Therapeutic hypothermia for acute ischaemic stroke. Results of a European multicentre, randomised, phase III clinical trial
Bibliographic record
Abstract
Abstract Introduction We assessed whether modest systemic cooling started within 6 hours of symptom onset improves functional outcome at three months in awake patients with acute ischaemic stroke. Patients and methods In this European randomised open-label clinical trial with blinded outcome assessment, adult patients with acute ischaemic stroke were randomised to cooling to a target body temperature of 34.0–35.0°C, started within 6 h after stroke onset and maintained for 12 or 24 h , versus standard treatment. The primary outcome was the score on the modified Rankin Scale at 91 days, as analysed with ordinal logistic regression. Results The trial was stopped after inclusion of 98 of the originally intended 1500 patients because of slow recruitment and cessation of funding. Forty-nine patients were randomised to hypothermia versus 49 to standard treatment. Four patients were lost to follow-up. Of patients randomised to hypothermia, 15 (31%) achieved the predefined cooling targets. The primary outcome did not differ between the groups (odds ratio for good outcome, 1.01; 95% confidence interval, 0.48–2.13; p = 0.97). The number of patients with one or more serious adverse events did not differ between groups (relative risk, 1.22; 95% confidence interval, 0.65–1.94; p = 0.52). Discussion In this trial, cooling to a target of 34.0–35.0°C and maintaining this for 12 or 24 h was not feasible in the majority of patients. The final sample was underpowered to detect clinically relevant differences in outcomes. Conclusion Before new trials are launched, the feasibility of cooling needs to be improved.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".