Body mass index–adjusted calf circumference is associated with mortality in hospitalized older patients with excess weight
Bibliographic record
Abstract
ABSTRACT Objectives Given the innovative nature of the method, our study aimed to assess the prognostic significance of body mass index (BMI)-adjusted calf circumference (CC) in older patients who are hospitalized. Methods This was a unique analysis as part of other cohorts comprising general hospitalized patients aged 60 years or older of both sexes. Only patients with excess weight (BMI ≥ 25 kg/m 2 ) were included. CC was adjusted by reducing 3, 7, or 12 cm for BMI (in kg/m 2 ) within 25-29.9, 30–39.9, and ≥40 kg/m 2 , respectively. CC was considered low if ≤ 34 cm for males and ≤ 33 cm for females. Clinical outcomes included prolonged length of hospital stay (LOS) and mortality. Results A total of 222 patients were included. After BMI adjustments, 72.1% of the patients were reclassified from a normal CC category to a low CC category. The frequency of low CC increased from 33.8% to 81.9% following BMI adjustments. Among those reclassified to the low CC, 11 died, compared to only 2 patients in the group that maintained a normal CC classification. BMI-adjusted CC was inversely associated with mortality (HR adjusted 0.84, 95% CI 0.73 to 0.95), but not with prolonged LOS. Conclusions Our novel study highlights the prognostic value of BMI-adjusted CC. As an anthropometric marker of muscle mass, it proved to be a predictor of mortality in older patients with high BMI. This adjustment is further important because it may help to better detect low muscle mass in these patients where such conditions might be masked.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".