Frailty and Cognitive Function After the Age of 40 in Adults With Moderate or Severe Congenital Heart Disease
Bibliographic record
Abstract
BACKGROUND Decades of progress in care and treatment for congenital heart disease (CHD) have gradually shifted the research focus from initial survival to long-term prognosis and the ageing of adults with CHD. Knowledge about the ageing adult with CHD will guide interventions to safeguard the quality of life across the life course. The present study compares the prevalence of frailty and cognitive dysfunction between adults with CHD and a control group. METHODS Using a multicenter design, we compared adults with moderate or complex CHD aged 40 or older, equally distributed 40-49, 50-59, and >60 years of age, with age and sex-matched controls. We assessed frailty phenotypes using the Fried method and cognitive dysfunction using the Montreal Cognitive Assessment (MoCA) tool. RESULTS In total, 156 adults with CHD (56.0 ± 10.4 years, 54.4% male) and 86 controls (55.6 ± 11.2 years, 55.8% male) were included in the study. Adults with CHD and controls did not differ in terms of mean score on the MoCa (mean score 27.1 vs. 26.9, p = 0.59). Similarly, there was no statistical difference in the prevalence of pre-frailty/frailty between adults with CHD and controls (36.5% vs. 29.0%, p = 0.26). CONCLUSION Prevalence rates of cognitive dysfunction and frailty were similar between adults with CHD and age-matched controls. As more patients, particularly those with complex heart lesions, reach older ages, the prevalence of cognitive impairment and frailty may change.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".