Classification of People With Chronic Respiratory Disease Into Preserved or Reduced Functional Exercise Capacity: A Retrospective Analysis of Associated Factors Considering Baseline Characteristics and Responses to Pulmonary Rehabilitation
Bibliographic record
Abstract
Purpose: To classify individuals with chronic respiratory disease (CRD) into preserved or reduced functional exercise capacity (FEC) using the baseline 6-minute walk distance (6MWD), as well as to compare between these two groups other baseline characteristics, physiological and symptomatologic responses to the baseline 6-minute walk test (6MWT), and responses in health-related quality of life (HRQoL) and FEC to pulmonary rehabilitation (PR). Method: Sociodemographic and clinical data, lung function, HRQoL, and FEC (6MWT) from individuals with CRD who participated in a PR programme were analyzed. Individuals were classified as with preserved or reduced FEC, if 6MWD was ≥ or < the lower limit of normality, respectively. Results: We included 117 individuals (50% male, age 61 years, 39% with chronic obstructive pulmonary disease), 76 classified as preserved FEC and 41 as reduced FEC. Individuals with reduced FEC had the lowest values for weight and lung function. No statistical difference was found when comparing the changes in HRQoL and 6MWD after PR between the preserved and reduced FEC groups. However, the mean 6MWD change in the reduced FEC group (61 m) was twice the change in the preserved FEC group (30m). Conclusions: The classification into preserved or reduced FEC proved to be useful in PR as it allowed to identify individuals with CRD with lower weight and lung function at baseline, but who seemed to benefit more from the programme.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".