Frailty increases the risk of hospitalization for atrial fibrillation in older adults: a population-based cohort study
Bibliographic record
Abstract
BACKGROUND AND AIMS: Atrial fibrillation (AF) is more common with increasing age and older adults have greater prevalence of frailty, multimorbidity and polypharmacy, which may impact clinical outcomes. The present study aims to investigate the relationship between frailty and the risk of hospitalization for AF in older adults, and second, the possible interaction of multimorbidity in this association. METHODS AND RESULTS: Data from the Progetto Veneto Anziani (Pro.V.A.), an observational cohort study in north-eastern Italy, were utilised. The analyses included 2909 individuals aged ≥65 years without AF at baseline, assessed between 1995 and 1997, with follow-ups at 4.4 and 7 years. Frailty was defined according to Fried's criteria, and multimorbidity as the number of chronic diseases. AF-related hospitalizations and deaths were recorded up to December 31, 2018. Multi-adjusted mixed-effects Cox regressions were performed to test associations. Over the follow-up period, 318 (10.9 %) participants experienced AF-related hospitalizations. Compared to robust participants, the hazard ratio (HR) of hospitalizations due to AF was 1.42 (95 % Confidence Interval (95 %CI): 1.04-1.95) in pre-frail and 1.98 (95 %CI: 1.21-3.26) in frail individuals, even after adjusting for multimorbidity. The number of chronic diseases was only marginally and not significantly associated with AF-related hospitalizations (HR 1.07, 95 %CI: 0.99-1.15), but did not significantly interact with frailty in the association with AF-related hospitalizations. CONCLUSION: Older adults with frailty present with higher hazards of AF-related hospitalizations, irrespective of the presence of multimorbidity. Further studies are needed to evaluate whether reducing frailty may prevent AF development and improve health outcomes in older adults.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".