Bedside tests of muscle mass in older adults with Type 2 diabetes
Bibliographic record
Abstract
<abstract><sec> <title>Objective</title> <p>Diabetes and sarcopenia often coexist in older adults, suggesting a possible bidirectional association. Available bedside measures of muscle mass consist of bedside ultrasound (MT, quadriceps muscle thickness) and Bioelectrical Impedance Analysis (BIA). We examined the association between ultrasound measures and BIA measures of muscle in older adults with measures of strength, performance and frailty in older adults with diabetes.</p> </sec><sec> <title>Design</title> <p>Cross-sectional study.</p> </sec><sec> <title>Methods</title> <p>81 subjects (age ≥ 65; mean age 80.8 ± 0.6 years, 27 women, 53 men) were recruited sequentially from geriatric medicine clinics. Each subject had Lean Body Mass (LBM, by BIA, in kg), grip strength, gait speed, Cardiovascular Health Study index (frailty) and MT (in cm) measured. All initial models were adjusted for biological sex.</p> </sec><sec> <title>Results</title> <p>In our final parsimonious models, only MT (as opposed to LBM) showed a significant correlation with grip strength (Standardized β = 0.217 ± 0.078; p = 0.007) and frailty (Standardized β = 0.276 ± 0.109; p = 0.013). Neither MT or LBM showed a significant association with subject performance (gait speed).</p> </sec><sec> <title>Conclusions</title> <p>Unlike BIA, bedside ultrasound measures of muscle thickness showed strong associations with both grip strength and frailty in the older adult population with diabetes, suggesting that bedside measures of MT might be a more clinically useful modality to assess muscularity in this patient population. Neither BIA or MT measures of subject muscularity showed any association with our performance indicator (gait speed).</p> </sec></abstract>
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.001 | 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 teacher head, 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".