Using the 6-min Walk Test to Monitor Peak Oxygen Uptake Response to Cardiac Rehabilitation in Patients With Heart Failure
Bibliographic record
Abstract
PURPOSE: We examined the agreement between peak oxygen uptake (V˙o2peak), estimated using prediction equations from the 6-min Walk Test (6MWT), and V˙o2peak measured using a cardiopulmonary exercise test (CPX) to estimate change in V˙o2peak in patients with heart failure (HF) enrolled in cardiac rehabilitation (CR). METHODS: This was secondary analysis of 54 (including 9 women) patients with HF who completed a clinical CR program. Four previously published equations using 6MWT distance were used to estimate V˙o2peak and were compared with a CPX at baseline, follow-up, and change using the standard and modified Bland-Altman method. Analyses were repeated for quartiles of cardiorespiratory fitness (CRF) based on measured V˙o2peak from the CPX. RESULTS: Bland-Altman plots revealed proportional bias between all prediction equations and the measured V˙o2peak. The difference between methods varied by the level of CRF, with overestimation of prediction equations at greater levels of CRF and underestimation at lower levels of CRF. This poor agreement remained when comparisons were made between the estimated and measured V˙o2peak values at quartiles of CRF, indicating prediction equations have limited ability to predict V˙o2peak at any level of CRF. CONCLUSION: Estimated V˙o2peak using 6MWT distance demonstrated poor agreement with measured V˙o2peak from a CPX. While distance ambulated on the 6MWT remains an important measure of physical performance in patients with HF, prediction equations using 6MWT distance are not appropriate to monitor changes in V˙o2peak following CR in patients with HF.
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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) | 0.001 | 0.000 |
| 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 | 0.001 | 0.001 |
| 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 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".