GDF-15 Is Associated with Poor Physical Function in Prefrail Older Adults with Diabetes
Bibliographic record
Abstract
Introduction. Growth differentiation factor 15 (GDF-15) has been shown to be a metabolic and appetite regulator in diabetes mellitus (DM) and obesity. We aimed to investigate (i) the association between GDF-15 and DM with and without poor physical function independent of inflammation and (ii) the prediction model for poor physical function in prefrail older adults. Methods. A cross-sectional study of 108-prefrail participants ≥60 years recruited for multidomain interventions. Data was collected for demographics, cognition, function, frailty, nutrition, handgrip strength (HGS), short physical performance battery (SPPB), and gait speed. Serum concentrations of GDF-15, IL-6, and TNF-α were measured. GDF-15 was classified into tertiles (T1, T2, and T3), and its association was studied with DM and physical function (DM poor physical function, DM no poor physical function, no DM poor physical function, and no DM no poor physical function). Results. Compared with T1, participants in T3 were significantly older, had a lower education level, had almost three times higher prevalence of DM, slower gait speed, longer chair-stand time, and lower SPPB scores. On multivariate analysis, the odds of having both DM and poor physical performance compared to having no DM and no poor physical performance were significantly higher in GDF-15 T3 vs. GDF-15 T1 (aOR 9.7, 95% CI 1.4-67.7; p = 0.021 ), and the odds of having DM no poor physical function compared to having no DM and no poor physical performance were significantly higher in GDF-15 T2 (aOR 12.7, 95% CI 1.1-143.7; p = 0.040 ) independent of BMI, IL-6, TNF-α, nutrition, physical function, education, age, and gender. Conclusion. The association of GDF-15 with DM-associated poor physical function is independent of inflammation in prefrail older adults. Its causal-association link needs to be determined in longitudinal studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".