A standardized approach to evaluate effectiveness of aerobic exercise training interventions in cardiovascular disease at the individual level
Bibliographic record
Abstract
Background Reliable change indices can determine pre-post intervention changes at an individual level that are greater than chance or practice effect. We applied previously developed minimal meaningful change (MMC RCI ) scores for oxygen uptake (V̇O 2 ) values associated with estimated lactate threshold (θ LT ), respiratory compensation point (RCP), and peak oxygen uptake (V̇O 2peak ) to evaluate the effectiveness of exercise training in cardiovascular disease patients. Methods 303 patients (65 ± 11 yrs.; 27% female) that completed a symptom-limited cardiopulmonary exercise test (CPET) before and after 6-months of guideline-recommended exercise training were assessed to determine absolute and relative V̇O 2 at θ LT , RCP, and V̇O 2peak . Using MMC RCI ∆V̇O 2 scores of ±3.9 mL·kg −1 ·min −1 , ±4.0 mL·kg −1 ·min −1 , and ± 3.6 mL·kg −1 ·min −1 for θ LT , RCP, and V̇O 2peak , respectively, patients were classified as "positive" (Δθ LT , ΔRCP, and/or ΔV̇O 2peak ≥ +MMC RCI ), "non-" (between ±MMC RCI ), or "negative" responders (≤ -MMC RCI ). Results Mean RCP ( n = 86) and V̇O 2peak ( n = 303) increased ( p < 0.05) from 19.4 ± 3.6 mL·kg −1 ·min −1 and 18.0 ± 6.3 mL·kg −1 ·min −1 to 20.1 ± 3.8 mL·kg −1 ·min −1 and 19.2 ± 7.0 mL·kg −1 ·min −1 at exit, respectively, whereas θ LT ( n = 140) did not change (15.5 ± 3.4 mL·kg −1 ·min −1 versus 15.7 ± 3.8 mL·kg −1 ·min −1 , p = 0.324). For changes in θ LT , 6% were classified as "positive" responders, 90% as "non-responders", and 4% as "negative" responders. For RCP, 10% exhibited "positive" changes, 87% were "non-responders", and 2% were "negative" responders. For ΔV̇O 2peak , 57 patients (19%) were classified as "positive" responders, 229 (76%) as "non-responders", and 17 (6%) as "negative" responders. Conclusion Most patients that completed the exercise training program did not achieve reliable improvements greater than that of chance or practice at an individual level in θ LT , RCP and V̇O 2peak .
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".