Variability of cardiopulmonary exercise testing in patients with atrial fibrillation and determination of exercise responders to high-intensity interval training and moderate-to-vigorous intensity continuous training
Bibliographic record
Abstract
Disabling atrial fibrillation (AF)-related symptoms and different testing settings may influence day-to-day cardiopulmonary exercise testing (CPET) measurements, which can affect exercise prescription for high-intensity interval training (HIIT) and moderate-to-vigorous intensity continuous training (M-VICT) and their outcomes. This study examined the reliability of CPET in patients with AF and assessed the proportion of participants achieving minimal detectable changes (MDC) in peak oxygen consumption (V̇O2peak) following HIIT and M-VICT. Participants were randomized into HIIT or M-VICT after completing two baseline CPETs: one with cardiac stress technologists (CPETdiag) and the other with a research team of exercise specialists (CPETresearch). Additional CPET was completed following 12 weeks of twice-weekly training. The reliability of CPETdiag and CPETresearch was assessed by intraclass correlation coefficient (ICC) and dependent t tests. The MDC score was calculated for V̇O2peak using a reliable change index. The proportion of participants achieving MDC was compared between HIIT and M-VICT using chi-square analysis. Eighteen participants (69 ± 7 years, 33% females) completed two baseline CPETs. The ICCs were significant for all measured variables. However, peak power output (POpeak: 124 ± 40 vs. 148 ± 40 watts, p < 0.001) and HR (HRpeak: 136 ± 22 vs. 148 ± 30 bpm, p = 0.023) were significantly greater in CPETresearch than CPETdiag. Few participants achieved MDC in V̇O2peak (5.6 mL/kg/min) with no difference between HIIT (0%) and M-VICT (10.0%, p = 0.244). POpeak and HRpeak differed significantly in patients with AF when CPETs were repeated under different settings. Caution must be practised when prescribing exercise intensity based on these measures as under-prescription may increase the number of exercise non-responders.
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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 | 0.010 |
| 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".