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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: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.

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.

Background: Among cardiac amyloidosis subtypes, transthyretin cardiac amyloidosis (ATTR) has gained increased recognition with the development of disease-specific therapies. Tafamidis, a selective oral stabilizer of the transthyretin tetramer, has emerged as an effective treatment. In the broader heart failure landscape, sodium-glucose cotransporter 2 inhibitors (SGLT2i) have become cornerstone therapies across the ejection fraction spectrum, improving survival and reducing hospitalizations in both HFrEF and HFpEF. However, the clinical benefit of combining Tafamidis with SGLT2i in ATTR remains largely unknown. Hypothesis: Combination therapy with Tafamidis and SGLT2i provides added clinical benefits in patients with ATTR cardiac amyloidosis. Methods: This retrospective cohort study included adults with confirmed ATTR cardiac amyloidosis diagnosed via 99mTc-pyrophosphate scintigraphy and treated with Tafamidis alone or with an SGLT2i across three academic centers from January 2019 to February 2025. Baseline characteristics and outcomes were collected from medical records. The primary endpoint was all-cause mortality. Kaplan-Meier analysis and multivariable Cox proportional hazards modeling were used, adjusting for age, sex, atrial fibrillation, diabetes, hypertension, hyperlipidemia, ejection fraction (EF), and glomerular filtration rate (GFR). Results: Among the 1,211 patients included in the 3-year follow-up analysis,946 received Tafamidis monotherapy and 265 received a combination of Tafamidis and an SGLT2i. The mean age of the cohort was 71.9 years (SD ±9.4), and 87.3% were male. A total of 142 mortality events occurred, with a higher cumulative mortality rate observed in the tafamidis-only group (16.3%) compared to the combination group (9.4%) (log-rank p = 0.042). In the multivariable Cox proportional hazards model, combination therapy with Tafamidis and an SGLT2i was independently associated with a significantly lower risk of mortality (adjusted HR =0.576, 95% CI:0.334–0.992, p =0.04). Additionally, increasing age (HR =1.049, 95% CI:1.024–1.074, p < 0.001) was associated with higher mortality, while EF(HR =0.971, 95% CI:0.958–0.984, p< 0.001) and GFR (HR =0.975, 95% CI:0.965-0.985, p< 0.001) were with lower mortality. Conclusion: Combination therapy with Tafamidis and SGLT2i was associated with improved survival compared to Tafamidis alone in ATTR cardiac amyloidosis. Further prospective trials are needed to validate these findings and guide therapy optimization.

Background: High serotonin from neuroendocrine tumors (NETs) can result in carcinoid heart disease (CaHD) with severe valve dysfunction, often requiring valve replacement surgery. Lutetium-177 (Lu-177), a targeted radioactive isotope therapy, is increasingly utilized in the treatment of NETs; however, there is limited data on its impact on bioprosthetic heart valves (BHVs) in CaHD. Methods: A retrospective review was conducted on all patients with stage IV metastatic NET who underwent BHV replacement at three tertiary centers in the United States. Patients were stratified by Lu-177 therapy, administered after valve replacement. A propensity matched cohort of CaHD patients with BHV who did not received Lu-177 was curated including age, sex, and baseline left ventricular ejection fraction. Serial transthoracic echocardiograms (TTEs) following surgery were evaluated for progression of BHV degeneration; rise in mean gradient or increase in grade of prosthetic/periprosthetic regurgitation (grade increase of ≥1 out of 5), from first TTE following surgery (TTE1) to most recent TTE (TTE2). Analysis was performed at the level of individual valves, recognizing that some patients had more than one valve implanted. To account for changes in Lu-177 exposure over time, we constructed a time-varying Cox proportional hazards model. Accounting for non-independence of multiple valves within the same patient, a clustered Cox model was fitted using robust standard errors. Mortality was compared between patients exposed to Lu-177 therapy and those not exposed. Results: 184 patients were identified, mean age 60.4 ± 10.3 years, 53.3 % male. Of these, 16 patients had Lu-177 therapy, with 45 individual BHVs within this group. Patients in the control group had a total of 60 BHVs. Across a median of 2.09 years [0.77-5.01] between TTE1 and TTE2, BHVs exposed to Lu-177 therapy demonstrated an increased risk of BHV degeneration (HR=2.44, 95% CI 1.05–5.69, p=0.038), accounting for the time between TTE1 and administration of Lu-177 and the non-independence of multiple BHVs within the same patient. There was no significant difference in mortality between the two cohorts (p=0.440). Conclusions: BHVs in patients with CaHD exposed to Lu-177 therapy demonstrated an increased risk of degeneration. These findings suggest an association between Lu-177 treatment and accelerated prosthetic valvular deterioration, warranting further investigation and close monitoring in this patient population.

Introduction: Elevated lipoprotein(a) [Lp(a)] levels (≥30 mg/dL or ≥50 mg/dL) have been associated with increased risk of cardiovascular diseases (CVD), including myocardial infarction and aortic stenosis. However, its association with all-cause mortality (ACM) in the setting of primary prevention remains unclear, with conflicting evidence regarding the cutoff associated with increased mortality risk. Objective: To assess the association between elevated Lp(a) and risk of ACM in the context of primary prevention. Methods: In this retrospective cohort study, we included adult patients (≥18 years old) who had at least one measurement of Lp(a) at any of the three Mayo Clinic sites between 2007 and 2024, with no history of CVDs (i.e., coronary artery disease, ischemic stroke/transient ischemic attack, or peripheral arterial disease) at the time of Lp(a) measurement. Lp(a) levels were categorized based on the following percentiles: ≤50th percentile (≤11.6 mg/dL), 50th to 80th percentiles (11.6–46.6 mg/dL), 80th to 90th percentiles (46.6–75 mg/dL), 90th to 95th percentiles (75–100 mg/dL), and >95th percentile (>100 mg/dL). Survival probabilities up to 15 years were compared across Lp(a) percentile categories using the Kaplan–Meier estimator and log-rank test. Additionally, univariable and multivariable Cox regression analyses were conducted to adjust for potential CV confounders and to quantify this association. Results: A total of 42,770 patients (median age: 53 years and 54% males) were included. We found no significant difference in survival probabilities between the Lp(a) categories based on the overall log-rank test (p=0.12; Figure 1A ). In the univariable analysis, only patients with Lp(a) >95th percentile (>100 mg/dL) had a statistically significant higher risk of ACM [hazard ratio (HR): 1.37; 95%CI: 1.07–1.74; p=0.012], compared to patients with Lp(a) <50th percentile (<11.6 mg/dL). Similarly, after adjusting for potential CV risk factors, only those with Lp(a) >95th percentile (>100 mg/dL) showed a significantly higher risk of ACM (adjusted HR: 1.37; 95%CI: 1.07–1.75; p=0.012, Figure 1B ). Conclusion: In the setting of primary prevention, only very high Lp(a) levels (≥100 mg/dL) were independently associated with increased risk of ACM, suggesting that higher Lp(a) thresholds may be more relevant for identifying individuals at increased risk of ACM than the conventional ≥50 mg/dL cutoff.