Kazemian, Sina

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.

Background/Objectives: Transcatheter aortic valve replacement (TAVR) has been introduced as an optimal treatment for patients with severe aortic stenosis, offering a minimally invasive alternative to surgical aortic valve replacement. Predicting these outcomes following TAVR is crucial. Artificial intelligence (AI) has emerged as a promising tool for improving post-TAVR outcome prediction. In this systematic review and meta-analysis, we aim to summarize the current evidence on utilizing AI in predicting post-TAVR outcomes. Methods: A comprehensive search was conducted to evaluate the studies focused on TAVR that applied AI methods for risk stratification. We assessed various ML algorithms, including random forests, neural networks, extreme gradient boosting, and support vector machines. Model performance metrics—recall, area under the curve (AUC), and accuracy—were collected with 95% confidence intervals (CIs). A random-effects meta-analysis was conducted to pool effect estimates. Results: We included 43 studies evaluating 366,269 patients (mean age 80 ± 8.25; 52.9% men) following TAVR. Meta-analyses for AI model performances demonstrated the following results: all-cause mortality (AUC = 0.78 (0.74–0.82), accuracy = 0.81 (0.69–0.89), and recall = 0.90 (0.70–0.97); permanent pacemaker implantation or new left bundle branch block (AUC = 0.75 (0.68–0.82), accuracy = 0.73 (0.59–0.84), and recall = 0.87 (0.50–0.98)); valve-related dysfunction (AUC = 0.73 (0.62–0.84), accuracy = 0.79 (0.57–0.91), and recall = 0.54 (0.26–0.80)); and major adverse cardiovascular events (AUC = 0.79 (0.67–0.92)). Subgroup analyses based on the model development approaches indicated that models incorporating baseline clinical data, imaging, and biomarker information enhanced predictive performance. Conclusions: AI-based risk prediction for TAVR complications has demonstrated promising performance. However, it is necessary to evaluate the efficiency of the aforementioned models in external validation datasets.

Background: Coronary in-stent restenosis (ISR) secondary to neointimal hyperplasia or neoatherosclerosis remains a significant challenge following percutaneous coronary interventions (PCI), with no consensus on the optimal revascularization strategy. We compared the outcome of PCI for ISR using drug-coated balloons (DCB) and drug-eluting stents (DES) and investigated the time trends in their clinical outcomes. Methods: PubMed, Embase, Scopus, and the Cochrane Library databases were searched through May 2024. We included randomized controlled trials (RCTs) comparing DCB versus DES among patients with coronary ISR. The primary outcome was target lesion revascularization (TLR). Secondary outcomes included all-cause mortality, myocardial infarction (MI), stent thrombosis, and late lumen loss (LLL). Random-effects models were employed to analyze outcomes within 1-year and beyond 1-year intervals. Meta-regression analysis was used to investigate the effect of age, sex, history of diabetes, hypertension, dyslipidemia, smoking, and ejection fraction on all outcomes by applying mixed-effect models. Results: We included 10 RCTs (1034 patients in the DCB group and 943 patients in the DES group). We found similar incidence of 1-year TLR (odds ratio [OR] 1.36; 95% confidence interval [CI] 0.86, 2.14; P 0.194; I 2 43.3%) and >1-year TLR (OR 0.94; 95% CI 0.57, 1.56; P 0.817; I 2 0%) with the use of DCB versus DES. The risks of all-cause mortality, MI, and stent thrombosis were comparable between DCB and DES in 1-year and beyond 1-year follow-ups. At 6-9 months angiographic follow-up, DCB was associated with non-significantly lower LLL compared to DES (standardized mean difference [SMD] -0.12 millimeters; 95% CI -0.29, 0.05; P 0.170; I 2 71.7%). Meta-regression indicated that higher prevalence of diabetes was associated with an increased risk of 1-year revascularization after DCB compared to DES (Estimate 0.07; P 0.003; I 2 0%). Additionally, male sex was associated with an increased LLL in DCB versus DES (Estimate 0.034; P 0.001; I 2 41.8%). No association was found between other baseline characteristics and measured clinical outcomes. Conclusion: DCB demonstrated comparable PCI outcomes compared to DES in patients with coronary ISR.