Abstract T MP94: Congestive Heart (or Cardiac) Failure: Risk Factors, Clinical Features and Outcomes in Patients With an Acute Ischemic Stroke
Bibliographic record
Abstract
Introduction: Congestive heart failure (CHF) is a relatively common comorbid condition in stroke patients. Limited information is known regarding CHF in patients with an acute ischemic stroke (AIS). Objective: We evaluated clinical characteristics, predisposing factors, and outcomes in stroke patients with history of CHF. Methods: We prospectively included AIS patients admitted to the institutions participating in the Registry of the Canadian Stroke Network (RCSN) between 2003 and 2008. History of chronic congestive heart failure (CHF) determined from medical records, physical examination and investigations. Primary outcome was death or disability at discharge (modified Rankin scale equal to or greater than 3). Secondary outcomes included admission ICU, disposition, length of hospital stay, death at 3 months and at 1 year and 30 day hospital readmissions. Logistic regression and survival analyses were performed to determine the association of risk factors with the outcomes of interest. Results: Among 12,686 patients with AIS, CHF was found in 1152 (9.1%) of patients. Mean age was 78.5±11 years. CHF patients were more likely to have hypertension, diabetes mellitus, hyperlipidemia, coronary artery disease, atrial fibrillation, vulvular heart disease and peripheral vascular disease. CHF more likely presented with a severe stroke (25.8% vs 14.1%, p<0.0001) and cardioembolic stroke subtype (42.2% vs 21.3%, p<0.0001). CHF was associated with higher risk of death at 30-days (24.2% vs 11.2%; p<0.0001) and at 1-year (44% vs 20.6;p<0.0001) and disability at discharge (70.3% vs 56%; p<0.0001). Mean length of stay was longer in stroke patients with CHF (15.51±23.91 vs 12.65±19.76 ; p=0.013). In the multivariate analysis, CHF (OR 1.18; 95%CI 1.01- 1.37) was an independent predictor of death and disability after adjusting age, stroke severity, and other comorbid conditions. Conclusions: In this large cohort study, CHF occurred in 9.1% of AIS patients. Stroke patients with CHF had poorer outcomes and longer hospitalization. Furthermore, after adjusting age, stroke severity and comorbidity, CHF was an independent predictor of death and disability.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".