Reproducibility of metabolic parameters measured during endurance shuttle walking test in patients with COPD
Bibliographic record
Abstract
RATIONALE: Cardiorespiratory adaptations to exercise can be monitored during endurance shuttle walking test (ESWT) using a portable telemetric gas analyser. The aim of this study was to investigate the reproducibility of metabolic parameters measured at the end of two ESWTs in patients with Chronic Obstructive Pulmonary Disease (COPD). METHODS: 97 patients with moderate to severe COPD (FEV1 = 49 ± 13% of predicted value, ranging from 31 to 78 % of predicted value) performed two ESWTs one week apart. ESWTs were performed at a speed corresponding to 85% of peak oxygen uptake, as predicted from the incremental shuttle walking test. Metabolic and cardiorespiratory parameters were monitored during both ESWTs using a portable Oxycon mobile device. Maximal values for oxygen uptake (VO2), heart rate (HR), ventilation (VE) and respiratory exchange ratio (RER) were compared using paired t-tests and Pearson correlations between maximal values of both tests were estimated. RESULTS: Mean differences between both ESWTs performances were -5.2 ± 66 sec and -6.8 ± 107 m for the endurance time and distance respectively. The mean differences for maximal values between ESWTs were not significantly different for each parameter. Significant correlations were found for each parameter between the maximal values of both tests, with good correlation coefficients (r2=0.79, 0.43, 0.63 and 0.53 for VO2, VE, HR and RER respectively). CONCLUSIONS: The results highlight a high level of reproducibility of the maximal values of metabolic and cardiorespiratory parameters measured during ESWTs. FUNDING: GlaxoSmithKline NCT01124422 ;ADC113877.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".