Outcome following decompressive craniectomy for malignant middle cerebral artery infarction in children
Bibliographic record
Abstract
AIM: Mortality from malignant middle cerebral artery infarction (MMCAI) approaches 80% in adult series. Although decompressive craniectomy decreases mortality and leads to an acceptable outcome in selected adult patients, there are few data on MMCAI in children with stroke. This study evaluated the frequency of MMCAI and the use of decompressive craniectomy in children. METHOD: We retrospectively reviewed cases of MMCAI from five pediatric tertiary care centers. RESULTS: Ten children (two females, eight males; median age 9y 10mo, range 22mo-14y) had MMCAI, with a median Glasgow Coma Scale score of 6 (range 3-9). MMCAI represented fewer than 2% of cases of pediatric arterial ischemic stroke. Three patients who did not undergo decompression, all of whom had monitoring of intracranial pressure, developed intractable intracranial hypertension, and fulfilled criteria for brain death. In contrast, seven patients underwent decompressive craniectomy and survived, with rapid improvement in their level of consciousness postoperatively. All seven survivors now walk independently with mild to moderate residual hemiparesis and speak fluently, even though four had left-sided infarcts. INTERPRETATION: Decompressive craniectomy can lead to a moderately good outcome for children with MMCAI and should be considered, even with symptomatic stroke and deep coma. Monitoring of intracranial pressure may delay life-saving treatment.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".