Citations

Abstract Background and Aims Patients with catecholaminergic polymorphic ventricular tachycardia (CPVT) are at risk for potentially life-threatening arrhythmic events (AEs) even while treated with β-blockers. The aim was to develop a model for individualized prediction of AEs in patients with RYR2-mediated CPVT on β-blocker monotherapy. Methods The derivation and independent validation cohorts included 743 and 129 patients, respectively. AEs were defined as arrhythmic syncope, appropriate implantable cardioverter–defibrillator shock, sudden cardiac arrest (SCA), and sudden cardiac death. Near-fatal or fatal AEs (nf/fAEs) included all AEs except for arrhythmic syncope. Prediction models using Cox regression were developed and internally and externally validated. Results A total of 102 (13.7%) patients in the derivation cohort and 24 (18.6%) patients in the validation cohort experienced ≥1 AE over a median follow-up of 5.1 [interquartile range (IQR), 7.7] and 2.4 (IQR, 4.4) years, respectively. Predictors of AE were arrhythmic syncope or SCA prior to diagnosis and age at β-blocker initiation. In the derivation and validation cohorts, the optimism-corrected C-indices of the models for AE were 0.67 [95% confidence interval (CI) 0.62–0.72] and 0.59 (95% CI 0.48–0.71), respectively. For nf/fAEs, ventricular arrhythmia severity before β-blocker initiation was a fourth independent predictor, and C-indices of the models in the derivation and validation cohorts were 0.74 (95% CI 0.68–0.80) and 0.60 (95% CI 0.47–0.72), respectively. In the derivation cohort, calibration slopes were 1.00 (95% CI 0.59–1.41) for AE and 1.00 (95% CI 0.69–1.32) for nf/fAE. Conclusions These externally validated risk prediction models using clinical parameters accurately distinguished CPVT patients on β-blocker monotherapy at low and high risk for future AEs while treated with β-blockers. These models provide guidance for implementation of clinical management therapies to prevent AEs in patients with CPVT.

Abstract Advocacy has long been at the core of the infectious diseases (ID) field, with clinicians and researchers advocating to ensure patients can access the care they need on an individual and global scale. The Infectious Diseases Society of America Training Program Directors’ (PD) Committee met in 2024 and discussed ways that advocacy is and should be incorporated into fellowship training, as well as highlighted the role PDs play in advocating for their trainees. Policies with a negative impact on ID clinical care, public health, and research underscore the importance of mobilizing the field of ID to advocate for the patients and communities we serve, as well as for ourselves. This paper presents ideas generated at this meeting and is meant to serve as a reference for ID PDs, as well as the wider ID community, as a call to action for teaching and participating in advocacy work.

Abstract Background The associations between different types of diabetes, characterized by distinct pathophysiology and genetic architecture, and pancreatic ductal adenocarcinoma (PDAC) risk are not understood. Methods We investigated associations of genetic susceptibility to type 2 diabetes (T2D), 8 T2D mechanistic clusters, type 1 diabetes (T1D), and maturity-onset diabetes of the young (MODY) with PDAC risk. We used genome-wide association study (GWAS) summary-level statistics for T2D (242 283 cases, 1 569 734 controls), T1D (18 942 cases, 501 638 controls), and PDAC (10 244 cases and 360 535 controls) in individuals of European ancestry. Results Two-sample Mendelian randomization (MR) using the Robust Adjusted Profile Score (MR-RAPS) method indicated that genetically predicted T2D was associated with PDAC risk (OR = 1.10; 95% CI = 1.05 to 1.15), particularly the T2D obesity (OR = 1.28; 95% CI = 1.15 to 1.42) and lipodystrophy (OR = 1.25; 95% CI = 1.03 to 1.51) clusters. No association was observed for T1D with PDAC risk (OR = 1.01; 95% CI = 0.99 to 1.02). Pathway/gene-set analysis using the summary-based Adaptive Rank Truncated Product (sARTP) method revealed a significant association between the MODY gene-sets and PDAC risk (P = 1.5 × 10−8), which remained after excluding 20 known PDAC GWAS loci (P = 7.6 × 10−4). HNF1A, FOXA3, and HNF4A were the top contributing genes after excluding the previously identified GWAS loci regions. Conclusions Our results from this genetic association study support that T2D, particularly the obesity and lipodystrophy mechanistic clusters, and MODY genomic susceptibility regions play a role in the etiology of PDAC.

