Exercise capacity and its relationship with body composition and nutrition status in patients with interstitial lung disease
Bibliographic record
Abstract
BACKGROUND: Patients with interstitial lung disease (ILD) are known to have diminished exercise ability. This study aimed to explore the relationship between nutrition status and body composition parameters with exercise capacity in ILD patients. A second aim focused on assessing the appropriateness of surrogate markers of nutrition status in ILD patients. METHODS: Disease severity was determined by the percentage of predicted forced vital capacity. Exercise capacity was determined using 6-minute walk distance. Nutrition status was assessed using the subjective global assessment (SGA), standardized phase angle (SPhA), and impedance ratio z-score (z-IR). Bioelectrical impedance analysis estimated body composition parameters. RESULTS: 45 of 79 participants (57%) were malnourished according to the SGA. FFM index z-score (z-FFMI) (r = 0.42, P = .02) and SGA (r = 0.49, P < .01) were significant predictors of exercise capacity independent of disease severity. Age (odds ratio [OR] = 1.1; 95% CI, 1.01-1.25; P = .04), low body mass index (OR = 0.73; 95% CI, 0.57-0.92; P = .01), z-FFMI (OR = 0.34; 95% CI, 0.17-0.68; P < .01), and body fat mass index z-score (OR = 0.39; 95% CI, 0.17-0.91; P = .03) were significantly associated with severe malnutrition. There was no significant difference in SPhA across SGA groups; however, a higher z-IR (poorer cell health) significantly increased the odds of severe malnutrition (OR = 2.75; 95% CI, 1.27-6.03; P = .02). CONCLUSION: In ILD patients, malnutrition and loss of FFM negatively impact the ability to perform activities of daily living.
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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 | 0.001 |
| 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".