Stroke in adults with congenital heart disease: Incidence and predictors
Bibliographic record
Abstract
Background: Stroke is an important cause of morbidity in adults with congenital heart disease (ACHD). However there is a lack of comprehensive data on the incidence and predictors of stroke in ACHD. Objective: To estimate the cumulative risk and incidence of stroke in ACHD, evaluate the role of different lesion categories and determine the most important predictors of stroke and their impact in ACHD. Methods: This retrospective study of 28,465 ACHD Quebec patients aged 18 to 64 years between 1998 and 2010 was based on aggregated province-wide administrative data. Lesions were classified as severe if they had a high probability of being associated with cyanosis or requiring early surgical intervention and as shunt lesions if defects primarily led to a mixture of oxygenated and deoxygenated blood; the remaining were categorized as right- and left-sided according to lateralization. In this dynamic cohort the cumulative incidence of stroke (ischemic and hemorrhagic combined) was adjusted for the competing risk of death and incidence rates were age- and sex-standardized to reference populations. Previously reported stroke-rates for women in the general population of Quebec in 2002 were 11 per 100,000 population for age-group 15-54 and 82 per 100,000 for age-group 55-64; corresponding rates for men were 18 per 100,000 (age-group 15-54) and 142 per 100,000 (age-group 55-64). By means of Cox proportional hazard (CPH) models with age as the time-scale and adjusted for classic cardiovascular risk factors the independent effect of different lesion categories was evaluated. The relevance of potential predictors was assessed in a nested case-control subcohort by a combination of stepwise model selection and Bayesian model averaging. To focus in on the absolute effect of newly diagnosed heart failure a propensity score matched cohort was created. The potential for information and selection bias was addressed by means of sensitivity analysis. Results: For an 18 year old patient the estimated overall cumulative risk of experiencing a stroke up to age 64 was 8.7% (95%-confidence interval (7.8 -9.5%). In males severe lesions accounted for the highest cumulative incidence with 16.2% (95%-CI: 10.3-21.2%), in females the left-sided lesions with 11.9% (95%-CI: 9.0-14.7%). Women had a 27% lower age-standardized stroke rate than men (incidence rate ratio: 0.73 (95%-CI: 0.60-0.88)). For females incidence rates age-standardized to the mid-year 2002 Quebec population were 11 per 100,000 population in age-group 20-54 and 82 per 100,000 in age-group 55-64; in males rates were 18 (age-group 20-54) and 142 per 100,000 (age-group 55-64) respectively. Contrasting severe to shunt lesions the hazard ratio (HR) of stroke was 3.10 (95%-CI: 2.05-4.51) for patients 18 to 44 years of age and 1.29 (0.80-2.01) for the 45 to 64 years old; for left-sided lesions HRs were 2.24 (1.51, 3.30) and 1.29 (0.98-1.69). Heart failure, diabetes, chronic kidney disease and lesion category emerged as the strongest predictors for stroke from Bayesian model averaging. Patients receiving their first diagnosis of heart failure had an absolute stroke risk of 6.7% (95%-CI 4.4-10.2%) over ten years of follow up compared to a risk of 3.1% (95%-CI: 2.0 – 4.9%) in non-heart failure patients (stratified log-rank test: p-value = 0.01); however CPH-analysis showed that the elevated risk was mainly contained in the first two years of follow-up.Conclusion: Stroke is 10 times more common in ACHD-patients than in the general population below age 55 and 2.5-4.5 times more common in patients aged 55 to 64. Severe and left-sided lesions are the lesion categories conveying the highest risk of stroke, in particular at younger age. Heart failure, diabetes and chronic kidney disease are the comorbidities with the strongest predictive ability for stroke. Further research is required to see if early detection and modifications of these risk factors may reduce the stroke rate in the ACHD 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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".