Comparative response to incremental cardiopulmonary exercise testing in patients with uni- and bilateral diaphragm dysfunction
Bibliographic record
Abstract
Introduction: Diaphragm dysfunction (DD) is associated with exercise intolerance, but the comparative impact of uni- and bilateral DD on exercise response remains poorly described. We compared exercise responses of patients with unilateral (UDD) and bilateral (BDD) DD during cardiopulmonary exercise testing (CPET). Methods: We recruited patients with DD from our center. DD was defined by ultrasound diaphragm thickening fraction (TFdi) <30%. Patients were classified as UDD or BDD. Exercise response during CPET [including peakVO2, ventilation (VE), ventilatory reserve, VE/VCO2 ratio, end-tidal CO2 (EtCO2)] was compared between groups. Resting physiological and diaphragm ultrasound variables were tested as predictors of exercise response. Results: 35 patients were included (27 UDD and 7 BDD). Mean age, BMI and smoking history were similar between groups (p>0.05). Patients with BDD had lower sitting and supine vital capacity, total lung capacity, and maximal inspiratory pressure (p<0.05). They also had significantly lower values of peakVO2 (11.2±1.8 vs 16±4.3 ml/kg/min, p=0.01), peakVE (p=0.03), VE/VCO2 ratio (23±4 vs 34±7, p=0.003) and higher ventilatory reserve (p=0.04), peak respiratory rate (49±5 vs 37±8, p<0.001), and EtCO2 (47±3 vs 36±8 mmHg, p=0.003). In BDD patients, TFdi was correlated to peakVO2 (rho=0.94, p<0.001) and EtCO2 (rho=0.60, p=0.04), but not in UDD. Conclusion: Compared to UDD, BDD is associated with a decrease in peakVO2 related to ventilatory inefficiency that can be predicted using resting diaphragm ultrasound. Future studies should address whether CPET and TFdi could serve as markers of response to therapeutic interventions in this population.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".