What Is the Driving Performance of Ambulatory Surgical Patients after General Anesthesia?
Bibliographic record
Abstract
BACKGROUND: Ambulatory surgical patients are advised to refrain from driving for 24 h postoperatively. However, currently there is no strong evidence to show that driving skills and alertness have resumed in patients by 24 h after general anesthesia. The purpose of this study was to determine whether impaired driver alertness had been restored to normal by 2 and 24 h after general anesthesia in patients who underwent ambulatory surgery. METHODS: Twenty patients who underwent left knee arthroscopic surgery were studied. Their driving simulation performance, electroencephalographically verified parameters of sleepiness, subjective assessment of sleepiness, fatigue, alertness, and pain were measured preoperatively and 2 and 24 h postoperatively. The same measurements were performed in a matched control group of 20 healthy individuals. RESULTS: Preoperatively, patients had significantly higher attention lapses and lower alertness levels versus normal controls. Significantly impaired driving skills and alertness, including longer reaction time, higher occurrence of attention lapses, and microsleep intrusions, were found 2 h postoperatively versus preoperatively. No significantly differences were found in any driving performance parameters or electroencephalographically verified parameters 24 h postoperatively versus preoperatively. CONCLUSIONS: Patients showed lower alertness levels and impaired driving skills preoperatively and 2 h postoperatively. Based on driving simulation performance and subjective assessments, patients are safe to drive 24 h after general anesthesia.
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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 | 0.000 |
| 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 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".