A Prospective Observational Study of Physical Activity Levels and Physical Fitness of People at High Risk for Lung Cancer
Bibliographic record
Abstract
Introduction: Physical activity (PA) is a potentially modifiable risk factor for lung cancer, with previous research revealing that people who engage in more PA have lower risk of developing lung cancer. PA levels of lung cancer screening participants have not previously been explored. Methods: Participants at a single Australian International Lung Screen Trial site were eligible for assessment of self-reported PA levels (International Physical Activity Questionnaire and Physical Activity Scale for the Elderly) and physical assessments (6-min walk distance, hand grip muscle strength, daily step count, and body composition) at a single time point during lung cancer screening. Statistics were predominantly descriptive, with parametric data presented as mean and SD and nonparametric data presented as median and interquartile range (IQR). Results: A total of 178 participants were enrolled in this study, with a median age of 61 years. Of the participants, 61% were men and 51% were people who currently smoke. The median total International Physical Activity Questionnaire score was 1756 MET/min/wk (IQR 689, 4049). Mean total Physical Activity Scale for the Elderly score was 160 (SD 72), higher than described in healthy sedentary adults. The median daily step count was 7237 steps (IQR 5353, 10,038) and mean 6-minute walk distance was 545 m (SD 92). Median grip strengths were within predicted normal range, with an elevated median percentage body fat and low skeletal muscle mass found on body composition. Conclusion: Almost a quarter of International Lung Screen Trial participants assessed reported low levels of PA and have a potentially modifiable risk factor to improve health outcomes. Larger studies are needed to characterize the burden of inactivity among high-risk lung cancer screening populations.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".