An Ambiguous Role for Fever in Worsening Outcome After Intracerebral Hemorrhage
Bibliographic record
Abstract
Intracerebral hemorrhage (ICH) accounts for 10-15% of all strokes and leaves most survivors with impairments. Fever, a rise in the thermoregulatory set point, complicates ICH. This review summarizes ICH fever studies and employs meta-analytic techniques to explore the relationship between fever and ICH. We discuss methodological considerations for future studies and provide an overview of mechanisms by which fever, and its treatment, may impact ICH. We searched the PubMed database using the following terms: ((fever OR hyperthermia) AND (intracerebral hemorrhage OR intraparenchymal hemorrhage OR intracerebral haemorrhage OR intraparenchymal haemorrhage)). Our search returned 727 studies, of which 21 were included in our final analysis, consisting of 19 clinical, and two preclinical, studies. We conducted a meta-analysis on the clinical data to quantify how fever is related to mortality, functional outcomes, and intraventricular hemorrhage. Analysis of clinical studies suggested that fever causes an increased risk of mortality but does not appear to be associated with poor outcomes among survivors, making it difficult to ascertain the extent of harm caused by post-ICH fever or the benefits of its treatment. Perhaps these inconsistencies stem from variable fever definitions, and temperature measurement and fever treatment protocols. Additionally, the lack of mechanistic data in clinical studies coupled with preclinical studies showing no harmful effects of moderate bouts of hyperthermia raise concerns about the direct contribution of hyperthermia and fever in post ICH outcome. Overall, the significance of temperature increases after ICH is unclear, making this an important area for future research.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".