Lung Resections for Elderly Patients with Lung Metastases: A Comparative Study of the Postoperative Complications and Overall Survival
Bibliographic record
Abstract
Background: Pulmonary metastasectomy (PM) is an established treatment option for selected patients with stage IV solid tumors. The aim of this study was to investigate the feasibility of and survival rate in PM for elderly patients. Methods: We retrospectively analyzed all of the patients who underwent PM with curative intention at our institution. The patients were categorized into two groups: the elderly group (≥70 years old) and the non-elderly group (<70 years old). Results: The elderly group consisted of 222 patients versus 538 patients in the non-elderly group. The median number of resected metastases was 2 ± 3 in the elderly group and 4 ± 5 in the non-elderly group (p < 0.01). No difference in the rate of postoperative complications was observed between the two groups (p = 0.3). The median length of hospital stay in each group was comparable (10 ± 5 vs. 10 ± 4.3 days, p = 0.3). The 5-year survival rate was 67% in the elderly group and 78% in the non-elderly group (p = 0.117). In the univariate analysis, COPD was associated with poor survival in the elderly group (p = 0.002). Conclusion: The resection of pulmonary metastases in elderly patients is safe, is not associated with increased risks of postoperative complication, and the survival benefit is not reduced in selected patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".