Uniportal video-assisted thoracic surgery lobectomy: a consensus report from the Uniportal VATS Interest Group (UVIG) of the European Society of Thoracic Surgeons (ESTS)
Bibliographic record
Abstract
OBJECTIVES: Our goal was to report the results of the first consensus paper among international experts in uniportal video-assisted thoracoscopic surgery (UniVATS) lobectomy obtained through a Delphi process, the objective of which was to define and standardize the main procedural steps, optimize its indications and perioperative management and identify elements to assist in future training. METHODS: The 40 members of the working group were convened and organized on a voluntary basis by the Uniportal VATS Interest Group (UVIG) of the European Society of Thoracic Surgeons (ESTS). An e-consensus finding exercise using the Delphi method was applied to require 75% agreement for reaching consensus on each question. Repeated iterations of anonymous voting continued for 3 rounds. RESULTS: Overall, 31 international experts from 18 countries completed all 3 rounds of questionnaires. Although a technical quorum was not achieved, most of the responders agreed that the maximum size of a UniVATS incision should be ≤4 cm. Agreement was reached on many points outlining the currently accepted definition of a UniVATS lobectomy, its indications and contraindications, perioperative clinical management and recommendations for training and future research directions. CONCLUSIONS: The UVIG Consensus Report stated that UniVATS offers a valid alternative to standard VATS techniques. Only longer follow-up and randomized controlled studies will predict whether UniVATS represents a valid alternative approach to multiport VATS for major lung resections or whether it should be performed only in selected cases and by selected centres. The next step for the ESTS UVIG is the establishment of a UniVATS section inside the ESTS databases.
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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 | 0.118 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".