ECG Features Associated With Adverse Cardiovascular Outcomes in Patients With Atrial Fibrillation: A Combined AFFIRM and AF‐CHF Analysis
Bibliographic record
Abstract
BACKGROUND: The association between standard parameters from a simple 12-lead ECG (i.e., QRS duration and PR, JT, and QT intervals) and adverse cardiovascular outcomes (cardiovascular mortality, all-cause mortality, arrhythmic mortality, and hospitalizations) in patients with a history of atrial fibrillation (AF) has not been previously studied. METHODS AND RESULTS: A pooled analysis of patient-level data was conducted on 5,436 patients, age 68.2 ± 8.3 years, 34.8% female, with a history of non-permanent AF randomized in AFFIRM and AF-CHF trials. The predictive value of ECG parameters was assessed in AF and sinus rhythm in multivariate Cox regression models. During a follow-up of 40.8 ± 16.3 months, QRS duration >120 milliseconds was independently associated with all-cause mortality (hazard ratio [HR] 1.46, 95% confidence interval [CI; 1.21-1.76] in AF, P < 0.001), cardiovascular mortality (HR 1.75, 95% CI (1.15-2.65) in sinus rhythm, P = 0.009; HR 1.56, 95% CI [1.27-1.93] in AF, P < 0.001), arrhythmic mortality (HR 1.90, 95% CI [1.09-3.32] in sinus, P = 0.024; HR 1.84, 95% CI [1.35-2.51] in AF, P < 0.001), any hospitalization (HR 1.15, 95% CI [1.02-1.29] in AF, P = 0.027), and cardiovascular hospitalization (HR 1.21, 95% CI [1.06-1.37] in AF; P = 0.004). Increased PR interval (>200 milliseconds) was independently associated with cardiovascular (HR 1.56, 95% CI [1.11-2.21], P = 0.010) and arrhythmic (HR 1.91, 95% CI [1.14-3.18], P = 0.004) mortality. The JT and QTc intervals were not predictive of mortality. CONCLUSIONS: Simple parameters from standard ECGs are significantly and independently associated with adverse cardiovascular outcomes in patients with a history of AF.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".