The impact of segmentectomy versus lobectomy on pulmonary function in patients with non-small-cell lung cancer: a meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Segmentectomy has been reported as an alternative to lobectomy for small-sized NSCLC without detriment to survival. The long-term benefits of segmentectomy over lobectomy on pulmonary function have not been firmly established. This meta-analysis aims to compare postoperative changes in pulmonary function in NSCLC patients undergoing segmentectomy or lobectomy. METHODS: Medline, Embase, Web of Science and Scopus were searched through March 2021. Statistical comparisons were made when appropriate. RESULTS: Fourteen studies (2412 participants) out of 324 citations were included in this study. All selected studies were high quality, as indicated by the Newcastle-Ottawa scale for assessing the risk of bias. Clinical outcomes were compared between segmentectomy and lobectomy. ΔFEV1 [10 studies, P < 0.01, WMD = 0.40 (0.29, 0.51)], ΔFVC [4 studies, P < 0.01, WMD = 0.16 (0.07, 0.24)], ΔFVC% [4 studies, P < 0.01, WMD = 4.05 (2.32, 5.79)], ΔFEV1/FVC [2 studies, P < 0.01, WMD = 1.99 (0.90, 3.08)], and ΔDLCO [3 studies, P < 0.01, WMD = 1.30 (0.69, 1.90)] were significantly lower in the segmentectomy group than in the lobectomy group. Subgroup analysis showed that in stage IA patients, the ΔFEV1% [3 studies, P < 0.01, WMD = 0.26 (0.07, 0.46)] was significantly lower in the segmentectomy group. The ΔDLCO% and ΔMVV% were incomparable. CONCLUSION: Segmentectomy preserves more lung function than lobectomy. There were significantly smaller decreases in FEV1, FVC, FVC%, FEV1/FVC and DLCO in the segmentectomy group than in the lobectomy group.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.012 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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