Remote Ischemic Conditioning to Reduce Perihematoma Edema in Patients with Intracerebral Hemorrhage (RICOCHET): A Randomized Control Trial
Bibliographic record
Abstract
Background: Early perihematomal edema (PHE) growth is associated with worse functional outcomes at 90 days. Remote Ischemic conditioning (RIC) may reduce perihematomal inflammation if applied early to patients with intracerebral hemorrhage (ICH). We hypothesize that early RIC, delivered for seven days in patients with spontaneous ICH, may reduce PHE growth. Methods: ICH patients presenting within 6 h of symptom onset and hematoma volume < 60 milliliters (mL) were randomized to an RIC + standard care or standard care (SC) group. The primary outcome measure was calculated edema extension distance (EED), with the cm assessed on day seven. Results: Sixty patients were randomized with a mean ± SD age of 57.5 ± 10.8 years, and twenty-two (36.7%) were female. The relative baseline median PHE were similar (RIC group 0.75 (0.5–0.9) mL vs. SC group 0.91 (0.5–1.2) mL, p = 0.30). The median EEDs at baseline were similar (RIC group 0.58 (0.3–0.8) cm vs. SC group 0.51 (0.3–0.8) cm, p = 0.76). There was no difference in the median day 7 EED (RIC group 1.1 (0.6–1.2) cm vs. SC group 1 (0.9–1.2) cm, p = 0.75). Conclusions: Early RIC therapy delivered daily for seven days was feasible. However, no decrease in EED was noted with the intervention.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".