Preventive Antibiotics for Infections in Acute Stroke
Bibliographic record
Abstract
OBJECTIVE: To provide a systematic overview and meta-analysis of randomized clinical trials evaluating preventive antibiotics in patients with acute stroke. DATA SOURCES: The MEDLINE (1966-February 2009) and Cochrane databases and reference lists of retrieved articles. STUDY SELECTION: Randomized controlled trials on preventive antibiotic treatment in stroke. For inclusion, at least case fatality or infection rate had to be recorded. DATA EXTRACTION: Each study was scored for methodological key issues and appraised by the Jadad scale. We extracted the data using a predetermined protocol and included all patients who were randomized or who started therapy in an intent-to-treat analysis. DATA SYNTHESIS: We identified 4 randomized clinical trials including 426 patients; 94% had ischemic stroke. Study interventions were fluoroquinolones in 2 and tetracycline or a combination of beta-lactam antibiotic with beta-lactamase inhibitor in 1. Therapy was started within 24 hours of stroke onset. Duration of therapy varied between 3 and 5 days. The methodological quality ranged from 2 to 5 on the Jadad scale, and studies were subject to potential bias. The proportion of patients with infection was significantly smaller in the antibiotic group than in the placebo/control group (32 of 136 [23.5%] vs 53 of 139 [38.1%] patients). The pooled odds ratio for infection was 0.44 (95% confidence interval, 0.23-0.86). Ten of 210 patients (4.8%) in the antibiotic group died, compared with 13 of 216 (6.0%) in the placebo/control group. The pooled odds ratio for mortality was 0.63 (95% confidence interval, 0.22-1.78). No major harm or toxicity was reported. CONCLUSIONS: In adults with acute stroke, preventive antibiotics reduced the risk of infection, but did not reduce mortality. The observed effect warrants evaluation of preventive antibiotics in large stroke trials.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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".