Reliability of the Determination of the Ventilatory Threshold in Patients with COPD
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to determine the interobserver reliability of the assessment of the ventilatory threshold (VT) using two methods in patients with chronic obstructive pulmonary disease (COPD) and in control subjects. METHODS: VT was identified from incremental exercise testing graphs of 115 subjects (23 controls and 23 in each COPD Global initiative for chronic Obstructive Lung Disease class) by two human observers and a computer analysis using the V-slope method and the ventilatory equivalent method (VEM). Agreement between observers in identifying oxygen uptake at VT (VO 2VT) and HR at VT (HR VT) across disease severity groups was evaluated using intraclass correlation (for humans) and Passing-Bablok regression analysis (human vs computer). RESULTS: For human observers, ICC (95% confidence interval) in determining VO 2VT were higher in controls (0.98 (0.97-0.99) both with V-slope and with VEM) than those in COPD patients (0.72 (0.60-0.81) with V-slope and 0.64 (0.50-0.74) with VEM). Passing-Bablok analysis showed that human and computerized determination of VO 2VT was interchangeable in controls but not in patients with COPD. Forced expiratory volume in one second and peak minute ventilation during exercise were the only variables independently associated with greater interobserver differences in VO 2VT. Interobserver differences in HRVT ranged from 2 ± 1 (controls) to 10 ± 3 bpm (GOLD 4). CONCLUSIONS: In patients with COPD, the reliability of human estimation of VO 2VT is less than that in controls and not interchangeable with a computerized analysis. This should be taken into account when using VT for exercise prescription, as a tool to monitor responses to an intervention, as a surrogate measure of overall aerobic fitness, or as a prognostic marker in patients with COPD.
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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 | 0.004 | 0.018 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".