Same day discharge for craniotomy
Bibliographic record
Abstract
PURPOSE OF REVIEW: Same-day protocols for craniotomy have been demonstrated to be feasible and safe. Its several benefits include decreased hospital costs, less nosocomial complications, fewer case cancellations, with a high degree of patient satisfaction. This paper reviews the most recent publications in the field of same-day discharge after craniotomy. RECENT FINDINGS: Since 2019, several studies on same-day neurosurgical procedures were published. Ambulatory craniotomy protocols for brain tumor were successfully implemented in more centers around the world, and for the first time, in a developing country. Additional information emerged on predictors for successful early discharge, and the barriers and enablers of same-day craniotomy programs. Moreover, the cost benefits of same-day craniotomy were reaffirmed. SUMMARY: Same- day discharge after craniotomy is feasible, safe and continues to expand to a wider variety of procedures, in new institutions and countries. There are several benefits to ambulatory surgery. Well-established protocols for perioperative management are essential to the success of early discharge programs. With continued research, these protocols can be refined and implemented in more institutions globally, ultimately to provide better, more efficient care for neurosurgical patients.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".