Swiss trial of decompressive craniectomy versus best medical treatment of spontaneous supratentorial intracerebral haemorrhage (SWITCH): an international, multicentre, randomised-controlled, two-arm, assessor-blinded trial
Bibliographic record
Abstract
RATIONALE: Decompressive craniectomy (DC) is beneficial in people with malignant middle cerebral artery infarction. Whether DC improves outcome in spontaneous intracerebral haemorrhage (ICH) is unknown. AIM: To determine whether DC without haematoma evacuation plus best medical treatment (BMT) in people with ICH decreases the risk of death or dependence at 6 months compared to BMT alone. METHODS AND DESIGN: SWITCH is an international, multicentre, randomised (1:1), two-arm, open-label, assessor-blinded trial. Key inclusion criteria are age ⩽75 years, stroke due to basal ganglia or thalamic ICH that may extend into cerebral lobes, ventricles or subarachnoid space, Glasgow coma scale of 8-13, NIHSS score of 10-30 and ICH volume of 30-100 mL. Randomisation must be performed <66 h after onset and DC <6 h after randomisation. Both groups will receive BMT. Participants randomised to the treatment group will receive DC of at least 12 cm in diameter according to institutional standards. SAMPLE SIZE: A sample of 300 participants randomised 1:1 to DC plus BMT versus BMT alone provides over 85% power at a two-sided alpha-level of 0.05 to detect a relative risk reduction of 33% using a chi-squared test. OUTCOMES: The primary outcome is the composite of death or dependence, defined as modified Rankin scale score 5-6 at 6 months. Secondary outcomes include death, functional status, quality of life and complications at 180 days and 12 months. DISCUSSION: SWITCH will inform physicians about the outcomes of DC plus BMT in people with spontaneous deep ICH, compared to BMT alone. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02258919.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.010 | 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".