Impact of fever on outcome in patients with stroke and neurological injury. Stroke 39
Bibliographic record
Abstract
Background and Purpose—Many studies associate fever with poor outcome in patients with neurological injury, but this relationship is blurred by divergence in populations and outcome measures. We sought to incorporate all recent scholarship addressing fever in brain-injured patients into a comprehensive meta-analysis to evaluate disparate clinical findings. Methods—We conducted a Medline search for articles since January 1, 1995 (in English with abstracts, in humans) and hand searches of references in bibliographies and review articles. Search terms covered stroke, neurological injury, thermoregulation, fever, and cooling. A total of 1139 citations were identified; we retained 39 studies with 67 tested hypotheses contrasting outcomes of fever/higher body temperature and normothermia/lower body temperature in patients with neurological injury covering 14 431 subjects. A separate meta-analysis was performed for each of 7 outcome measures. Significance was evaluated with Zc developed from probability values or t values. Correlational effect size, r(es), was calculated for each study and used to derive Cohen’s d unbiased combined effect size and relative risk. Results—Fever or higher body temperature was significantly associated with worse outcome in every measure studied. Relative risk of worse outcome with fever was: mortality, 1.5; Glasgow Outcome Scale, 1.3; Barthel Index, 1.9; modified Rankin Scale, 2.2; Canadian Stroke Scale, 1.4; intensive care length of stay, 2.8; and hospital length of
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".