Fat-Free Mass Index Controlled for Age and Sex and Malnutrition Are Predictors of Survival in Interstitial Lung Disease
Why this work is in the frame
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Bibliographic record
Abstract
<b><i>Background:</i></b> Literature focusing on nutritional variables and survival in interstitial lung disease (ILD) is limited by its focus on weight and BMI and has not considered body composition. <b><i>Objectives:</i></b> The primary objective of this study was to examine whether body composition measures, specifically fat-free mass index z-score (z-FFMI) and body fat mass index z-score (z-BFMI), were predictors of survival in fibrotic ILD patients. The second objective was to examine if nutrition status was a predictor of survival. <b><i>Method:</i></b> Seventy-eight outpatients diagnosed with fibrotic ILD were recruited in this cross-sectional study. Body composition data using dual frequency bioelectrical impedance analysis (BodyStat 1500MD; UK) and nutrition status using the subjective global assessment (SGA) were determined. To control for age and sex, z-FFMI and z-BFMI were calculated using population means. Participant charts were reviewed for diagnosis, age, disease severity, and exercise capacity. <b><i>Results:</i></b> Age (HR 1.08, 95% CI [1.03–1.13], <i>p</i> &#x3c; 0.01), BMI (HR 0.90, 95% CI [0.84–0.97], <i>p</i> &#x3c; 0.01]), z-FFMI (HR 0.70, 95% CI [0.56–0.87], <i>p</i> = 0.02), z-BFMI (HR 0.74, 95% CI [0.57–0.96], <i>p</i> &#x3c; 0.01), 6-min walk distance (6MWD) (HR 0.99, 95% CI [0.99–1.00], <i>p</i> &#x3c; 0.01), percent predicted diffusing capacity for carbon monoxide (%DLco) (HR 0.93, 95% CI [0.89–0.97], <i>p</i> &#x3c; 0.01), and severe malnutrition (SGA-C) (HR 6.98, 95% CI [2.00–24.27], <i>p</i> &#x3c; 0.01) were significant predictors of survival. When controlled for exercise capacity and disease severity, z-FFMI and severe malnutrition were significant predictors of survival independent of %DLco. <b><i>Conclusion:</i></b> z-FFMI and severe malnutrition were significant predictors of survival in fibrotic ILD patients independent of disease severity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it