Comparison of Videothoracoscopy and Axillary Thoracotomy for the Treatment of Spontaneous Pneumothorax
Bibliographic record
Abstract
Surgical treatment of spontaneous pneumothorax can be done through a thoracotomy or a video-thoracoscopic approach. Although the videothoracoscopic technique is currently popular it is not obviously superior to a more traditional axillary thoracotomy approach. We compared our recent experience with both techniques to determine the optimal surgical treatment for spontaneous pneumothoraces. A retrospective review of 79 patients treated surgically (34 thoracotomy and 45 thoracoscopy) for spontaneous pneumothoraces was done. Patients were treated between 1991 and 1997. Patients older than 60 years of age and those with spontaneous pneumothoraces secondary to generalized pulmonary emphysema were excluded. There were no operative deaths. Recurrence rate [thoracotomy, two of 34; thoracoscopy, three of 45 (P < 0.89)], air leak exceeding 7 days [thoracotomy, three of 34; thoracoscopy, three of 45 (P < 0.73)], operating room times [thoracotomy, 54 +/- 26 minutes; thoracoscopy, 53 +/- 16 minutes (P < 0.59)], and postoperative length of stay [thoracotomy, 5.7 +/- 4.3 days; thoracoscopy, 4.7 +/- 4.4 days (P < 0.26)] were not significantly different for the two techniques. We conclude that axillary thoracotomy and videothoracoscopy are equally effective surgical treatments for spontaneous pneumothoraces. A large randomized trial would be needed to determine whether one approach is truly superior to the other.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".