Clinical characteristics, precipitating factors, management and outcome of patients with prior stroke hospitalised with heart failure: an observational report from the Middle East
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study is to report the prevalence, clinical characteristics, precipitating factors, management and outcome of patients with prior stroke hospitalised with acute heart failure (HF). DESIGN: Retrospective analysis of prospectively collected data. SETTING: Data were derived from Gulf CARE (Gulf aCute heArt failuRe rEgistry), a prospective multicentre study of consecutive patients hospitalised with acute HF in 2012 in seven Middle Eastern countries and analysed according to the presence or absence of prior stroke; demographics, management and outcomes were compared. PARTICIPANTS: A total of 5005 patients with HF. OUTCOME MEASURES: In-hospital and 1-year outcome. RESULTS: The prevalence of prior stroke in patients with HF was 8.1%. Patients with stroke with HF were more likely to be admitted under the care of internists rather than cardiologists. When compared with patients without stroke, patients with stroke were more likely to be older and to have diabetes mellitus, hypertension, atrial fibrillation, hyperlipidaemia, chronic kidney disease, ischaemic heart disease, peripheral arterial disease and left ventricular dysfunction (p=0.001 for all). Patients with stroke were less likely to be smokers (0.003). There were no significant differences in terms of precipitating risk factors for HF hospitalisation between the two groups. Patients with stroke with HF had a longer hospital stay (mean±SD days; 11±14 vs 9±13, p=0.03), higher risk of recurrent strokes and 1-year mortality rates (32.7% vs 23.2%, p=0.001). Multivariate logistic regression analysis showed that stroke is an independent predictor of in-hospital and 1-year mortality. CONCLUSIONS: This observational study reports high prevalence of prior stroke in patients hospitalised with HF. Internists rather than cardiologists were the predominant caregivers in this high-risk group. Patients with stroke had higher risk of in-hospital recurrent strokes and long-term mortality rates. TRIAL REGISTRATION NUMBER: NCT01467973.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".