Lifetime Prevalence of Congenital Heart Disease in the General Population From 2000 to 2010
Bibliographic record
Abstract
BACKGROUND: Our objective was to obtain contemporary lifetime estimates of congenital heart disease (CHD) prevalence using population-based data sources up to year 2010. METHODS AND RESULTS: The Quebec CHD database contains 28 years of longitudinal data on all individuals with CHD from 1983 to 2010. Severe CHD was defined as tetralogy of Fallot, truncus arteriosus, transposition complexes, endocardial cushion defects, and univentricular hearts. We used latent class bayesian models combining case definitions from physician claims, hospitalization, and surgical data to obtain point and interval prevalence estimates of CHD in the first year of life, in children (<18 years of age) and in adults. We identified 107 559 CHD patients from 1983 to 2010. Prevalence of CHD in the first year of life was 8.21 per 1000 live births (95% confidence interval, 7.47-9.02) from 1998 to 2005. In 2010, overall prevalence of CHD was 13.11 per 1000 (95% confidence interval, 12.43-13.81) in children and 6.12 per 1000 (95% confidence interval, 5.69-6.57) in adults. CHD prevalence increased by 11% in children and 57% in adults from 2000 to 2010. Prevalence in the severe CHD subgroup increased by 19% (95% confidence interval, 17%-21%) in children and 55% (51%-62%) in adults. By 2010, adults accounted for 66% of the entire CHD population. CONCLUSIONS: With an increase of >50% in CHD prevalence since 2000, by 2010 adults accounted for two thirds of patients with severe and other forms of CHD in the general population. Our findings should inform allocation of resources and the planning of workforce needs for the predominantly adult CHD population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".