Citations

Objective To compare the diagnostic accuracy of four available automated electronic medical record (EMR) retrieval methods, including a large language model (LLM)-assisted workflow, against manual chart adjudication for identifying cardiovascular events. Design Retrospective diagnostic accuracy study. Setting Three sites within a single US tertiary health system. Participants Two adult cohorts with previously adjudicated cardiovascular outcomes were included. Cohort 1 included 2258 patients treated with immune checkpoint inhibitors, and Cohort 2 included 1426 patients who underwent transcatheter aortic valve replacement. Primary and secondary outcome measures The reference standard was clinician manual chart adjudication. Outcomes included ischaemic stroke or transient ischaemic attack, myocardial infarction (MI), heart failure (HF) exacerbation or hospitalisation and a composite major adverse cardiovascular events (MACE) outcome. Automated retrieval methods included International Classification of Diseases (ICD) codes, primary diagnosis, problem list and a zero-shot LLM workflow. Area under the (receiver operating characteristic) curve (AUC), sensitivity, specificity and net reclassification improvement were assessed. Results In Cohort 1, the LLM achieved the highest AUC for stroke (0.920; 95% CI 0.881 to 0.958), MI (0.938; 95% CI 0.905 to 0.971) and composite MACE (0.880; 95% CI 0.854 to 0.907), whereas ICD-based retrieval had a higher AUC for HF (0.882; 95% CI 0.845 to 0.918 vs 0.873; 95% CI 0.831 to 0.914). In Cohort 2, the LLM achieved the highest AUC for all evaluated outcomes: stroke (0.915; 95% CI 0.862 to 0.968), MI (0.928; 95% CI 0.839 to 1.000), HF (0.844; 95% CI 0.803 to 0.884) and composite MACE (0.862; 95% CI 0.829 to 0.895). In Cohort 1, differences in AUC between the LLM and ICD methods were not statistically significant across outcomes, whereas in Cohort 2 the LLM showed significantly higher AUC for stroke and composite MACE. Conclusion In this multisite retrospective validation study, the LLM-assisted workflow showed strong but context-dependent performance for identifying cardiovascular events from the EMR. Performance varied by outcome and cohort, and ICD-based retrieval remained competitive for some use cases. These findings support a complementary role for LLM-assisted extraction in retrospective cardiovascular outcomes research.

Background: Corticosteroids are widely used in pericarditis despite guideline recommendations reserving them for select indications. Observational studies have reported inconsistent associations between corticosteroid use and pericarditis recurrence, and optimal dosing and tapering strategies remain unclear. We conducted a systematic review of oral corticosteroids for acute or recurrent pericarditis to characterize patterns of treatment and evaluate the association between corticosteroids and pericarditis recurrence across different disease contexts. Methods: MEDLINE, EMBASE, CENTRAL, and Scopus were searched from inception to November 26, 2025. Studies enrolling adults with acute or recurrent pericarditis treated with oral corticosteroids were included. Randomized trials, cohort studies, and case–control studies reporting clinical outcomes were eligible. Risk of bias was assessed using the Newcastle–Ottawa Scale (NOS). Data were synthesized descriptively due to anticipated clinical and methodological heterogeneity. Results: Ten studies (2 prospective, 8 retrospective) including 2632 patients (800 corticosteroid-treated) met inclusion criteria. Prednisone was most frequently studied, with heterogeneous dosing (0.25–1.0 mg/kg/day) and non-standardized tapering strategies. Follow-up ranged from 1 to 6.7 years, and overall risk of bias was moderate with limited adjustment for confounding. Findings on recurrence were inconsistent in acute idiopathic and post-procedure pericarditis, while most studies in recurrent pericarditis reported higher recurrence with corticosteroid exposure. Conclusions: Evidence evaluating oral corticosteroids in pericarditis is limited by heterogeneity, confounding, and inconsistent reporting of treatment strategies. Observational data show variable associations with recurrence across clinical contexts. High-quality randomized trials stratified by pericarditis etiology and acuity are needed to define the optimal use of corticosteroids in pericarditis.

