Lung Metastatectomy: Can Laser-Assisted Surgery Make a Difference?
Bibliographic record
Abstract
BACKGROUND: Resection of lung metastases with curative intention in selected patients is associated with prolonged survival. Laser-assisted resection of lung metastases results in complete resection of a high number of lung metastases, while preserving lung parenchyma. However, data concerning laser lung resections are scarce and contradictory. The aim of this study was to conduct a systematic review to evaluate the utility of laser-assisted pulmonary metastasectomy. METHODS: An electronic search in MEDLINE (via PubMed), complemented by manual searches in article references, was conducted to identify eligible studies. RESULTS: Fourteen studies with a total of 1196 patients were included in this metanalysis. Laser-assisted surgery (LAS) for lung metastases is a safe procedure with a postoperative morbidity up to 24.2% and almost zero mortality. LAS resulted in the resection of a high number of lung metastases with reduction of the lung parenchyma loss in comparison with conventional resection methods. Survival was similar between LAS and conventional resections. CONCLUSION: LAS allows radical lung-parenchyma saving resection of a high number of lung metastases with similar survival to conventional methods.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".