Aims: Endocarditis accounts for significant morbidity and mortality. Timely diagnosis and prompt treatment are of paramount importance for optimal patient outcome. However, only few studies have assessed quality of care (QoC) in endocarditis. We aimed to describe QoC and changes in epidemiological features of endocarditis from 1990 to 2019. Methods and results: Using primary indices of mortality, incidence, years of life lost, years lived with disability, and disability-adjusted life year, obtained from the Global Burden of Disease Study 2019, we calculated four secondary measures. Principal component analysis was performed to calculate QoC index (QCI), scored on a scale of 0–100 with higher values indicating better QoC, for different locations, age groups, and genders from 1990 to 2019. The all-ages incidence rate of endocarditis was estimated to increase significantly from 1990 to 2019, while mortality rate did not change. The age-standardized QCI was 73.6% globally, with higher values in high-income countries than in low-income countries. High-income North America (82.0%) and Asia Pacific (81.1%) had the highest QCI, whereas Eastern Europe (43.3%) had the lowest. Globally, the 30–49 and 95+ age groups had the highest (91.3%) and the lowest (71.7%) QCI, respectively. In most countries, particularly those with lower socio-demographic index, women had better QCI. Conclusion: This is the first global assessment of QCI, shedding light on the current trends and highlighting the necessity of improving the endocarditis QoC, mainly by timely case detection, adherence to antibiotic prophylaxis guidelines, utilizing targeted antibiotics and advanced treatments, in the African region and resolving gender inequality in selected countries.

Background: Rheumatic heart disease (RHD) takes a heavy toll in low‐ and middle‐income countries. We aimed to present worldwide estimates for the burden of the RHD during 1990 to 2019 using the GBD (Global Burden of Disease) study. Methods and Results: Sociodemographic index (SDI) and age‐period‐cohort analysis were used to assess inequity. The age‐standardized death, disability‐adjusted life years, incidence, and prevalence rates of RHD were 3.9 (95% uncertainty interval, 3.3–4.3), 132.9 (95% uncertainty interval, 115.0–150.3), 37.4 (28.6–46.7), and 513.7 (405.0–636.3) per 100 000 in 2019, respectively. The age‐standardized incidence and prevalence rates increased by 14.4% and 13.8%, respectively. However, disability‐adjusted life years and death rates decreased by 53.1% and 56.9%, respectively. South Asia superregion had the highest age‐standardized disability‐adjusted life years and deaths. Sub‐Saharan Africa had the highest age‐standardized incidence and prevalence rates. There was a steep decline in RHD burden among higher‐SDI countries. However, only age‐standardized deaths and disability‐adjusted life years rates decreased in lower‐SDI countries. The age‐standardized years of life lost and years lived with disability rates for RHD significantly declined as countries' SDI increased. The coefficients of birth cohort effect on the incidence of RHD showed an increasing trend from 1960 to 1964 to 2015 to 2019; however, the birth cohort effect on deaths attributable to RHD showed unfailingly decreasing trends from 1910 to 1914 to 2015 to 2019. Conclusions: There was a divergence in the burden of RHD among countries based on SDI levels, which calls for including RHD in global assistance and funding. Indeed, many countries are still dealing with an unfinished infectious disease agenda, and there is an urgency to act now to prevent an increase in future RHD burden.

Bladder cancer is among the leading causes of cancer death worldwide. Data on the bladder cancer burden are valuable for policy-making. We aimed to estimate the burden of bladder cancer by country, age group, gender and sociodemographic status between 1990 and 2016. Data from vital registration systems and cancer registries were the input to estimate the bladder cancer burden. Mortality was estimated in an ensemble model approach, incidence was estimated by dividing mortality by the mortality-to-incidence ratio and prevalence was estimated using the mortality-to-incidence ratio as a surrogate for survival. We modeled the years lived with disability using disability weights of bladder cancer sequelae. Years of life lost were calculated by multiplying the number of deaths by age by the standard life expectancy at that age. Disability adjusted life-years were calculated by summing the years lived with disability and the years of life lost. Moreover, we also estimated the burden attributable to bladder cancer risk factors, smoking and high fasting plasma glucose using the comparative risk assessment framework of the Global Burden of Disease study. In 2016 there were 437,442 incident cases (95% UI 426,709-447,912) of bladder cancer with an age standardized incidence rate of 6.69/100,000 (95% UI 6.52-6.85). Bladder cancer led to 186,199 deaths (95% UI 180,453-191,686) in 2016 with an age standardized rate of 2.94/100,000 (95% UI 2.85-3.03). Bladder cancer was responsible for 3,315,186 disability adjusted life-years (95% UI 3,193,248-3,425,530) in 2016 with an age standardized rate of 49.45/100,000 (95% UI 47.68-51.11). Of bladder cancer deaths 26.84% (95% UI 19.78-33.91) and 7.29% (95% UI 1.49-16.19) were due to smoking and high fasting glucose, respectively, in 2016. Although the number of bladder cancer incident cases is growing globally, the age standardized incidence and number of deaths are decreasing, as mirrored by a decreasing smoking contribution.

