Prevalence of sarcopenia among patients with hepatocellular carcinoma: A systematic review and meta‑analysis
Bibliographic record
Abstract
Sarcopenia is a common condition in patients with hepatocellular carcinoma (HCC). Sarcopenia affects the prognosis of patients with HCC and reduces their quality of life. However, to date, there has been no systematic review and meta‑analysis to assess the prevalence of sarcopenia in patients with HCC, to the best of our knowledge. PubMed, Embase, Web of Science and the Cochrane Library were comprehensively screened for relevant literature published from March 2001 to June 2022. A random effect analysis was conducted to pool the incidence rates for each study. Subgroup and meta‑regression analyses were used to investigate the latent sources of heterogeneities. The Newcastle‑Ottawa Scale was used to estimate the quality of the included studies. The I2 statistic was used to evaluate heterogeneity between studies. In total, 48 studies encompassing 8,959 patients were included in the meta‑analysis. The results of the present meta‑analysis showed that nearly half (42%) of the patients with HCC had sarcopenia (95% CI, 0.36‑0.48). The morbidity of sarcopenia in studies with a high proportion of males (45%) was higher compared with the morbidity observed in studies with a lower proportion of males (37%). In addition, the incidence rate in younger patients (46%) was found to be higher compared with the incidence rate in older patients (39%). In conclusion, the findings in the present systematic review revealed that a large number of patients with HCC suffer from sarcopenia, indicating the necessity of developing screening and intervention measures to improve the outcome in these patients.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.029 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".