Therapeutic hypothermia for intracerebral hemorrhage: Systematic review and meta-analysis of the experimental and clinical literature
Bibliographic record
Abstract
BACKGROUND: Intracerebral hemorrhage remains the deadliest form of stroke worldwide, inducing neuronal death through a wide variety of pathways. Therapeutic hypothermia is a robust and well-studied neuroprotectant widely used across a variety of specialties. AIMS: This review summarizes results from preclinical and clinical studies to highlight the overall effectiveness of therapeutic hypothermia to improve long-term intracerebral hemorrhage outcomes while also elucidating optimal protocol regimens to maximize therapeutic effect. SUMMARY OF REVIEW: A systematic review was conducted across three databases to identify trials investigating the use of therapeutic hypothermia to treat intracerebral hemorrhage. A random-effects meta-analysis was conducted on preclinical studies, looking at neurobehavioral outcomes, blood brain barrier breakdown, cerebral edema, hematoma volume, and tissue loss. Several mixed-methods meta-regression models were also performed to adjust for variance and variations in hypothermia induction procedures. Twwenty-one preclinical studies and five human studies were identified. The meta-analysis of preclinical studies demonstrated a significant benefit in behavioral scores (ES = -0.43, p = 0.02), cerebral edema (ES = 1.32, p = 0.0001), and blood brain barrier (ES = 2.73, p ≤ 0.00001). Therapeutic hypothermia was not found to significantly affect hematoma expansion (ES = -0.24, p = 0.12) or tissue loss (ES = 0.06, p = 0.68). Clinical study outcome reporting was heterogeneous; however, there was recurring evidence of therapeutic hypothermia-induced edema reduction. CONCLUSIONS: The combined preclinical evidence demonstrates that therapeutic hypothermia reduced multiple cell death mechanisms initiated by intracerebral hemorrhage; yet, there is no definitive evidence in clinical studies. The cooling strategies employed in both preclinical and clinical studies were highly diverse, and focused refinement of cooling protocols should be developed in future preclinical studies. The current data for therapeutic hypothermia in intracerebral hemorrhage remains questionable despite the highly promising indications in preclinical studies. Definitive randomized controlled studies are still required to answer this therapeutic question.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.031 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".