Longer Periods of Hypothermia Provide Greater Protection Against Focal Ischemia: A Systematic Review of Animal Studies Manipulating Treatment Duration
Bibliographic record
Abstract
Decades of animal research show therapeutic hypothermia (TH) to be potently neuroprotective after cerebral ischemic injuries. While there have been some translational successes, clinical efficacy after ischemic stroke is unclear. One potential reason for translational failures could be insufficient optimization of dosing parameters. In this study, we conducted a systematic review of the PubMed database to identify all preclinical controlled studies that compared multiple TH durations following focal ischemia, with treatment beginning at least 1 hour after ischemic onset. Six studies met our inclusion criteria. In these six studies, six of seven experiments demonstrated an increase in cerebroprotection at the longest duration tested. The average effect size (mean Cohen's d ± 95% confidence interval) at the shortest and longest durations was 0.4 ± 0.3 and 1.9 ± 1.1, respectively. At the longest durations, this corresponded to percent infarct volume reductions between 31.2% and 83.9%. Our analysis counters previous meta-analytic findings that there is no relationship, or an inverse relationship between TH duration and effect size. However, underreporting often led to high or unclear risks of bias for each study as gauged by the SYRCLE Risk of Bias tool. We also found a lack of investigations of the interactions between duration and other treatment considerations (e.g., method, delay, and ischemic severity). With consideration of methodological limitations, an understanding of the relationships between treatment parameters is necessary to determine proper "dosage" of TH, and should be further studied, considering clinical failures that contrast with strong cerebroprotective results in most animal studies.
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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 | 0.014 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.013 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".