Performance of Residents and Anesthesiologists in a Simulation-based Skill Assessment
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Anesthesiologists and anesthesia residents are expected to acquire and maintain skills to manage a wide range of acute intraoperative anesthetic events. The purpose of this study was to determine whether an inventory of simulated intraoperative scenarios provided a reliable and valid measure of anesthesia residents' and anesthesiologists' skill. METHODS: Twelve simulated acute intraoperative scenarios were designed to assess the performance of 64 residents and 35 anesthesiologists. The participants were divided into four groups based on their training and experience. There were 31 new CA-1, 12 advanced CA-1, and 22 CA-2/CA-3 residents as well as a group of 35 experienced anesthesiologists who participated in the assessment. Each participant managed a set of simulated events. The advanced CA-1 residents, CA-2/CA-3 residents, and 35 anesthesiologists managed 8 of 12 intraoperative simulation exercises. The 31 CA-1 residents each managed 3 intraoperative scenarios. RESULTS: The new CA-1 residents received lower scores on the simulated intraoperative events than the other groups of participants. The advanced CA-1 residents, CA-2/CA-3 residents, and anesthesiologists performed similarly on the overall assessment. There was a wide range of scores obtained by individuals in each group. A number of the exercises were difficult for the majority of participants to recognize and treat, but most events effectively discriminated among participants who achieved higher and lower overall scores. CONCLUSION: This simulation-based assessment provided a valid method to distinguish the skills of more experienced anesthesia residents and anesthesiologists from residents in early training. The overall score provided a reliable measure of a participant's ability to recognize and manage simulated acute intraoperative events. Additional studies are needed to determine whether these simulation-based assessments are valid measures of clinical performance.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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