Adverse Events Within 24 hours After 1070 Adult Brain Tumor Surgeries Recovered in a Neurocritical Care Unit or a Postanesthesia Care Unit.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: By convention, patients who have undergone a craniotomy for tumor are monitored in a neurocritical care unit (NCCU) overnight, yet there is little evidence to justify the need for such intense care. Here, we compared postoperative adverse events in patients after brain tumor surgeries surveilled in a NCCU overnight or postanesthesia care unit (PACU) for a shorter duration. METHODS: We retrospectively studied 1070 consecutive patients who underwent craniotomy for brain tumor between 2016 and 2021. Inclusion criteria were age ≥18 years and craniotomy for resection or biopsy of intracerebral or extracerebral tumors. Cohorts were divided into 2 groups based on recovery destination, NCCU or PACU. Medical history, preoperative and postoperative neuroimaging, surgical resection features, diagnosis, and postoperative adverse events within 24 hours were reviewed for all patients. RESULTS: < .001). CONCLUSION: The incidence of adverse events within 24 hours after brain tumor surgery was not different between patients being surveilled for a long period in a NCCU or for a short period in a PACU.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".