A method of assessing reasons for conversion during video-assisted thoracoscopic lobectomy
Why this work is in the frame
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Bibliographic record
Abstract
Conversion rates during video-assisted thoracoscopic lobectomy are reported, but no previous publications have classified the cause of conversion. The aim of the study was to develop a quality assessment tool [vascular, anatomy, lymph node, technical (VALT) 'Open'] to evaluate reasons and nature of conversion during the development of a video-assisted thoracoscopic lobectomy program. Between 2006 and 2008, 237 patients with a median age of 65 years underwent video-assisted thoracoscopic lobectomy primarily for lung. The number of video-assisted thoracoscopic lobectomy cases over open cases has increased over the period. Conversion rate has dropped from 15% (2006) to 11% (2008). A total of 32 cases required conversion. The VALT 'Open' classification for reason to convert and nature of conversion was used. The average length of stay was shorter for non-converted cases. No uncontrolled conversions where the patient was unstable were required, and in the 14 cases converted following some difficulty, such as pulmonary artery injury. A pattern to the learning curve became predictable. The quality assessment tool used (VALT 'Open') will allow cause of conversion and nature of conversion to be tracked and audited during the development of a video-assisted thoracoscopic surgery lobectomy program.
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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) | 0.001 | 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 | 0.000 |
| 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