Background:The development of symptoms or left ventricular dysfunction in severe aortic stenosis (AS) is associated with high morbidity and mortality. While elective transcatheter aortic valve replacement (TAVR) is supported by robust randomized evidence, data on TAVR performed in non-elective settings (urgent, emergent, or salvage) remain limited and heterogeneous. In these settings, outcomes may be influenced more by baseline clinical severity than by procedural factors. This study aimed to systematically evaluate the safety and effectiveness of non-elective TAVR and to compare the associated outcomes with those of elective TAVR.Methods:This systematic review and meta-analysis were conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and registered with PROSPERO. The PubMed, Embase, and Scopus databases were searched for studies published after 2002 evaluating urgent, emergent, or salvage TAVR in adult patients with severe AS. Eligible studies were required to include elective TAVR as a comparator. Outcomes included mortality and major procedural complications. Prespecified era-based analyses and sensitivity analyses excluding studies at critical risk of bias were performed. Risk of bias was assessed using the ROBINS-I tool.Results:A total of 17 observational studies published between 2015 and 2025 were included, comprising 215,141 patients. Compared with elective patients, those undergoing non-elective TAVR had more advanced heart failure, higher NYHA class, greater comorbidity burden, and higher surgical risk scores, whereas baseline echocardiographic severity of AS was similar. Pooled outcomes for non-elective TAVR showed in-hospital, 30-day, and 1-year mortality rates of 5.1%, 12.4%, and 26.7%, respectively. Non-elective TAVR was associated with higher mortality at all time points compared with elective procedures; meanwhile, rates of stroke, vascular complications, and permanent pacemaker implantation were similar, while major bleeding and acute kidney injury were more frequent. Era-based analyses showed a stable relative mortality risk over time.Conclusions:Although non-elective TAVR is associated with worse outcomes than elective procedures, these differences appear to be largely driven by baseline clinical severity rather than by the transcatheter intervention. In unstable patients with severe AS, non-elective TAVR remains the most effective definitive treatment option compared with balloon aortic valvuloplasty or conservative management.The PROSPERO Registration:CRD420251239620, https://www.crd.york.ac.uk/PROSPERO/view/CRD420251239620.

Coronary artery disease (CAD) remains a leading cause of global morbidity and mortality. Accurate diagnosis of ischemia-causing coronary stenoses is essential for guiding revascularization and improving outcomes. Although invasive fractional flow reserve (FFR) remains the gold standard for functional lesion assessment, its use is limited by procedural invasiveness, cost, and complexity. CT-derived FFR (FFRct), based on computational fluid dynamics (CFD), was the first major advance in noninvasive physiological assessment, but its adoption has been hindered by intensive off-site computation and dependence on high-quality imaging. This review summarizes the evolution from invasive FFR to AI-driven functional assessment of coronary lesions. We examine the principles and validation of CFD-based FFRct and then focus on the shift toward artificial intelligence, including both machine learning (ML) and deep learning (DL) approaches. These methods range from models using engineered geometric and plaque features trained on large synthetic datasets to end-to-end systems that learn directly from imaging data. We discuss key validation studies evaluating diagnostic accuracy, prognostic value, and clinical utility, with attention to performance in challenging settings such as intermediate stenoses, heavy calcification, and patients with comorbidities. We also highlight major barriers to widespread adoption, including dependence on input data quality, limited explainability, regulatory hurdles, and integration into clinical workflows. Finally, we outline future directions, including AI-enabled virtual PCI planning, multimodal risk stratification, and broader access to functional cardiac assessment. AI has the potential to transform noninvasive coronary imaging by enabling a single CCTA scan to provide rapid, integrated evaluation of anatomy, plaque characteristics, and physiological significance, supporting more personalized care and better clinical outcomes.

