Ntsekhe, Mpiko

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.

Abstract Aims Rheumatic heart disease (RHD) remains the most prevalent acquired cardiovascular disease among young adults in developing countries, and there is a critical need for an efficient, affordable, and available screening strategy to detect RHD in these resource-limited areas. The 12-lead electrocardiogram (ECG) is a ubiquitous, inexpensive diagnostic tool, and application of artificial intelligence to the ECG (AI-ECG) has allowed for screening of various cardiovascular pathologies. Methods and results Patients aged >18 years with severe RHD with at least one transthoracic echocardiogram and one standard 12-lead ECG performed at Groote Schuur Hospital, Cape Town, within 180 days of each other were eligible. A total of 920 RHD patients were identified, with 2199 corresponding controls from the same medical centre. Patients were allocated to derivation (80%), validation (10%), and testing (10%) groups, respectively. The AI-ECG to detect RHD from a standard 12-lead ECG was built using the Keras framework under Tensorflow backend. In the test group, the AI-ECG for RHD exhibited strong algorithm performance with an AUC of 0.890 (95% Confidence Interval 0.848–0.940) and an accuracy of 83.8%. The algorithm remained robust between RHD presentation: mitral valve alone (AUC 0.913) and mixed mitral and aortic valve disease (AUC 0.858). There were minor performance differences in the subgroup analysis of patient sex, age, and ECG characteristics. Conclusion In this study, an AI-ECG algorithm was successfully developed to screen for advanced RHD from a standard 12-lead ECG, and the AI-ECG performance remained acceptable across most subgroups, including RHD manifestation, patient sex, age <70 years, and ECG characteristics.

Objective The prevalence, predictors and outcome of myopericarditis in patients with tuberculous (TB) pericarditis are unknown. Methods Eighty-one patients (mean age±SD, 36.1±13.3 years; 54 (66.7%) men; 58 (71.6%) HIV seropositive) with TB pericarditis were recruited between January 2006 and September 2008. Myopericarditis was defined as echocardiographic LV systolic dysfunction (immediately after pericardiocentesis), elevated peripheral blood troponin T (>0.03 ng/mL), or elevated peripheral blood creatine kinase (CK >174 IU/L) with a CK:CK-myocardial band (MB) mass ratio of >6%. The outcome measure was case fatality rate at 6 months of follow-up. Results Myopericarditis was present in 43 (53.1%) patients. Patients with myopericarditis, as compared with those without, were more likely to be HIV seropositive (35 (81.4%) vs 23 (60.5%) respectively, p=0.038) and have lower peripheral CD4 count (median (IQR) 98 (54–290) vs 177 (104–429), p=0.026). Electrocardiographic ST segment elevation was more common in myopericarditis (15 (36.6%) vs 4 (10.8%), p=0.008) and predicted myopericarditis independently of CD4 count on multiple logistic regression analysis (OR 4.36, 95% CI 1.34 to 17.34, p=0.0132). At 6 months, 14 (18%) patients had died with no significant difference between those with or without myopericarditis (6/42 (14%) vs 8/36 (22%), respectively (p=0.363)). Conclusions Myopericarditis is common in TB pericardial effusion and associated with HIV-related immunosuppression. It can be identified by electrocardiographic ST-elevation, particularly when peripheral CD4 count is low. There was no significant difference in case fatality rate in those with or without myopericarditis.