Uniportal vs. multiportal thoracoscopic segmentectomy: a north American study
Bibliographic record
Abstract
Background: Uniportal video-assisted thoracoscopic surgery (VATS) segmentectomy is gaining worldwide acceptance, but experience in North America is still limited. We report a North American multicenter comparison of uniportal vs. multiportal VATS segmentectomy. Methods: We performed an institutional review board-exempt retrospective chart review on prospectively collected databases at two North American centers, from January 2012 to December 2020. We included all VATS segmentectomy patients and excluded emergent cases (n=1), patients with incomplete records (n=2), and segmentectomy performed in conjunction with another type of lung resection (n=1). We recorded patient demographics, perioperative data, 30-day postoperative complications and compared outcomes between cohorts. We provided descriptive statistics for each group. We calculated propensity score matching and paired patients 1:1. We defined P values less than 0.05 as statistically significant. Results: We performed a total of 423 VATS segmentectomies, 181 uniportal (42.7%) vs. 242 multiportal (57.2%). Indications for surgery were primary lung cancer (n=339), metastatic (n=41), benign disease (n=40), and other (n=3). We staged 85.1% of patients preoperatively with positron emission tomography-computed tomography (PET-CT) scan according to National Comprehensive Cancer Network (NCCN) guidelines. Propensity score matching generated 156 patients on each group. Operating time was significantly lower in the uniportal group compared to multiportal (130 vs. 161 min respectively, P<0.001). We found no difference in estimated blood loss, Clavien-Dindo class III-IV complications, conversion to thoracotomy, R0 resection rate, nodal upstaging, hospital length of stay, 30-day readmission or mortality. Conclusions: Our experience from two North American centers indicates that, in experienced hands, postoperative outcomes after uniportal and multiportal VATS segmentectomy are comparable.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".