Objective: An endoscopically placed duodenal-jejunal bypass liner (DJBL) may provide a safe adjunctive therapy for those with poorly controlled type 2 diabetes mellitus (T2DM) and obesity. Background: Although some endoscopic therapies have been shown to improve glycemic indices secondary to weight loss, small bowel interventions may have direct metabolic effects. A meta-analysis of observational studies demonstrated reduction in HbA1c by 1.3% at 1 year after DJBL in patients with T2DM and obesity. Methods: This was a multicenter, double-blind, randomized, sham-controlled trial comparing DJBL to sham procedure with medical management and lifestyle modification. Primary endpoints included mean difference in changes in HbA1c at 12 months between arms, and device-related serious adverse events (SAEs). Secondary endpoints included percent total weight loss (%TWL) and subjects achieving HbA1c≤7% and TWL≥5% at 12 months. Results: Three hundred twenty subjects were randomized to DJBL (n=212) and sham (n=108). Baseline HbA1c and BMI were 8.79±0.92% and 38.45±5.75 kg/m 2 . On modified intent-to-treat analysis, change in HbA1c at 12 months was −1.10±1.45% and −0.28±1.54% for DJBL and sham groups, respectively ( P =0.0004). Rate of device-related SAEs was 9.4% including intolerance (3.7%), hemorrhage (2.8%), and hepatic abscess (2.3% stopping study early). At 12 months, DJBL group experienced greater weight loss compared with sham (7.7±9.6% TWL and 2.1±5.4% TWL, respectively; P <0.0001), with significantly more patients achieving HbA1c ≤ 7% (28.3% vs. 9.4%; P <0.0003) and TWL ≥ 5% (60.4% vs. 21.3%; P <0.0001). Conclusions: DJBL met primary glycemic control efficacy and primary safety endpoints, while providing clinically significant weight loss, and comorbidity improvement.

Abstract Background Clinical nutrition (CN) is becoming increasingly complex because of the rising prevalence of chronic illness, cancer, and malnutrition‐related conditions such as short bowel syndrome and refeeding syndrome. Despite its clinical significance, nutrition education among US physicians remains limited. Simultaneously, large language model (LLM)–based artificial intelligence assistants (AIAs) have emerged as tools to support complex clinical decision‐making but remain largely untested in CN. Methods This retrospective study evaluated four LLM‐based AIAs—ChatGPT (OpenAI), OpenEvidence (OpenEvidence Inc), Gemini (Google, Google DeepMind), and Copilot (Microsoft Corporation)—using five complex CN cases from our nutrition support service. Each AIA was queried with patient‐specific CN questions. Responses were blinded and reviewed by five physician CN experts using an eight‐item assessment tool evaluating clarity, relevance, evidence, and clinical utility. Results All AIAs produced clinically appropriate responses, with Gemini scoring highest in relevance (4.04) and clarity (4.16). Overall satisfaction scores ranged from 3.08 (Copilot) to 3.84 (Gemini). Citation quality and originality of insights varied and were generally limited, and no consistent differences in performance were observed across the five cases among the four AIAs. Conclusion LLM‐based AIAs can reliably replicate expert reasoning in CN. Although not yet a source of novel clinical insights, the true potential of this approach may lie in its application among physicians without specialized expertise in CN, helping to bridge existing knowledge gaps in nutrition care. Presenting full clinical cases, as shown in this study, could support AIA‐enabled e‐consultation in the future, thereby addressing gaps in CN education.

