were recurrent HF, followed by atrial fibrillation, chest pain, and pneumonia. Predictive performance was moderate for emergency readmission (AUC 0.70; calibration slope 1.30) and good for mortality (AUC 0.84; calibration slope 1.01). Emergency readmission risk was primarily associated with greater prior healthcare utilisation, a higher number of active medical problems, high risk of falls, older age, and impaired kidney function. Mortality risk was most strongly associated with abnormal red blood cell distribution width, elevated blood urea, older age, and lower systolic blood pressure. A lower number of discharge medications, particularly cardiovascular therapies, was associated with a higher risk of emergency readmission and a lower risk of mortality. Representative synthetic patient profiles demonstrated heterogeneity in the factors contributing to predicted risks, illustrating the value of patient-level risk visualisation. Conclusions: Predictive models identified clinically meaningful predictors of emergency readmission and mortality following HF hospitalisation. Patient-level visualisation of individual risk drivers may support more personalised post-discharge management.

Background Structural heart disease (SHD) drives heart failure and cardiovascular mortality but remains underdiagnosed, and echocardiography is limited as a population-level screening tool. Objectives We evaluated whether a composite artificial intelligence-enabled electrocardiogram (AI-ECG), combining independently developed models for left ventricular systolic (LVSD) and diastolic dysfunction (LVDD), identifies prevalent and predicts incident SHD across diverse populations. Methods In this multinational cohort study, detection was assessed cross-sectionally in a Korean clinical cohort (Incheon Sejong Hospital) and a US dataset (Columbia University Irving Medical Center), and incident risk was assessed in the Korean cohort and the UK Biobank among individuals without baseline SHD or heart failure. Adults with paired ECG and echocardiography were analyzed for detection, with the composite defined as positive on either model. SHD comprised reduced left ventricular ejection fraction, moderate or severe valvular disease, left ventricular hypertrophy, or pulmonary hypertension. Detection was assessed by sensitivity and specificity, and incident risk by Cox models and the C statistic. Results Among 46,082 and 36,286 participants in the two detection cohorts, the composite detected SHD with sensitivity of 71.8% and 76.1% and specificity of 88.3% and 70.1%, with positivity across all phenotypes. Among at-risk individuals, composite positivity was associated with incident SHD (hazard ratios, 3.75 and 2.75), with C statistics of 0.69 to 0.78. Conclusions A composite AI-ECG identified prevalent and predicted incident SHD across multinational cohorts, capturing signals beyond its training targets and supporting its potential as a scalable cardiovascular screening tool; whether ECG-based risk stratification improves outcomes requires prospective evaluation.

BACKGROUND: Chronic coronary syndromes (CCS) remain under-characterized in Latin America, where clinical profiles may differ from high-income countries. OBJECTIVE: We aim to characterize the clinical presentation, coronary anatomic profile, and pharmacologic treatment patterns of adults living with CCS using data from the Mexican Chronic Coronary Syndrome Registry (RESINCCRO). METHODS: RESINCCRO is an observational, multicenter, cross-sectional registry conducted across ~50 centers in five regions from Mexico. We included adults ([&ge;]18 years) enrolled between September 2024 and March 2025 who met 2019 ESC CCS criteria. Coronary imaging data was collected from medical records into a standardized electronic case report form. RESULTS: We enrolled 3,029 adults (men [72.5%]; mean age 67.2 {+/-} 10.7 years). Cardiometabolic comorbidities were frequent: overweight/obesity (76%), arterial hypertension (69.0%), type 2 diabetes (44.0%), and chronic kidney disease (24.2%). Persistent angina/equivalents occurred in (23.9%), of which most had Canadian Cardiovascular Society class I - II (91.2%). The mean LVEF was of 53.7 {+/-} 12.0. Cardiac rehabilitation participation was (6.2%). Median LDL-C was 70 mg/dL (IQR 51 - 95) and LDL <55 mg/dL was only 26.1%, despite high prescription of lipid-lowering therapies, including statins (93.2%), ezetimibe (24.6%), and PCSK9 inhibitors (2.4%). 60.3% had obstructive epicardial disease. CONCLUSIONS: Mexican adults with CCS exhibit high cardiometabolic burden, frequent symptoms, suboptimal LDL-C goal attainment, low rehabilitation uptake, and a substantial obstructive phenotype. These findings highlight opportunities to intensify secondary prevention, adopt mechanism-directed evaluation and therapy, and expand cardiac rehabilitation to improve CCS care in Mexico.

