Prevalence and Incidence of Dilated Cardiomyopathy in the United States and Western Europe: A Systematic Review
Bibliographic record
Abstract
Background: Dilated cardiomyopathy (DCM) is a major contributing factor for heart failure and cardiac transplantation worldwide. Estimating the prevalence and incidence of DCM is critical for understanding the burden of illness in these patients and improving the landscape of preventative treatments. Previous reviews have shown substantial prevalence and incidence estimates for DCM within key regions such as the United States and several European countries. This review aimed to describe the published evidence on the prevalence and incidence of DCM within the United States, France, Germany, Italy, Spain, and the United Kingdom. Methods: and Embase were searched from database inception to May 9, 2023 for English-language studies reporting the prevalence or incidence of DCM within general populations of adults or children in countries of interest. Manual searches of relevant conferences and bibliographies of previous literature reviews were also conducted. Results: Of 6,145 identified articles, 10 unique studies were included in the review. Six studies reported prevalence, and five studies reported incidence of DCM in various populations. Prevalence estimates of DCM, including idiopathic and non-idiopathic causes, within adults (≥ 18 years) and/or heterogeneous (all ages) populations ranged from 42.8 to 118.3 per 100,000 persons; idiopathic DCM estimates ranged from 8.3 to 59.2 per 100,000 persons. Prevalence of adolescent (about 11 - 18 years) DCM, including idiopathic and non-idiopathic causes, ranged from 2.6 to 212.8 per 100,000 persons. Annual incidence rates of idiopathic DCM in adult/heterogeneous populations ranged from 6.0 to 7.0 per 100,000 persons. Annual incidence of DCM due to idiopathic/non-idiopathic causes among pediatric populations was reported as 0.6 per 100,000 persons. Reported prevalence and incidence rates by sex showed male preponderance, and estimates were higher in Black persons compared with White and Hispanic persons; higher DCM prevalence estimates were observed in studies utilizing newer DCM definitions using ICD coding compared with older definitions. Conclusion: This study highlights the varied prevalence and incidence rates of DCM reported across different geographic locations, time periods, sexes, races, and disease definitions. When comparing these rates, it is crucial to consider factors such as data sources, case definitions, case-finding methodologies, and study populations.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".