Risk of stroke in chronic heart failure patients with preserved ejection fraction, but without atrial fibrillation: analysis of the CHARM-Preserved and I-Preserve trials
Bibliographic record
Abstract
AIMS: The incidence and predictors of stroke in patients with heart failure and preserved ejection fraction (HF-PEF), but without atrial fibrillation (AF), are unknown. We described the incidence of stroke in HF-PEF patients with and without AF and predictors of stroke in those without AF. METHODS AND RESULTS: We pooled data from the CHARM-Preserved and I-Preserve trials. Using Cox regression, we derived a model for stroke in patients without AF in this cohort and compared its performance with a published model in heart failure patients with reduced ejection fraction (HF-REF)-predictive variables: age, body mass index, New York Heart Association class, history of stroke, and insulin-treated diabetes. The two stroke models were compared and Kaplan-Meier curves for stroke estimated. The risk model was validated in a third HF-PEF trial. Of the 6701 patients, 4676 did not have AF. Stroke occurred in 124 (6.1%) with AF and in 171 (3.7%) without AF (rates 1.80 and 1.00 per 100 patient-years, respectively). There was no difference in performance of the stroke model derived in the HF-PEF cohort and the published HF-REF model (c-index 0.71, 95% confidence interval 0.57-0.84 vs. 0.73, 0.59-0.85, respectively) as the predictive variables overlapped. The model performed well in the validation cohort (0.86, 0.62-0.99). The rate of stroke in patients in the upper third of risk approximated to that in patients with AF (1.60 and 1.80 per 100 patient-years, respectively). CONCLUSIONS: A small number of clinical variables identify a subset of patients with HF-PEF, but without AF, at elevated risk of stroke.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".