Effects of early decompressive craniectomy on functional outcome of patients with malignant middle cerebral artery infarctions
Bibliographic record
Abstract
Background: This study aimed to compare the functional outcome of patients with malignant middle cerebral artery (MCA) infarction who had undergone either early decompressive craniectomy (DC) or optimal medical therapy (OMT). Methods: This study was conducted during a 2- year period in Golestan Hospital of Ahvaz, Iran. The selected patients with malignant MCA infarction who were admitted within 48 hours of presenting signs were included. The patients were randomly assigned to undergo either early DC (n = 12) or OMT (n = 12) in the neurosurgical intensive care unit (ICU). The functional outcomes in the subjects were evaluated with the Glasgow Outcome Scale (GOS) and the National Institutes of Health Stroke Scale (NIHSS) at discharge, 6, and 12-month intervals. Results: The patients who underwent DC had significantly higher GOS at discharge (P = 0.013), 6 (P = 0.022), and 12 (P = 0.042) months as compared to the medical therapy group. However, the NIHSS score did not show any significant difference between the two groups during the study. Likewise, DC was associated with lower mortality at 6 (P = 0.027) and 12 (P = 0.014) months; moreover, the lower mortality rate (P = 0.014), severe disability (P = 0.040), higher good recovery (P < 0.001), and moderate disability (P < 0.001) were observed after 12 months of follow-up. Conclusion: These findings suggest that early DC in patients with malignant MCA can decrease mortality and improve the functional outcome according to GOS criteria compared to medical therapy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".