Sarcopenic obesity in cirrhosis—The confluence of 2 prognostic titans
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sarcopenia and obesity are 2 major health conditions with a growing prevalence in cirrhosis. The concordance of these 2 conditions, sarcopenic obesity, is associated with higher rates of mortality and impact on the metabolic profile and physical function than either condition alone. To date, there is little consensus surrounding the diagnostic criteria for sarcopenia, obesity or as a result, sarcopenic obesity in patients with cirrhosis. Cross-sectional imaging, although the most accurate diagnostic technique, has practical limitations for routine use in clinical practice. Management strategies are focused on increasing muscle mass and strength. The present review provides an overview of the diagnosis, pathophysiology, prognostic implications and management strategies available for sarcopenic obesity in cirrhosis. We also discuss the associated condition myosteatosis, the pathological accumulation of fat in skeletal muscle. Much work needs to be done to advance both clinical care and research in this area. Future directions require consensus definitions for sarcopenia, obesity and sarcopenic obesity, an expansion of our understanding of the complex pathogenesis of the muscle-liver-adipose tissue axis in cirrhosis and evidence to support management recommendations for nutrition, exercise and pharmacological therapies.
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.
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) | 0.001 | 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) | 0.001 | 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 it