BACKGROUND: Although chronic obstructive pulmonary disease (COPD) and heart failure with preserved ejection fraction often coexist with overlapping clinical features, they are usually studied separately. The SPIROMICS HF (Subpopulations and Intermediate Outcome Measures in COPD and Heart Failure Study) is testing hypotheses that new computed tomography emphysema subtypes are associated with specific cardiovascular phenotypes (eg, cor pulmonale , cor pulmonale parvus ), common airway branch variants are associated with right heart dysfunction, and symptomatic tobacco-exposed persons with preserved spirometry have signs of increased left ventricular afterload. METHODS: SPIROMICS is a multicenter observational study of COPD with extensive pulmonary phenotyping of participants with ≥20 pack-years smoking and nonsmoking controls. COPD and COPD severity were defined by standard spirometric criteria and symptomatic tobacco-exposed persons with preserved spirometry by ≥20 pack-years, normal spirometry, and COPD Assessment Test score >10. SPIROMICS HF selected all participants in SPIROMICS visit 5 at major sites. Its comprehensive speckle-tracking echocardiography, which included physiological perturbations of leg raise and low-intensity exercise, was harmonized prospectively with the Multi-Ethnic Study of Atherosclerosis Early Heart Failure and HeartSHARE (Combining Omics, Deep Phenotyping, and Electronic Health Records for Heart Failure Subtypes and Treatment Targets) studies. The cardiopulmonary magnetic resonance imaging protocol with gadolinium administration included myocardial fibrosis sequences, pulmonary angiography, time-resolved 3-dimensional cine magnetic resonance imaging (4-dimensional flow) of venous return, and metronome-paced tachypnea to induce dynamic hyperinflation. Coronary artery calcium was assessed on computed tomography scans. The Kansas City Cardiomyopathy Questionnaire was administered. RESULTS: Of the final sample of 753 participants, 57% had COPD (15% mild, 27% moderate, and 15% severe), 18% had symptomatic tobacco-exposed persons with preserved spirometry, 16% were smoking controls, and 8% were nonsmoking controls. Reproducibility of the main measures from speckle-tracking echocardiography (intraclass correlation coefficient, 0.83–0.99), exercise echocardiography (intraclass correlation coefficient, 0.71–0.99) and magnetic resonance imaging (intraclass correlation coefficient, 0.57–0.99) were good-to-excellent, including in severe COPD. CONCLUSIONS: SPIROMICS HF aims to characterize and understand cardiopulmonary interactions in COPD and COPD-related phenotypes to inform targeted treatments for combined cardiopulmonary failure.

ABSTRACT Background Early catheter ablation for atrial fibrillation (AF) improves outcomes, but the optimal timing, especially in heart failure (HF) subtypes, remains unclear. Objective To evaluate the impact of ablation timing on outcomes in patients with HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF). Methods We used the TriNetX database (2010–2024) to identify HF patients with AF who underwent ablation. Patients were classified as early ablation (≤ 1 year of first AF diagnosis) or delayed ablation (1–3 years), with propensity score matching (PSM) applied to balance the baseline characteristics. The primary outcome was AF recurrence, defined by repeat ablation, direct current cardioversion (DCCV), or antiarrhythmic drug (AAD) use after a 3‐month blanking period. Secondary outcomes included stroke, hospitalization, and mortality over 5 years. Results After PSM, delayed ablation was associated with higher AF recurrence in both HFrEF (HR = 1.28, p < 0.001) and HFpEF (HR = 1.21, p = 0.02), as seen in multivariate analysis. In HFrEF, delayed ablation was associated with higher incidence of re‐do ablation, AAD use, and DCCV, while in HFpEF, higher recurrence with delayed ablation was associated with increased AAD use. Both cohorts had similar stroke and mortality rates between early and delayed ablation. Conclusions Delayed ablation in HFrEF and HFpEF was linked to higher AF recurrence, driven by increased redo ablations, DCCV, AAD use in HFrEF, and higher AAD use in HFpEF. Stroke, HF hospitalization and mortality rates were similar, suggesting earlier ablation may enhance rhythm control over other outcomes.

Background The Woven EndoBridge (WEB) device represents an innovative solution for cerebral aneurysm occlusion, particularly for challenging wide-neck bifurcation aneurysms. However, factors affecting sustained occlusion remain poorly understood. We utilized machine learning to attempt to identify predictors of favorable long-term outcomes following WEB treatment. Methods In this multicenter retrospective study, we collected patient demographics, aneurysm characteristics, procedural details, and clinical outcomes. The primary endpoint was improvement in occlusion status, defined as maintained Raymond-Roy Occlusion Classification (RROC) grade 1, or improvement from grade 2 to 1, or from grade 3 to either 2 or 1 on final angiographic follow up. The dataset was split into training (75%) and validation (25%) sets. The CatBoost algorithm was selected based on performance metrics, with Shapley Additive exPlanations (SHAP) values calculated to determine feature importance. Furthermore, a multivariable binomial logistic regression model was performed to validate machine learning findings. Results Among 720 aneurysms from 36 hospitals, 84% showed improvement in occlusion at follow up. Both machine learning and multivariable logistic regression identified aneurysm height as the most consistent correlate of nonimprovement (odds ratio (OR) 0.90 per mm, p = 0.022). In the CatBoost model, the highest-ranking features by SHAP included aneurysm height, patient age, treatment acuity, ACom location, WEB-SLS device, bifurcation anatomy, aneurysm multiplicity, baseline modified Rankin Scale, access route, and partial thrombosis. Conclusions Machine-learning and regression analyses identified consistent predictors of occlusion improvement after WEB treatment, with aneurysm height most strongly linked to nonimprovement. These insights may guide patient selection and follow up. Findings require cautious interpretation and external validation in larger cohorts.