Aim Incorporating patient-reported outcomes (PROs) into clinical practice and real-world research is essential to enable a more holistic assessment of treatment effectiveness, beyond migraine frequency alone. Given the number of calcitonin gene-related peptide (CGRP)-targeted treatments available, switching between CGRP-targeted preventive therapies is a common practice. Real-world evidence on switching to intravenous eptinezumab in adults with migraine for whom prior subcutaneous or oral CGRP-targeted preventive therapies failed is limited. The ongoing INFUSE study was designed to evaluate the real-world effectiveness of switching to eptinezumab in US clinical practice among adults with migraine for whom ≥1 prior CGRP-targeted preventive therapy had failed. Methods INFUSE, a real-world, non-interventional study evaluating the effectiveness of eptinezumab in US clinical practice, included adults with migraine for whom ≥1 prior CGRP-targeted preventive therapy had failed and who were newly initiating eptinezumab treatment. PROs were collected electronically. To provide an overall assessment of the change in migraine disease, Patient Global Impression of Change (PGIC) was utilized. Other outcomes allowed for the evaluation of novel end points, such as brain fog and participant-defined good days. Results The baseline population included 190 participants (female, 88.9%; 35–54 years of age, 53.7%). At month 6, 44.1% (95% confidence interval (CI): 35.3–53.4%) of participants reported “much/very much improved” on PGIC, and 75.7% (95% CI: 66.9–82.7%) reported any improvement. Mean good days increased by 6.3 per month at month 6 ( P < 0.001). Among participants reporting brain fog at baseline (93.7%), 55.8% (95% CI: 46.2–64.9%) reported improvement at month 6. Conclusion This research provides insights into capturing the broader migraine burden and the holistic impact of preventive treatment and highlights the potential for achieving ambitious goals. In this population for whom ≥1 prior CGRP-targeted preventive therapy had failed, switching to eptinezumab was associated with participant-reported, clinically meaningful improvements in PROs, including frequency, disability, disease status, and brain fog.

Coronary microvascular dysfunction (CMD) has emerged as a crucial contributor to cardiovascular morbidity and mortality, particularly in patients with ischemia and non-obstructive coronary arteries (INOCA). The condition arises from a complex interplay of structural and functional abnormalities within the small coronary vessels, driven by underlying molecular mechanisms including endothelial nitric oxide synthase (eNOS) uncoupling, oxidative stress, and chronic inflammation. Lipid metabolism plays a central role in this pathology, especially in the setting of elevated low-density lipoprotein cholesterol (LDL-C). Furthermore, the protective capacity of high-density lipoprotein (HDL) is increasingly understood to depend on its functionality rather than absolute levels, as it can become dysfunctional and pro-inflammatory in pathological states. Emerging evidence has identified lipoprotein(a) [Lp(a)] and triglyceride-rich lipoproteins as significant, independent contributors to microvascular injury. Comprehensive clinical assessment of microvascular dysfunction therefore requires integration of advanced lipid profiling, including apolipoprotein B (ApoB), [Lp(a)], and the triglyceride-glucose (TyG) index with invasive and non-invasive measures of coronary flow reserve to more precisely stratify risk. In this narrative review, we synthesize current observational, mechanistic, and early interventional data linking diverse lipid phenotypes to coronary microvascular dysfunction. We propose a concept of lipid-driven CMD endotypes, such as ApoB-/particle overload, dysfunctional HDL, Lp(a)-mediated risk, and metabolic/TyG-high states, and map these to a practical, mechanism-informed management framework. While intensive LDL-C lowering with high-intensity statins and combination therapy remains guideline-directed care for high-risk patients, evidence for dedicated microvascular benefit from newer lipid and cardiometabolic agents is still largely hypothesis-generating. A personalized approach that aligns lipid phenotyping, CMD endotyping, and existing guideline-based therapies may help refine risk assessment and inform future trials.