Minimally invasive endovascular procedures offer reduced surgical trauma, shorter recovery times, and improved outcomes, but rely on 2D fluoroscopic X-ray imaging, which provides limited depth perception and exposes patients and clinicians to ionizing radiation. Here we present an augmented reality (AR) system that fuses intravascular ultrasound (IVUS) and electromagnetic (EM) position tracking with preoperative computed tomography (CT) to produce an anatomically accurate, deformation-corrected navigational reference. A robotic device performs ECG-gated pullback of the IVUS probe, capturing 4D aortic motion across the cardiac cycle. We introduce a deep learning architecture for extracting vascular lumen boundaries and side-branch orifices from artifact-prone IVUS streams, and a semantically driven non-rigid CT-IVUS fusion pipeline robust to false positive landmarks. We evaluate the platform with trained surgeons in benchtop phantom studies and in-vivo ovine models, and demonstrate its application to fenestrated endovascular aneurysm repair (FEVAR). Compared to fluoroscopy alone, AR guidance significantly reduces cannulation time, radiation exposure, and cognitive workload, while improving procedural efficiency and safety. Our IVUS-EM and CT aortic datasets are released open source.

Aims Polymer-free drug-eluting stents were developed to enhance vascular biocompatibility and safety while maintaining antirestenotic efficacy. The TRANSEVER registry evaluated 12-month clinical outcomes of the polymer-free everolimus-eluting ISAR SUMMIT stent in a large, real-world population undergoing percutaneous coronary intervention. Methods This prospective, multicentre study enrolled patients with coronary artery disease undergoing PCI with the ISAR SUMMIT stent across 33 centres in India. The primary endpoint was target-lesion failure (TLF) at 12 months, a composite of cardiac death, target vessel myocardial infarction, or clinically driven target lesion revascularisation. Secondary endpoints included the patient-oriented composite endpoint (POCE) of all-cause death, any myocardial infarction, stroke, revascularization, and definite/probable stent thrombosis. Results A total of 1,000 patients were enrolled, of whom 996 completed 12-month follow-up. The cohort presented with a high-risk profile, including an acute coronary syndrome (ACS) in 89.8% of the cases and diabetes mellitus in 44.4% of them. Procedural outcomes were excellent in terms of device success and final TIMI 3 flow (achieved in all treated lesions). At 12 months, TLF occurred in 15 patients (1.5%). Definite or probable stent thrombosis was observed in 8 patients (0.8%). POCE was observed in only 21 patients (2.1%). Conclusions In this large, contemporary real-world population with a very high proportion of patients presenting with ACS, the polymer-free everolimus-eluting ISAR SUMMIT stent demonstrated favourable 12-month clinical outcomes, with low rates of target lesion failure and stent thrombosis. These results suggest that this novel device is both safe and effective for routine clinical use.

