Effect of Granulocyte Colony-Stimulating Factor on Clinical Pregnancy Outcomes of Recurrent Miscarriage and Recurrent Implantation Failure Cases: A Meta-Analysis
Bibliographic record
Abstract
Objective: This meta-analysis aimed to evaluate the effect of granulocyte colony-stimulating factor (G-CSF) on the treatment of recurrent miscarriage (RM) and recurrent implantation failure (RIF). Methods: Eligible randomized controlled trials (RCTs) and cohort studies were retrieved from the Web of Science, Cochrane, and PubMed databases and evaluated using the Jadad scale or Newcastle-Ottawa Scale. Cochran’s Q test and I 2 statistics were used to assess heterogeneity. The effect sizes for clinical pregnancy and abortion rates of patients were pooled as risk ratios (RRs) and 95% confidence intervals (CI) using RevMan 5.3. Publication bias was assessed using funnel plots. Results: Thirteen studies (nine RCTs and three cohort studies) involving 1262 participants were included. Compared to the control/placebo group, the use of G-CSF significantly improved the clinical pregnancy rate [RRs (95% CI) = 1.73 (1.41, 2.12), p < 0.00001] of RIF patients;Whereas it had no significant impact on their abortion rate [RRs (95% CI) = 1.13 (0.43, 2.95), p = 0.80]. Both subcutaneous and intrauterine injections of G-CSF could improve the clinical pregnancy rate in RIF patients. However, subcutaneous injection showed a tendency to increase the abortion rate [RRs (95% CI) = 1.98 (0.40, 9.87), p = 0.40], whereas intrauterine injection showed a tendency to decrease the abortion rate for RIF patients [RRs (95% CI) = 0.93 (0.24, 3.53), p = 0.11]. In addition, G-CSF use had no significant impact on the clinical pregnancy rate of RIF patients in a South American study [RRs (95% CI) = 1.20 (0.60, 2.38), p = 0.60]. For RM patients, the use of G-CSF showed improved clinical pregnancy rates [RRs (95% CI) = 1.43 (0.76, 2.70), p = 0.27] and lower abortion rates [RRs (95% CI) = 0.80 (0.46, 1.14), p = 0.44] than control/placebo group;However, the difference was not significant. Similar results were observed in the subcutaneous, intrauterine injection, and regions subgroups of RM patients. Conclusions: This meta-analysis confirmed the benefits of G-CSF in improving the clinical pregnancy rate of RIF patients. No conclusive evidence supports the link between G-CSF use and increased abortion rate in RIF patients and clarifies the association of G-CSF use with clinical pregnancy and abortion rates in patients with RM.
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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 | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.075 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".