P.130 Efficacy of decompressive craniectomy after subarachnoid hemorrhage: a propensity-matched analysis of a South Australian Cerebrovascular Registry
Bibliographic record
Abstract
Background: The efficacy of decompressive craniectomy (DC) for patients with intracranial hypertension secondary to aneurysmal subarachnoid haemorrhage (aSAH) remains unclear. Methods: We identified aSAH patients who underwent DC following microsurgical aneurysm repair from a prospectively maintained cerebrovascular registry and compared their outcomes with a propensity-matched cohort who did not. Results: A total of 45 aSAH patients underwent DC between 01/09/2011 and 20/07/2020 and were compared with 45 propensity-matched controls. There were no differences in patient age (p=0.48), gender (p=0.53) or the proportion requiring endovascular vasospasm treatment (p=1.00). However, patients in the DC subgroup had a higher mean WFNS grade (3.47±1.53) compared with matched controls (2.8±1.25, p=0.03). Patients treated with DC had a higher rate of inpatient mortality (20.00% vs 0.00%, p=0.0025), unfavourable outcome (mRS≥4) at 1st (42.22% vs 11.11%, p=0.0016) and final (31.11% vs 2.94%, p<0.001) follow-up, and NIS-Subarachnoid Hemorrhage Outcome Measure positivity (40.00% vs 13.33%, p=0.0079). They also had a higher median mRS at 1st [3(2–4) vs 1(1–2), p<0.001], and final [2(1–4 vs 1(1 (0–2), p<0.001] follow-up. Conclusions: Patients treated with DC fared worse at every endpoint, which was disproportionate to the difference in presenting WFNS grade. These data do not support the use of DC following microsurgical clipping of a ruptured aneurysm.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".