Background: Cardiovascular disease remains the leading cause of death in the United States, and marked geographic disparities in cardiovascular mortality persist. However, the community-level socioeconomic indicators most strongly associated with these disparities remain unclear. Community-level measures capture the social and economic conditions that influence cardiovascular health across populations and may help identify communities at greatest risk. We used the Area Health Resources File (AHRF) to identify socioeconomic measures most strongly associated with county-level cardiovascular mortality. Methods: We performed a national cross-sectional ecological analysis using the 2024-2025 Area Health Resources File (AHRF), including counties in the 50 U.S. states and the District of Columbia. The primary outcome was an AHRF-defined cardiovascular mortality composite derived from 2021-2023 National Center for Health Statistics (NCHS) mortality data. Community-level socioeconomic measures included 2023 overall, pediatric, and family childhood poverty and 2019-2023 overall, female, and White unemployment. County-level associations were evaluated using Spearman rank correlation and regional differences using the Kruskal-Wallis test. Sensitivity analyses used a partial mortality composite and Kendall {tau} correlation. Results: Among 1,982 counties, cardiovascular mortality varied significantly across U.S. Census divisions (P<0.001), with the highest population-weighted rate in the East South Central division (348.5 deaths/100,000) and the lowest in the Mountain division (233.9 deaths/100,000). Pediatric poverty demonstrated the strongest association with cardiovascular mortality ({rho}=0.612), followed by family childhood poverty ({rho}=0.603) and overall poverty ({rho}=0.524, all P<0.001). In contrast, unemployment measures were more weakly associated (overall {rho}=0.209, White {rho}=0.176, female {rho}=0.141, all P<0.001). Results were consistent in sensitivity analyses. Conclusions: County-level poverty, particularly pediatric poverty, was more strongly associated with cardiovascular mortality than unemployment across U.S. counties. These findings suggest pediatric poverty may serve as a useful community-level indicator for identifying populations at increased cardiovascular risk and prioritizing future public health interventions.

We conducted a scaling evaluation of unlabeled pretraining for electrocardiogram foundation model performance. One-dimensional vision transformer masked autoencoders were pretrained across increasing ECG volumes and fine-tuned for rhythm, morphology, diagnostic, and structural heart disease tasks. Models pretrained below 400,000 ECGs failed to consistently exceed controls without self-supervised pre-training, whereas 600,000 to 800,000 ECGs improved AUROC across tasks, suggesting a minimum threshold for effective ECG representation learning.

Background: Rheumatic heart disease (RHD) remains a major cause of premature death in low- and middle-income countries and First Nations communities. Early detection and management can prevent progression, but requires echocardiography, which is limited in high-burden settings. Task-sharing echocardiographic screening is an accessible, evidence-based approach but implementation remains unclear. Methods: We conducted a prospective implementation evaluation of a co-designed task-sharing screening programme across five remote First Nations Australian communities between May 2023 and November 2025. Predominantly community health workers (CHWs), alongside nurses and doctors, were trained to scan using handheld devices with off-site cardiologist interpretation. We assessed implementation outcomes and used a realist evaluation to explore how context shaped CHWs ability to complete training and embed screening into routine work. Data included scanning activity, surveys, costing, interviews, focus groups, and field notes. Findings: We trained 32 staff (21 CHWs, 8 nurses, 3 doctors) to scan across five sites. Scanning frequency was lower and more variable than anticipated: 360 scans (including training and post-certification) of 5 - 20 year olds over 14 months, with site-level coverage of 3 - 85%. Fidelity was limited by device unavailability, charging problems, and delays in uploads and reviews. Set-up and training cost A$51,903 per site, plus A$9,858/year in implementation support. Screening was easier for CHWs to embed when the legitimacy of their role as a scanner was communicated, but harder when invisible work outweighed opportunities to scan. Interpretation: Future implementation will require efforts to legitimise CHWs scanning and support invisible work. Event-based screening offers a promising complementary strategy. Scale-up requires policy support. Funding: This research was funded by the Australian Medical Research Futures Fund Cardiovascular Health Mission (GNT2015869), in addition to philanthropic donations from Medtronic Australasia, Edwards Life Sciences and the Rotary Club of Kiama. Hand-held devices (Philips Lumify, USA) were donated by Humpty Dumpty Foundation and East Timor Hearts Fund.

We present FootNet, a 453-image multi-view smartphone foot dataset for binary foot segmentation, with expertannotated masks across six anatomical views (dorsal, medial, and plantar, both left and right). We benchmark four segmentation models under a controlled protocol: U-Net with a MobileNetV2 encoder achieves the best performance (IoU 0.9268, Dice 0.9608, 95 % CI [0.9209, 0.9320]); DeepLabV3 with MobileNetV3-Large scores IoU 0.8984 (Dice 0.9449); UNet++ with MobileNetV2 scores IoU 0.8913 (Dice 0.9391); and SAM ViT-B with oracle boundingbox prompt scores IoU 0.9219 on the matched 191-image subset. Bonferroni-corrected Wilcoxon signed-rank tests (k = 6 comparisons) show U-Net significantly outperforms DeepLab (p < 0.001, r = 0.638) and SAM ViT-B with oracle boundingbox (p = 0.005, r = 0.202); UNet++ does not significantly differ from DeepLab (p = 0.062). Connected-component postprocessing yields negligible benefit (mean {triangleup}IoU = +0.0003, 12 of 453 images improved). The extended dataset is available upon request

