Global, Regional, and National Burden of Myocarditis and Cardiomyopathy, 1990–2017
Bibliographic record
Abstract
Objective: To estimate the burden of myocarditis (MC), alcoholic cardiomyopathy (AC), and other cardiomyopathy (OC) for 195 countries and territories from 1990 to 2017. Methods: We collected detailed information on MC, AC, and OC between 1990 and 2017 from the Global Burden of Disease study 2017, which was designed to provide a systematic assessment of health loss due to diseases and injuries in 21 regions, covering 195 countries and territories. Estimates of MC, AC, and OC burden were produced using a standard Cause of Death Ensemble model and a Bayesian mixed-effects meta-regression tool, and included prevalence, deaths, years lived with disability (YLDs), and years of life lost (YLLs). All estimates were presented as counts, age-standardized rates per 100,000 people and percentage change, with 95% uncertainty intervals (UIs). Results: Worldwide, there were 1.80 million (95% UI 1.64–1.98) cases of MC, 1.62 million (95% UI 1.37–1.90) cases of AC and 4.21 million (95% UI 3.63–4.87) cases of OC, contributing to 46,486 (95% UI 39,709–51,824), 88,890 (95% UI 80,935–96,290), and 233,159 (95% UI 213,677–248,289) deaths in 2017, respectively. Furthermore, globally, there were 131,376 (95% UI 90,113–183,001) YLDs and 1.26 million (95% UI 1.10–1.42) YLLs attributable to MC, 139,087 (95% UI 95,134–196,130) YLDs and 2.84 million (95% UI 2.60–3.07) YLLs attributable to AC, and 353,325 (95% UI 237,907–493,908) YLDs and 5.51 million (95% UI 4.95–5.99) YLLs attributable to OC in 2017. At the national level, the age-standardized prevalence rates varied by 10.4 times for MC, 252.6 times for AC and 38.1 times for OC; the age-standardized death rates varied by 43.9 times for MC, 531.0 times for AC and 43.3 times for OC; the age-standardized YLD rates varied by 12.4 times for MC, 223.7 times for AC, and 34.1 times for OC; and the age-standardized YLL rates varied by 38.4 times for MC, 684.8 times for AC, and 36.2 times for OC. Between 1990 and 2017, despite the decreases in age-standardized rates, the global numbers of prevalent cases, deaths, YLDs, and YLLs have increased for all the diseases. Conclusion: Accurate assessment of the burden of MC, AC, and OC is essential for formulating effective preventative prevention and treatment programs and optimizing health system resource allocation. Our results suggest that MC, AC, and OC remain important global public health problems with increasing numbers of prevalent cases, deaths, YLDs, and YLLs over the past decades, and there are significant geographic variations in the burden of these diseases. Further research is warranted to expand our knowledge of potential risk factors and to improve the prevention, early detection and treatment of these diseases.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".