Muscle Mass and Mortality After Cardiac Transplantation
Bibliographic record
Abstract
BACKGROUND: Frailty assessment is recommended to evaluate the candidacy of adults referred for orthotopic heart transplantation (OHT). Psoas muscle area (PMA) is an easily measured biomarker for frailty. There has yet to be a study examining the prognostic impact of PMA in OHT patients. METHODS: In this retrospective study, preoperative and postoperative computed tomography (CT) scans were retrieved for adults transplanted between 2000 and 2015 at a tertiary care hospital. Psoas muscle area was measured on a single axial image. Outcomes of interest were all-cause mortality over 6 years and a composite of in-hospital mortality or major morbidity (prolonged ventilation, stroke, dialysis, mediastinitis, or reoperation). RESULTS: Of 161 adult patients transplanted, 82 had at least 1 abdominal CT scan. At baseline, mean PMA was 25.7 ± 5.8 cm in men and 16.0 ± 3.6 cm in women, and decreased by 8% from the first to the last available CT scan. Adjusting for age, sex, body mass index, and cardiomyopathy etiology, every 1-cm increase in PMA was found to be associated with a 9% reduction in long-term mortality (hazard ratio, 0.91; 95% confidence interval [CI], 0.83-0.99; P = 0.031) and a 17% reduction in in-hospital mortality or major morbidity (odds ratio, 0.83; 95% CI, 0.72-0.96; P = 0.014). When PMA was smaller than the sex-specific median, the risk of mortality or major morbidity increased fourfold (odds ratio, 4.29; 95% CI, 1.19-15.46; P = 0.026). CONCLUSIONS: Muscle mass is an independent predictor of mortality and major morbidity after OHT. Further research is needed to determine whether frail OHT patients with low PMA may benefit from muscle-building interventions to improve outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".