Reliability of Calf Bioelectrical Impedance Spectroscopy and Magnetic-Resonance-Imaging-Acquired Skeletal Muscle Hydration Measures in Healthy People
Bibliographic record
Abstract
Purpose. The purpose of this study was to investigate the test-retest reliability, relative variability, and agreement between calf bioelectrical impedance-spectroscopy (cBIS) acquired extracellular fluid (ECF), intracellular fluid (ICF), total water and the ratio of ECF : ICF, magnetic-resonance-imaging (MRI) acquired transverse relaxation times ( T2 ), and apparent diffusion coefficient (ADC) of calf muscles of the same segment in healthy individuals. Methods. Muscle hydration measures were collected in 32 healthy individuals on two occasions and analyzed by a single rater. On both occasions, MRI measures were collected from tibialis anterior (TA), medial (MG), and lateral gastrocnemius (LG) and soleus muscles following the cBIS data acquired using XiTRON Hydra 4200 BIS device. The intraclass correlation coefficients (ICC2,1), coefficient of variation (CV), and agreement between MRI and cBIS data were also calculated. Results. ICC2,1 values for cBIS, T2 , and ADC ranged from 0.56 to 0.92, 0.96 to 0.99, and 0.05 to 0.56, respectively. Relative variability between measures (CV) ranged from 14.6 to 25.6% for the cBIS data and 4.2 to 10.0% for the MRI-acquired data. The ratio of ECF : ICF could significantly predict T2 of TA and soleus muscles. Conclusion. MRI-acquired measures of T2 had the highest test-retest reliability of muscle hydration with the least error and variation on repeated testing. Hence, T2 of a muscle is the most reliable and stable outcome measure for evaluating individual muscle hydration.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".