Outpatient Brain Tumor Surgery and Spinal Decompression: A Prospective Study of 1003 Patients
Bibliographic record
Abstract
BACKGROUND: Outpatient craniotomy, biopsy, and spinal decompression have been performed at our center for more than a decade. Early feasibility studies suggest that they are safe, successful, cost-effective, and well-tolerated by patients. However, a large-scale study of this magnitude has not been performed. OBJECTIVE: To characterize postoperative complications and the rate of successful discharge from the day surgery unit (DSU). We also discuss patient satisfaction and benefits to flow of care. METHODS: From August 1996 to December 2009, 1003 consecutive patients were prospectively selected as outpatient candidates. Retrospective chart review was performed for all procedures and analyzed by intent to treat. RESULTS: Of 249 patients who underwent a craniotomy, 92.8% were successfully discharged from the DSU, 5.2% were admitted from the DSU, and 2.0% were discharged and later readmitted. Of 602 patients who underwent spinal decompression, 97.3% were successfully discharged from the DSU, 2.5% were admitted from the DSU, and 0.2% were discharged and readmitted at a later date. Of 152 patients who underwent a brain biopsy, 94.1% were successfully discharged from the DSU, 4.6% were admitted from the DSU, and 1.3% were discharged and later readmitted. No patients experienced a negative outcome as a result of early discharge. CONCLUSION: Outpatient craniotomy, biopsy, and spinal decompression are safe, successful, and cost-effective.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".