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Effects of presurgical exercise training on exercise capacity in operable lung cancer: A pilot study

2006· article· en· W2231859057 on OpenAlexaff
Carolyn J. Peddle‐McIntyre, Neil D. Eves, Kerry S. Courneya, Mark J. Haykowsky, John R. Mackey, Anil A. Joy, Tony Reiman, Timothy W. Winton, Lee W. Jones

Bibliographic record

VenueJournal of Clinical Oncology · 2006
Typearticle
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsMedicineLung cancerVO2 maxPhysical therapySurgeryInternal medicineHeart rateBlood pressure

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.094
GPT teacher head0.444
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

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