Association Between Skeletal Muscle Mass Indices and Cognitive Function Among Inpatients With Stable Schizophrenia
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To investigate the correlation between appendicular skeletal muscle mass (ASM)/height (ASMIht), ASM/body mass index (ASMIBMI), ASM/weight (ASMIwt), and ASM/waist circumference (ASMIwc) and cognitive function among inpatients with stable schizophrenia. METHODS: This was a cross-sectional study of 235 stable schizophrenia inpatients, including 60% males (n=141). Patient demographic information and body composition data were collected. The Montreal Cognitive Assessment-Chinese version (MoCA-C) was used to measure cognitive function. To determine the association between the muscle mass indices and cognitive function, multiple linear regressions were established. RESULTS: The median age of males and females were 51 years (range 42-55) and 51 (range 39-58), respectively. Spearman's correlation analysis revealed a significant association between ASMIwc and the MoCA-C scores (r=0.323, false discovery rate [FDR]=0.004) in males, while ASMIBMI, ASMIwt, and ASMIwc (r=0.268-0.421, all FDR <0.05) were significantly correlated with MoCA-C scores in females. Furthermore, covariate-adjusted multiple linear regression analysis further confirmed that only the ASMIwc was related to MoCAC scores after controlling for relevant variables (males: β=0.565, 95% confidence interval [CI], 0.156-0.974, p=0.007; females: β=0.96, 95% CI, 0.394-1.526, p=0.001). CONCLUSION: Our findings showed a substantial correlation between the ASMIwc and cognitive function in schizophrenia inpatients. Further validation of these data in broader study populations is now necessary.
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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 | 0.001 |
| 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) | 0.000 | 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