Effects of presurgical exercise training on exercise capacity in operable lung cancer: A pilot study
Bibliographic record
Abstract
17047 Background: Exercise capacity is a strong independent predictor of surgical outcome in patients with operable NSCLC and thus an established clinical tool to assess preoperative eligibility. The purpose of this study was to determine the effects of preoperative exercise training on exercise capacity in operable lung cancer. Methods: Using a single-group design, participants with suspected operable lung cancer were screened for eligibility at the time of diagnosis. Twenty-six patients were recruited and offered exercise training until surgical resection. Exercise training consisted of 5 endurance cycle ergometry sessions per week at 60 to 100% of patient’s baseline exercise capacity. Patients underwent cardiopulmonary exercise testing (CPET) including peak oxygen consumption (VO2peak), six minute walk distance (6MWD), and a pulmonary function test at baseline, immediately prior and 30 days post surgical resection. Results: The mean time from diagnosis to resection was 67 ± 27 days. During this time, 6 patients were deemed ineligible and were removed from the analysis. Of the remaining 20 patients, 18 completed exercise training and 13 performed CPET post resection. The overall adherence rate was 72% (range 0%–100%) with patients completing a mean of 30 exercise sessions (range 0–75). Intention-to-treat analysis indicated that VO2peak and 6MWD increased by 2.3 mL · kg−1 · min−1 [95% CI, 1.0 to 3.7; p = .002] and 40m [95% CI, 16 to 64; p=.003] respectively, from baseline to presurgery but decreased from pre to post resection [VO2peak, −2.7 mL · kg−1 · min−1, 95% CI, −3.9 to −1.6; p < .001; 6 MWD, −44 m, 95% CI, −94 to 6.4; p = .082]. There were no differences between baseline and postsurgical exercise capacity. Per protocol analyses indicated that patients who achieved acceptable exercise adherence (≥80% of prescribed sessions, n = 12) increased VO2peak and 6MWD by 3.2 mL · kg−1 · min−1 [95% CI, 1.1 to 5.4; p = .005] and 49 meters [95% CI, 12 to 85; p = .013], respectively. Conclusion: Preoperative exercise training is associated with improvements in exercise capacity in patients with operable NSCLC, particularly if acceptable adherence is achieved. This benefit may have important implications for surgical outcome and postsurgical recovery in this population. No significant financial relationships to disclose.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".