P3481Incremental value of the Essential Frailty Toolset for fatal and nonfatal adverse events in older adults with atrial fibrillation undergoing cardiac procedures
Bibliographic record
Abstract
Background: Atrial fibrillation (AF) is associated with a greater risk of fatal and nonfatal adverse events in older adults with coronary and heart valve disease. The CHADS2 and HAS-BLED scores are recommended to stratify risk in these patients but they do not consider critical non-cardiac factors such as frailty. Purpose: To determine whether frailty is incrementally predictive of death, stroke and major bleeding events in older adults with atrial fibrillation undergoing surgical or transcatheter cardiac procedures. Methods: Posthoc analysis of a multicenter prospective cohort study, in which older adults 70 years and above were enrolled in Canada, the United States, and France between 2012–2017. For the purposes of this analysis, patients with pre-exisiting AF were retained if they underwent coronary artery bypass grafting, surgical valve repair or replacement, transcatheter aortic valve replacement or combined procedures. Frailty was assessed by trained observer pre-procedure using the Essential Frailty Toolset (EFT) comprised of five timed chair rises, cognitive testing, serum albumin and hemoglobin; with scores ≥3 out of 5 indicating frailty. The primary endpoint was a composite of 30-day all-cause death, stroke or major bleed. The secondary endpoint was 1-year all-cause death. Logistic regression models were adjusted for the Society of Thoracic Surgeons-predicted risk of mortality, procedure type, the CHADS2 and modified HAS-BLED scores.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".