Quantifying Improvement in V˙o 2peak and Exercise Thresholds in Cardiovascular Disease Using Reliable Change Indices
Bibliographic record
Abstract
PURPOSE: Improving aerobic fitness through exercise training is recommended for the treatment of cardiovascular disease (CVD). However, strong justifications for the criteria of assessing improvement in key parameters of aerobic function including estimated lactate threshold (θ LT ), respiratory compensation point (RCP), and peak oxygen uptake (V˙ o2peak ) at the individual level are not established. We applied reliable change index (RCI) statistics to determine minimal meaningful change (MMC RCI ) cutoffs of θ LT , RCP, and V˙ o2peak for individual patients with CVD. METHODS: Sixty-six stable patients post-cardiac event performed three exhaustive treadmill-based incremental exercise tests (modified Bruce) ∼1 wk apart (T1-T3). Breath-by-breath gas exchange and ventilatory variables were measured by metabolic cart and used to identify θ LT , RCP, and V˙ o2peak . Using test-retest reliability and mean difference scores to estimate error and test practice/exposure, respectively, MMC RCI values were calculated for V˙ o2 (mL·min -1. kg -1 ) at θ LT , RCP, and V˙ o2peak . RESULTS: There were no significant between-trial differences in V˙ o2 at θ LT ( P = .78), RCP ( P = .08), or V˙ o2peak ( P = .74) and each variable exhibited excellent test-retest variability (intraclass correlation: 0.97, 0.98, and 0.99; coefficient of variation: 6.5, 5.4, and 4.9% for θ LT , RCP, and V˙ o2peak , respectively). Derived from comparing T1-T2, T1-T3, and T2-T3, the MMC RCI for θ LT were 3.91, 3.56, and 2.64 mL·min -1. kg -1 ; 4.01, 2.80, and 2.79 mL·min -1. kg -1 for RCP; and 3.61, 3.83, and 2.81 mL·min -1. kg -1 for V˙ o2peak . For each variable, MMC RCI scores were lowest for T2-T3 comparisons. CONCLUSION: These MMC RCI scores may be used to establish cutoff criteria for determining meaningful changes for interventions designed to improve aerobic function in individuals with CVD.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".