Investigating the Impact of Forced Vital Capacity on Maximum Exercise Capacity and Dyspnea During Incremental Exercise
Bibliographic record
Abstract
Abstract Rationale: Patients with restrictive lung disease have a reduced quality of life regardless of the underlying diagnosis. It is unclear if therapies targeting improvement in forced vital capacity (FVC) leads to an improvement in exercise capacity and reduced breathlessness. We assume that the reduction in FVC alone is the sole contributor for reduction in exercise capacity leading to symptoms. This study investigated the impact of FVC on maximum power output (MPO) and effort required to breath alongside other independent variables. Methods: A cross-sectional, retrospective study of all patients >18 years of age with non-obstructive spirometry (FEV1/FVC <70%) and FVC<80% predicted who performed incremental cardio-pulmonary exercise testing (CPET) on cycle ergometry at the McMaster University Medical Centre between 1988-2012. MPO achieved ranged from 0 to 2200 kpm/min, with data analysis focused on MPO values between the 5th and 95th percentiles (200-1200 kpm/min) to exclude outliers. Patients rated their breathing effort at incremental workloads using a modified Borg scale (mBorg). A nonlinear multivariate regression model assessed the independent variables contributing to MPO and mBorg breathing effort scores. Results: 5658 patients had a non-obstructive defect (mean±SD age 56±15.3, BMI 28.65±6.3, FVC 2.47L±0.7, DLCO 80.8%±20.1). Quadriceps muscle strength, FVC and KCO were the top 3 variables influencing MPO (MPO kpm/min = 35[asterisk]Quad0.34[asterisk]FVC0.60[asterisk]Kco 0.33, r=0.81). A 10% increase in FVC was associated with a modest 6% increase in MPO. Dyspnea (mBorg) during exercise was influenced predominantly by power at each work load and the MPO. However, for each 100 ml increase in FVC, there was only a modest improvement in mBorg scores of 0.04. Conclusion: In patients with restrictive spirometry, muscle strength, efficiency of gas exchange, and FVC influence MPO, although the independent impact of FVC on MPO is limited. Similarly, small changes in FVC had minimal effects on perceived dyspnea. These findings underscore the importance of muscle strength and gas exchange properties in determining exercise capacity and dyspnea perception. Improving FVC alone may be insufficient to substantially alter exercise capacity and symptomatic outcomes.
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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 | 0.001 | 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 | 0.000 |
| 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".