ICES (Intraoperative Stereotactic Computed Tomography-Guided Endoscopic Surgery) for Brain Hemorrhage
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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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it