Non-technical skills of surgeons and anaesthetists in simulated operating theatre crises
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Bibliographic record
Abstract
BACKGROUND: Deficiencies in non-technical skills (NTS) have been increasingly implicated in avoidable operating theatre errors. Accordingly, this study sought to characterize the impact of surgeon and anaesthetist non-technical skills on time to crisis resolution in a simulated operating theatre. METHODS: Non-technical skills were assessed during 26 simulated crises (haemorrhage and airway emergency) performed by surgical teams. Teams consisted of surgeons, anaesthetists and nurses. Behaviour was assessed by four trained raters using the Non-Technical Skills for Surgeons (NOTSS) and Anaesthetists' Non-Technical Skills (ANTS) rating scales before and during the crisis phase of each scenario. The primary endpoint was time to crisis resolution; secondary endpoints included NTS scores before and during the crisis. A cross-classified linear mixed-effects model was used for the final analysis. RESULTS: Thirteen different surgical teams were assessed. Higher NTS ratings resulted in significantly faster crisis resolution. For anaesthetists, every 1-point increase in ANTS score was associated with a decrease of 53·50 (95 per cent c.i. 31·13 to 75·87) s in time to crisis resolution (P < 0·001). Similarly, for surgeons, every 1-point increase in NOTSS score was associated with a decrease of 64·81 (26·01 to 103·60) s in time to crisis resolution in the haemorrhage scenario (P = 0·001); however, this did not apply to the difficult airway scenario. Non-technical skills scores were lower during the crisis phase of the scenarios than those measured before the crisis for both surgeons and anaesthetists. CONCLUSION: A higher level of NTS of surgeons and anaesthetists led to quicker crisis resolution in a simulated operating theatre environment.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it