Background: Thyroid cancer (TC) is the most prevalent malignancy of the endocrine system. Over the past decades, TC incidence rates have been increasing. TC quality of care (QOC) has yet to be well understood. We aimed to assess the quality of TC care and its disparities.Methods: We retrieved primary epidemiologic indices from the Global Burden of Disease (GBD) 1990–2017 database. We calculated four secondary indices of mortality to incidence ratio, disability‐adjusted life years (DALYs) to prevalence ratio, prevalence to incidence ratio, and years of life lost (YLLs) to years lived with disability (YLD) ratio and summarized them by the principal component analysis (PCA) to produce one unique index presented as the quality of care index (QCI) ranged between 0 and 100, to compare different scales. The gender disparity ratio (GDR), defined as the QCI for females divided by QCI for males, was applied to show gender inequity.Results: In 2017, there were 255,489 new TC incident cases (95% uncertainty interval [UI]: 245,709–272,470) globally, which resulted in 41,235 deaths (39,911–44,139). The estimated global QCI was 84.39. The highest QCI was observed in the European region (93.84), with Italy having the highest score (99.77). Conversely, the lowest QCI was seen in the African region (55.09), where the Central African Republic scored the lowest (13.64). The highest and lowest socio‐demographic index (SDI) regions scored 97.27 and 53.85, respectively. Globally, gender disparity was higher after the age of 40 years and in favor of better care in women.Conclusion: TC QOC is better among those countries of higher socioeconomic status, possibly due to better healthcare access and early detection in these regions. Overall, the quality of TC care was higher in women and younger adults. Countries could adopt the introduced index of QOC to investigate the quality of provided care for different diseases and conditions.

Background and Aims: Current heart failure (HF) risk stratification strategies require comprehensive clinical evaluation. In this study, artificial intelligence (AI) applied to electrocardiogram (ECG) images was examined as a strategy to predict HF risk. Methods: Across multinational cohorts in the Yale New Haven Health System (YNHHS), UK Biobank (UKB), and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), individuals without baseline HF were followed for the first HF hospitalization. An AI-ECG model that defines cross-sectional left ventricular systolic dysfunction from 12-lead ECG images was used, and its association with incident HF was evaluated. Discrimination was assessed using Harrell’s C-statistic. Pooled cohort equations to prevent HF (PCP-HF) were used as a comparator. Results: Among 231 285 YNHHS patients, 4472 had primary HF hospitalizations over 4.5 years (inter-quartile range 2.5–6.6). In UKB and ELSA-Brasil, among 42 141 and 13 454 people, 46 and 31 developed HF over 3.1 (2.1–4.5) and 4.2 (3.7–4.5) years. A positive AI-ECG screen portended a 4- to 24-fold higher risk of new-onset HF [age-, sex-adjusted hazard ratio: YNHHS, 3.88 (95% confidence interval 3.63–4.14); UKB, 12.85 (6.87–24.02); ELSA-Brasil, 23.50 (11.09–49.81)]. The association was consistent after accounting for comorbidities and the competing risk of death. Higher probabilities were associated with progressively higher HF risk. Model discrimination was 0.718 in YNHHS, 0.769 in UKB, and 0.810 in ELSA-Brasil. In YNHHS and ELSA-Brasil, incorporating AI-ECG with PCP-HF yielded a significant improvement in discrimination over PCP-HF alone. Conclusions: An AI model applied to a single ECG image defined the risk of future HF, representing a digital biomarker for stratifying HF risk.