Step, Error, and Event Frameworks in Endovascular Aortic Repair
Bibliographic record
Abstract
OBJECTIVE: Competency-based surgical education requires detailed and actionable feedback to ensure adequate and efficient skill development. Comprehensive operative capture systems such as the Operating Room Black Box (ORBB; Surgical Safety Technologies, Inc), which continuously records and synchronizes multiple sources of intraoperative data, have recently been integrated into hybrid rooms to provide targeted feedback to endovascular teams. The objective of this study is to develop step, error, and event frameworks to evaluate technical performance in elective endovascular aortic repair (EVAR) comprehensively captured by the ORBB (Surgical Safety Technologies, Inc; Toronto, Canada). METHODS: This study is based upon a modified Delphi consensus process to create evaluation frameworks for steps, errors, and events in EVAR. International experts from Vascular Surgery and Interventional Radiology were identified, based on their records of publications and invited presentations, or serving on relevant journal editorial boards. In an initial open-ended survey round, experts were asked to volunteer a comprehensive list of steps, errors, and events for a standard EVAR of an infrarenal aorto-iliac aneurysm (AAA). In subsequent survey rounds, the identified items were presented to the expert panel to rate on a 5-point Likert scale. Delphi survey rounds were repeated until the process reached consensus with a predefined agreement threshold (Cronbach α>0.7). The final frameworks were constructed with items achieving an agreement (responses of 4 or 5) from greater than 70% of experts. RESULTS: Of 98 invited proceduralists, 38 formed the expert consensus panel (39%), consisting of 29 vascular surgeons and 9 interventional radiologists, with 34% from North America and 66% from Europe. Consensus criteria were met following the third round of the Delphi consensus process (Cronbach α=0.82-0.93). There were 15, 32, and 25 items in the error, step, and event frameworks, respectively (within-item agreement=74%-100%). CONCLUSION: A detailed evaluation tool for the procedural steps, errors, and events in infrarenal EVAR was developed. This tool will be validated on recorded procedures in future work: It may focus skill development on common errors and hazardous steps. This tool might be used to provide high-quality feedback on technical performance of trainees and experienced surgeons alike, thus promoting surgical mastery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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) | 0.001 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".