Risk factors, inpatient care, and outcomes of pneumonia after ischemic stroke
Bibliographic record
Abstract
OBJECTIVES: Pneumonia is the most common medical complication after stroke. Although several risk factors have been reported, the role of common comorbidities in the development of pneumonia is not well established. Moreover, there is discrepancy in the literature regarding the impact of pneumonia on stroke outcomes. METHODS: This is a multicenter retrospective cohort study including consecutive patients with ischemic stroke admitted to Regional Stroke Centers participating in the Registry of Canadian Stroke Network in July 2003-March 2007. Pneumonia was defined as a complication that occurred within the first 30 days of the stroke and was confirmed radiographically. The main outcome measure was adjusted 30-day mortality. Secondary outcomes were adjusted 7- and 365-day mortality, institutionalization, length of stay, and modified Rankin score on discharge. We also assessed the impact of organized stroke care on pneumonia development and mortality. RESULTS: Overall, 8,251 patients were included in the study. Stroke-associated pneumonia was observed in 587 patients (7.1%). Pneumonia increased 30-day (odds ratio [OR] 2.2 [95% confidence interval (CI) 1.8-2.7]) and 1-year mortality (OR 3.0 [95% CI 2.5-3.7]), but not 7-day mortality. Pneumonia was associated with poor functional outcome. Higher access to organized inpatient care resulted in a reduction of 30-day mortality (OR 0.50 [95% CI 0.41-0.61]). Older age, male sex, stroke severity, dysphagia, chronic obstructive pulmonary disease, coronary artery disease, nonlacunar ischemic stroke, and preadmission dependency were independent predictors of pneumonia. CONCLUSIONS: Development of pneumonia after stroke was associated with mortality at 30 days and 1 year, longer length of stay, and dependency at discharge. Patients who received more inpatient stroke services had reduced mortality after pneumonia.
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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 | 0.006 |
| 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 | 0.001 |
| 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".