Is Heart Rate A Reliable Test Termination Criterion With Individuals Undergoing Chemotherapy For Metastatic Cancer
Bibliographic record
Abstract
Aerobic exercise is increasingly studied in cancer patients undergoing chemotherapy. However, there can be feasibility and acceptability issues when using maximal cardiopulmonary testingto prescribe intensity. Therefore, submaximal testing is suggested, with predicted % heart rate max (HRmax) or %HR reserve (HRR) and perceived exertion (PE) as stopping criteria. However, the HRmax prediction and the presence of autonomic dysfunction in cancer patients may increase the heterogeneity regarding the intensity at which the submaximal test is stopped, leading to suboptimal exercise prescription. PURPOSE: To assess if using a target HR as a stopping criterion during a submaximal test efficiently translates into a proper intensity during subsequent exercise sessions in cancer patients undergoing chemotherapy. METHODS: Eleven individuals (57 ± 7 years) undergoing treatments for metastatic cancer performed a modified YMCA (mYMCA) test. Participants were divided into two groups: REACH (n = 5) who reached the target HR (±10 bpm) at the end of mYMCA and No-REACH (n = 6) who terminated the test without reaching it. HR, RPE (Borg CR10 scale), capillary lactate (La-) and power output were collected during the mYMCA and two different exercise sessions (high-intensity interval exercise [HIIE] and moderate-intensity exercise [MICE]). RESULTS: During the last complete stage of the mYMCA, despite the difference in ∆bpm from target HR between groups (REACH: 6 [4] bpm, 74 [12] %HRR; No-REACH: 21 [13] bpm, 60 [14] %HRR; p = 0.002), there was no group difference for PE (REACH: 7 [3], No-REACH: 8 [2]; p = 0.08) and La- (REACH: 5.5 [1.2], No-REACH: 5.5 [4.5]; p = 0.92). Except for PE at the end of MICE (REACH: 3 [2] vs. No-REACH: 5 [1]; p = 0.02), there was no difference between REACH and No-REACH for end-session La- (HIIE: 4.9 [1.7] vs. 4.4 [3.2]; p = 0.37; MICE: 2.8 [1.6] vs. 3.7 [2.1]; p = 0.43) nor for PE at the end of HIIE (5 [4] vs. 6 [6]; p = 0.27). CONCLUSIONS: These results suggest that using HR as the only stopping criterion for a submaximal test may lead some cancer patients to exceed the targeted submaximal threshold and perform a near-maximal test. These results raise the relevance of combining objective and subjective intensity measures to provide a personalized exercise prescription. Supported by the Sylvain Poissant Foundation.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 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".