Background The 2022-2023 global mpox outbreak highlighted the critical need for robust genomic surveillance capabilities to track mpox virus (MPXV) evolution and transmission dynamics. Methods Building upon our established SARS-CoV-2 sequencing infrastructure, we implemented a Molecular Loop probe-based long-read sequencing approach using Pacific Biosciences Sequel II technology for comprehensive MPXV genomic surveillance across the United States (US). From August 2024 to June 2025, we generated 326 high-quality whole genome sequences from residual mpox-positive clinical specimens collected by Labcorp across all 10 US Department of Health and Human Services regions. Results Our analysis identified two samples containing clade Ib MPXV in January and June 2025 and captured shifting trends in clade IIb diversity, with 13 distinct lineages observed. We also identified multiple instances of large (~1.6-17.6kb) deletions proximal to the inverted terminal repeats in clade IIb genomes. APOBEC3 mutation analysis indicated substantial evidence of human-to-human transmission among both clades. Further, we observed significantly higher APOBEC3-associated SNPs per kilobase (P<0.001) in clade IIb genomic variable regions relative to their central conserved region. Our assay exhibited strong reproducibility across biological replicates from individual patients and accuracy was confirmed via parallel sequencing of select specimens by US Centers for Disease Control and Prevention (CDC) using metagenomic sequencing. We also demonstrated via custom simulation that our assay discriminates all known MPXV clades and lineages, including those we have not observed in the US. Conclusions Our integrated nationwide surveillance system facilitates real-time genomic tracking of outbreak evolution, with demonstrated capacity across SARS-CoV-2 and MPXV, positioning this platform for rapid deployment during future pathogen emergence.

Background: Monoclonal antibodies have emerged as a prophylactic strategy to prevent symptomatic SARS-CoV-2 infection in immunocompromised individuals. However, the evolutionary and clinical implications of breakthrough infections under this regime remain unclear. Methods: A male in their 80s with a haematological/oncological diagnosis received a 2000 mg intravenous infusion of sotrovimab in March 2023 and was diagnosed with COVID-19 by RT-qPCR from a nasopharyngeal swab in August 2023. Weekly samples (n=24) were collected through February 2024 (171 days). All samples underwent whole-genome sequencing, with select mutations subjected to functional assessment. Findings: Sequencing identified the GE.1 lineage at all timepoints. An intra-host recombination event in ORF1ab (positions 8942-12458) was detected prior to 23 weeks post-detection, followed by a 14-fold increase in viral load (7.42e+06 to 1.00e+08 RNA copies/mL) and a marked shift in the viral population. E340D, a sotrovimab resistance mutation, was detected at low abundance (46%) within the first week post-infection, fluctuated over time, and was nearly fixed by week 15 (107 days) post-detection. We assessed five spike mutations - V36M, S98F, and V213G in the N-terminal domain, Y505P in the receptor-binding domain, and P681Q near the S1/S2 cleavage site - and additionally evaluated the impact of E340D. V36M conferred the highest infectivity across all cell lines, with the most significant effect in low-TMPRSS2 cells. While all mutations showed enhanced infectivity with the addition of E340D, the effect was most pronounced in mutations with lower baseline infectivity. The addition of E340D significantly decreased relative neutralizing titres for V36M, S98F, and V213G, enabling escape from neutralizing antibodies in XBB-responsive individuals, illustrating an enhanced phenotypic advantage. Patient neutralizing activity was absent pre-sotrovimab, and sotrovimab-induced neutralization was further compromised by selection of E340D. Interpretation: Sotrovimab pre-exposure prophylaxis in an immunocompromised patient did not prevent SARS-CoV-2 infection, and selected for resistant mutation E340D, with unexpected fitness consequences across non-receptor binding domain spike regions.