The Safety and Feasibility of Image-Guided BrainPath-Mediated Transsulcul Hematoma Evacuation: A Multicenter Study
Bibliographic record
Abstract
BACKGROUND: Subcortical injury resulting from conventional surgical management of intracranial hemorrhage may counteract the potential benefits of hematoma evacuation. OBJECTIVE: To evaluate the safety and potential benefits of a novel, minimally invasive approach for clot evacuation in a multicenter study. METHODS: The integrated approach incorporates 5 competencies: (1) image interpretation and trajectory planning, (2) dynamic navigation, (3) atraumatic access system (BrainPath, NICO Corp, Indianapolis, Indiana), (4) extracorporeal optics, and (5) automated atraumatic resection. Twelve neurosurgeons from 11 centers were trained to use this approach through a continuing medical education-accredited course. Demographical, clinical, and radiological data of patients treated over 2 years were analyzed retrospectively. RESULTS: Thirty-nine consecutive patients were identified. The median Glasgow Coma Scale (GCS) score at presentation was 10 (range, 5-15). The thalamus/basal ganglion regions were involved in 46% of the cases. The median hematoma volume and depth were 36 mL (interquartile range [IQR], 27-65 mL) and 1.4 cm (IQR, 0.3-2.9 cm), respectively. The median time from ictus to surgery was 24.5 hours (IQR, 16-66 hours). The degree of hematoma evacuation was ≥90%, 75% to 89%, and 50% to 74% in 72%, 23%, and 5.0% of the patients, respectively. The median GCS score at discharge was 14 (range, 8-15). The improvement in GCS score was statistically significant ( P < .001). Modified Rankin Scale data were available for 35 patients. Fifty-two percent of those patients had a modified Rankin Scale score of ≤2. There were no mortalities. CONCLUSION: The approach was safely performed in all patients with a relatively high rate of clot evacuation and functional independence.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".