ICES (Intraoperative Stereotactic Computed Tomography-Guided Endoscopic Surgery) for Brain Hemorrhage
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Intracerebral hemorrhage (ICH) is a devastating disease without a proven therapy to improve long-term outcome. Considerable controversy about the role of surgery remains. Minimally invasive endoscopic surgery for ICH offers the potential of improved neurological outcome. METHODS: We tested the hypothesis that intraoperative computerized tomographic image-guided endoscopic surgery is safe and effectively removes the majority of the hematoma rapidly. A prospective randomized controlled study was performed on 20 subjects (14 surgical and 4 medical) with primary ICH of >20 mL volume within 48 hours of ICH onset. We prospectively used a contemporaneous medical control cohort (n=36) from the MISTIE trial (Minimally Invasive Surgery and r-tPA for ICH Evacuation). We evaluated surgical safety and neurological outcomes at 6 months and 1 year. RESULTS: The intraoperative computerized tomographic image-guided endoscopic surgery procedure resulted in immediate reduction of hemorrhagic volume by 68±21.6% (interquartile range 59-84.5) within 29 hours of hemorrhage onset. Surgery was successfully completed in all cases, with a mean operative time of 1.9 hours (interquartile range 1.5-2.2 hours). One surgically related bleed occurred peri-operatively, but no patient met surgical safety stopping threshold end points for intraoperative hemorrhage, infection, or death. The surgical intervention group had a greater percentage of patients with good neurological outcome (modified Rankin scale score 0-3) at 180 and 365 days as compared with medical control subjects (42.9% versus 23.7%; P=0.19). CONCLUSIONS: Early computerized tomographic image-guided endoscopic surgery is a safe and effective method to remove acute intracerebral hematomas, with a potential to enhance neurological recovery. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00224770.
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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".