Determinants of Survival in Older Adults With Congenital Heart Disease Newly Hospitalized for Heart Failure
Bibliographic record
Abstract
BACKGROUND: Nearly 90% of patients with adult congenital heart disease (ACHD) die after the age of 40 years, and heart failure (HF) is the most common cause of death. We aimed to characterize the association between an incident HF hospitalization (HFH) and mortality and to identify the predictors of 1-year postdischarge mortality after incident and repeated HFHs, respectively. METHODS: Patients with ACHD aged ≥40 years between 2000 and 2010 were identified from the Québec CHD database. We conducted a propensity score-matched study to explore the association between an incident HFH and mortality. We performed Bayesian model averaging to identify the predictors of 1-year postdischarge mortality with a posterior probability ≥50% considered to be evidence of a significant association. RESULTS: The mortality hazard ratio was high at 6.01 (95% CI, 4.02-10.72) within 1-year postdischarge, decreasing significantly but entering an elevated equilibrium until year 4 with a continued 3-fold increase in death. Kidney dysfunction (hazard ratio, 2.28 [95% credible interval, 1.59-3.28], posterior probability, 100.0%) and a history of ≥2 HFHs in the past 12 months (hazard ratio, 1.77 [95% credible interval, 1.18-2.66], posterior probability: 82.2%) were the most robust predictors of 1-year mortality after incident and repeated HFHs, respectively. CONCLUSIONS: In patients with ACHD aged ≥40 years, incident HFH was associated with high mortality risk at 1 year, declining but remaining elevated for 4 years. Kidney dysfunction was a potent predictor of 1-year mortality risk after incident HFHs. Repeated HFHs further increased mortality risk. These observations should inform early risk-tailored health services interventions for monitoring and prevention of HF and its associated complications in older patients with ACHD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".