A Protocol to Establish Exercise Intensity Domains for Aerobic Exercise Training in Coronary Artery Disease
Bibliographic record
Abstract
INTRODUCTION/PURPOSE: The oxygen uptake (V̇O 2 )-power output (PO) relationship from incremental exercise needs to be adjusted to accurately prescribe constant-intensity exercise training. We assessed the accuracy of a "step-ramp-step" (SRS) protocol for prescribing constant PO exercise within moderate-intensity (below estimated lactate threshold, θ LT ), heavy-intensity (between θ LT and respiratory compensation point, RCP), and severe-intensity (above RCP) domains in 14 patients with coronary artery disease (CAD). METHODS: The SRS protocol included the following: 6 min of cycling at 25-40 W, a ramp-incremental test until task failure (5-15 W · min -1 ), and, after a 20 min recovery, 12 min of cycling at ~50%-60% of peak ramp PO. On separate days, patients performed three domain-specific constant PO exercises at 80% θ LT (moderate intensity [MOD]), 70% of the difference between θ LT and RCP (heavy intensity [HVY]), and 115% RCP (severe intensity [SEV]). Measured V̇O 2 values for MOD and HVY were compared with those predicted using either SRS-corrected or uncorrected approaches and, for SEV, were compared with peak ramp V̇O 2 . RESULTS: The PO values for MOD, HVY, and SEV were 53 ± 27, 96 ± 50, and 116 ± 56 W, respectively, eliciting V̇O 2 of 1012 ± 362, 1541 ± 638, and 1944 ± 744 mL·min -1 . The SRS-corrected predictions did not differ from measured V̇O 2 for MOD (-25 ± 61 mL·min -1 ; P = 0.201) or HVY (-40 ± 89 mL·min -1 ; P = 0.208), whereas uncorrected predictions underestimated V̇O 2 by -128 ± 72 mL·min -1 ( P = 0.002) and -199 ± 99 mL·min -1 ( P = 0.001) in MOD and HVY, respectively. Peak V̇O 2 from SEV did not differ from the ramp (1906 ± 766 mL·min -1 ; P = 0.759). CONCLUSIONS: In CAD, the V̇O 2 -PO relationship from incremental exercise must be corrected to prescribe constant-intensity training. The SRS protocol is an accurate approach to ensure prescriptive accuracy.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".