Global, regional, and national burden of myocarditis and cardiomyopathy, 1990-2017
Bibliographic record
Abstract
Abstract Background To estimate the burden of myocarditis (MC) and cardiomyopathy for 195 countries and territories from 1990 to 2017. Methods We collected detailed information on MC and cardiomyopathy between 1990 and 2017 from the Global Burden of Disease study (GBD) 2017. Cardiomyopathy was divided into two types in GBD 2017, including alcoholic cardiomyopathy (AC) and other cardiomyopathy (OC). All estimates were presented as counts, age-standardised rates per 100 000 people and percentage change, with 95% uncertainty intervals (UIs). Results Worldwide, there were 1.80 million (95% UI 1.64 to 1.98) cases of MC, 1.62 million (95% UI 1.37 to 1.90) cases of AC and 4.21 million (95% UI 3.63 to 4.87) cases of OC, contributing to 46 486 (95% UI 39 709 to 51 824), 88 890 (95% UI 80 935 to 96 290) and 233 159 (95% UI 213 677 to 248 289) deaths in 2017, respectively. At the national level, the age-standardised prevalence rates varied by 10.4 times for MC, 252.6 times for AC and 38.1 times for OC; and the age-standardised death rates varied by 43.9 times for MC, 531.0 times for AC and 43.3 times for OC. Between 1990 and 2017, despite the decreases in age-standardised rates, the global numbers of prevalent cases and deaths have significantly increased for all the diseases. Females had greater decreases in age-standardised prevalence and death rates than males for all the diseases. Conclusions MC, AC and OC remain important global public health problems, and there are significant geographic variations in the burden for all these diseases. More effective and geo-specific strategies are necessary to counteract and mitigate the future burden of these diseases. Key questions What is already known? ➢ Myocarditis (MC), alcoholic cardiomyopathy (AC) and other cardiomyopathy (OC) impose a substantial economic burden on healthcare systems. Studies that have systematically assessed the global, regional, and national burden of these diseases are still scarce. What are the new findings? ➢ Globally, there were an estimated 1.80 million (95% uncertainty interval (UI) 1.64 to 1.98) cases of MC, 1.62 million (95% UI 1.37 to 1.90) cases of AC and 4.21 million (95% UI 3.63 to 4.87) cases of OC in 2017. ➢ The global numbers of deaths due to MC, AC, and OC in 2017 were 46 486 (95% UI 39 709 to 51 824), 88 890 (95% UI 80 935 to 96 290) and 233 159 (95% UI 213 677 to 248 289), respectively. ➢ Across 21 world regions, the highest age-standardised prevalence rates of MC, AC and OC were seen in High-income Asia Pacific, Eastern Europe and Southern Sub-Saharan Africa, respectively. While the highest age-standardised death rates of MC, AC and OC were seen in Oceania, Eastern Europe and Central Europe, respectively. ➢ Despite the decreases in age-standardised rates, the global numbers of prevalent cases and deaths of MC, AC and OC have significantly increased between 1990 and 2017. What do the new findings imply? ➢ Our findings suggested that total numbers of prevalent cases and deaths of MC, AC and OC are increasing worldwide. More effective and geo-specific strategies aimed at counteracting and mitigating the future burden of these diseases are warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".