Role of granulocyte colony stimulating factor in the treatment of cirrhosis of liver: a systematic review
Bibliographic record
Abstract
Objective We performed a systematic review to analyze the benefits of and risk factors associated with granulocyte colony stimulating factor (GCSF) in patients with liver cirrhosis. Methods PubMed, Scopus, and Embase were searched for randomized controlled trials and case–control studies that compared the use of GCSF with another treatment or control group. The Jadad and Newcastle–Ottawa scales were used to assess the risk of bias in the included studies. The primary outcome studied was mortality; and the secondary outcomes were the disease severity score, liver transplantation criteria, complications, CD34 + cell count, adverse events, and health-related quality of life (HRQOL). PROSPERO registration number CRD42023416014. Results The initial search yielded 2,235 studies, of which seven studies of 670 patients with liver cirrhosis were included. Multiple cycles of GCSF significantly improved the survival rate, disease severity score, CD34 + cell count, and HRQOL; and significantly reduced the incidences of liver transplantation, ascites, infection, and hepatic encephalopathy. Fatigue and backache were the most commonly reported adverse events. Conclusion GCSF significantly improves the survival rate and disease severity scores, and reduces the incidence of complications in patients with liver cirrhosis. The administration of GCSF is likely to be effective in patients awaiting liver transplantation.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".