Pre-Exercise Participation Cardiovascular Screening in a Heterogeneous Cohort of Adult Cancer Patients
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to investigate the extent of pre-exercise participation ("preparticipation") health screening in a heterogeneous cohort of adult cancer patients. METHODS: Patients (n = 413) with histologically confirmed solid or hematologic malignancy were categorized into preparticipation health screening risk stratification based on American College Sports Medicine (ACSM) recommendations. Risk of an exercise-related event was evaluated during a symptom-limited cardiopulmonary exercise test (CPET) with 12-lead electrocardiography (ECG). RESULTS: Participant risk was categorized as low risk (n = 59, 14%), moderate risk (n = 217, 53%), and high risk (n = 137, 33%). Mean peak oxygen consumption was 21.7 ± 6.7 mL/kg(-1) per minute(-1) or 19.5 ± 21.7% below age- and sex-predicted sedentary values. No major serious adverse events or fatal events were observed during CPET procedures. A total of 31 positive ECG tests were observed, for an event rate of 8%. ACSM risk stratification did not predict the risk of a positive test. Age, statin use, antiplatelet therapy use, cardiovascular disease, prior treatment with anthracycline or radiation therapy, and being sedentary were predictors of a positive test (all p < .10). CONCLUSION: The patient risk-stratification profile strongly suggests that the use of formalized preparticipation health screening is required in all oncology scenarios; however, risk of an exercise-induced event is low, suggesting that the use of exercise testing is not required for pre-exercise clearance in the majority of 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".