Abstract 17352: Incidence and Predictors of Stroke in Patients with Chronic Heart Failure: Does Left Ventricular Function Matter? Insights From the CHARM Program
Bibliographic record
Abstract
Objectives Patients with heart failure and reduced ejection fraction (HF-REF) are at increased risk of stroke, with some studies suggesting an inverse association between ejection fraction (EF) and stroke risk. The rate of stroke in simultaneously enrolled patients with HF-REF and preserved EF (HF-PEF) has not been reported and the predictors of stroke in a contemporary population of patients with HF are unknown. The Candesartan in Heart Failure: Assessment of Reduction in Mortality and morbidity (CHARM) program, which included patients with a wide range of EF, provided a unique opportunity to examine these questions about stroke in HF. Methods We evaluated risk factors for stroke with multivariable Cox proportional hazard regression analysis using forward- and backward-stepwise selection of candidate variables, with gender, history of hypertension, EF and randomized treatment (i.e. candesartan) forced into the model. Results Of the 7599 participants in CHARM, 287 (3.8%) experienced a fatal or nonfatal stroke during a median follow-up of 37.7 months. The stroke rate was 1.3 (95% CI=1.1-1.5) and 1.4 (95% CI=1.2-1.7) per 100 pt yrs in subjects with reduced and preserved EF respectively. The 5 strongest predictors of stroke (ranked by chi-square value) were: older age, previous stroke, higher systolic blood pressure, diabetes and atrial fibrillation on baseline ECG; other independent predictors are shown in the figure. Univariate predictors not retained in the multivariable model were: history of hypertension, NYHA class III or IV, baseline oral anticoagulant use, previous coronary bypass surgery, current smoking, signs of HF, diuretic use and female sex; none of the other forced variables were predictive in either the univariate or multivariable models. Conclusions The rate of stroke is similar in patients with HF-REF and HF-PEF. Even in this relatively normotensive population, higher systolic BP was associated with greater stroke risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| 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 | 0.000 |
| 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".