Serum growth differentiation factor 15 level is associated with muscle strength and lower extremity function in older patients with cardiometabolic disease
Bibliographic record
Abstract
AIMS: Sarcopenia is a serious problem because of its poor prognosis. Growth differentiation factor 15 (GDF15) is associated with mitochondrial dysfunction, inflammation, insulin resistance and oxidative stress, which may play crucial roles for the development of sarcopenia. We aimed to examine whether serum GDF15 level is associated with muscle mass, strength and lower extremity function in older patients with cardiometabolic disease. METHODS: Serum GDF15 levels were measured in 257 patients with cardiometabolic diseases (including 133 patients with diabetes) who had visited the frailty clinic, using a latex turbidimetric immunoassay. Appendicular skeletal muscle index, handgrip strength, timed-up-and-go test and gait speed were evaluated. Power, speed, balance and total scores based on the sit-to-stand test were calculated to assess lower extremity function. RESULTS: The highest tertile of serum GDF15 was independently associated with low handgrip strength, low gait speed, long timed-up-and-go time and scores of lower extremity function but not an appendicular skeletal muscle index in multiple logistic regression analyses after adjustment for covariates. Patients in the highest tertile of GDF15 were at the risk of having three to nine times lower grip strength, three times lower gait speed, five to six times lower mobility and five to 11 times reduction in lower extremity function as compared with those in the lowest GDF15 tertile dependent on the models. CONCLUSIONS: Elevated serum GDF15 level was independently associated with low muscle strength and lower extremity function in older patients with cardiometabolic disease. Serum GDF15 could be one of the biomarkers for muscle weakness and low physical performance. Geriatr Gerontol Int 2020; 20: 980-987.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".