Ventilatory inefficiency relative to oxygen uptake and carbon dioxide output are independent predictors of mortality in pulmonary arterial hypertension
Bibliographic record
Abstract
Background: Exercise intolerance is a well-established prognostic marker in a number of cardiopulmonary diseases. In pulmonary arterial hypertension (PAH), excessive ventilatory (VE) response relative to metabolic demand associated with insufficient O 2 delivery are important factors impairing patients' exercise capacity. We therefore investigated whether the dynamic relationship between VE and both pulmonary carbon dioxide output (VCO 2 ) and O 2 uptake (VO 2 ) would constitute negative prognostic markers in this patient population. Methods: Eighty-one patients (36 idiopathic and 45 with associated conditions) were followed-up for up to 5 yrs. VE/VCO 2 slope (rest-to-peak data) and VO 2 efficiency slope (OUES) were calculated and analyzed in association with traditional cardiopulmonary exercise test (CPET)-based measurements. Results: Fourteen patients (17 %) died during the follow-up period. Resting variables were not related to prognosis ( p >0.05). Univariate analysis indicated that peak VO 2 , ΔVO 2 /Δ work rate, ΔV’E/ΔV’CO 2 and OUES were associated with lower survival ( p <0.05). A multiple regression analysis of dichotomized data obtained after a ROC curve analysis showed that ΔV’E/ΔV’CO 2 ≥ 55 [hazard ratio (HR) (95% CI)= 11.16 (1.4-86.6); p = 0.02] and OUES ≤ 0.56 [HR 11.24 (3.5-35.8); p = 0.02] were independent predictors of mortality. Association of these findings increased OR for mortality to 18.2 (5.8-57.3), p <0.01. Conclusion: Ventilatory inefficiency relative to pulmonary gas exchange during rapidly-incremental CPET is a marker of poor prognosis in patients with PAH.
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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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.001 |
| 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".