Non-invasive convective head cooling during stroke thrombectomy: A prospective multi-center feasibility trial
Bibliographic record
Abstract
INTRODUCTION: Non-invasive convective head cooling is a promising putative neuroprotective therapy for ischemic stroke patients as it may portably, non-invasively, and selectively cool the ischemic penumbra. We aimed to investigate the feasibility of utilizing non-invasive convective head cooling in ischemic stroke patients before and during endovascular thrombectomy (EVT). PATIENTS AND METHODS: We conducted a multi-center, prospective, non-randomized, open-label trial at two comprehensive stroke centers in ischemic stroke patients where EVT was planned. Patients were assessed for eligibility in the emergency department (ED) and had a cooling cap fitted that circulated coolant between -5°C and 0°C until EVT completion. The primary feasibility endpoint was adherence, defined as tolerating cooling for ⩾50% of the time from cooling cap application until EVT completion. RESULTS: Between July and November 2024, 40 EVT patients (19 (47.5%) female, mean ± SD age 71.6 ± 12.6 years) underwent a median (IQR) duration of convective head cooling of 86 (58-106) min. Thirty-nine (97.5%) participants met the primary feasibility endpoint. The enrollment rate was five participants per site per month. Median (IQR) time from comprehensive stroke center arrival to cooling start was 10 (5-51) min. Thirty-two (80%) patients received general anesthesia. eTICI 2b-3 reperfusion was achieved in 38 (95.0%) participants. Median (IQR) 24-h infarct volume was 14.3 (5.5-29.1) mL. Median (IQR) 3-month modified Rankin Scale score was 2 (1-5). Three-month mortality occurred in 8/38 (21.1%) participants. Nine serious adverse events occurred in 8 (20.0%) participants, none of which were attributed to head cooling. CONCLUSIONS: Convective head cooling is feasible in patients undergoing EVT and warrants further investigation in larger randomized controlled trials.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".