The Impact of Quadriceps Muscle Layer Thickness on Length of Stay of Patients Listed for Renal Transplant
Bibliographic record
Abstract
Background: Quadriceps muscle layer thickness (QMLT), which is measured using ultrasound, is an emerging strategy to identify sarcopenia. Purpose: The purpose of the study was to assess whether pre-operative QMLT values are associated with a prolonged length of stay (LOS; defined as >14 days) following a renal transplant. Methods: Between March 2019 and January 2020, we performed a prospective study among patients undergoing renal transplantation. Physical Frailty scores and QMLT measurements were performed pre-operatively. The primary outcome was a greater LOS following transplant. Secondary outcomes included complications and renal function. Statistical analysis: Percentiles divided patients into two categories of QMLT (low and high). Continuous outcomes were compared using a two-sided t-test or Mann–Whitney U test, and Chi-square analysis and Fisher exact testing were used for nominal variables. Results: Of 79 patients, the frailty prevalence was 16%. Among patients with low and higher QMLTs, LOS of >14 days were 21% vs. 3% [p = 0.04], respectively. Demographically, there was a higher percentage of patients with living donors in the high- vs. low-QMLT groups (40 vs. 7%). However, in a subgroup analysis excluding living-donor recipients, the difference between groups was preserved (23% vs. 0%, p = 0.01). No differences in secondary outcomes were seen between groups. Conclusions: Low quadriceps muscle layer thickness may be associated with a prolonged length of stay for renal recipients. Further research is needed to confirm our findings.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 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".