Different desensitization therapeutic effects on patients with ABO-incompatible liver transplantation: a network-meta analysis
Bibliographic record
Abstract
Objective To compare the efficacy of three different desensitization therapies in ABO-incompatible liver transplantation (ABO-ILT) by meta-analysis. Methods The recipients were divided into three groups according to the different desensitization protocal: (rituximab+ TPE/PP) group, rituximab group; (rituximab+ IVIG) group, ABO-compatible liver transplantation (ABO-CLT) group. Different incidence rate of events were compared. Studies published during January 2003 and May 20, 2018 were electronically retrieved from PubMed, EMbase, MEDLINE, Cochrane Library, Scopus, CNKI, WanFang Data, VIP. Newcastle-Ottawa Scale was used to evaluated the the quality of literature. Meta-analysis was performed to calculate OR and 95% confidence interval by using the random effect model analyses with WinBUGS 14.3 software. Statistical significance was approved when P<0.05. Results Nine studies were selected. No statistical significance was observed in the postoperative 1- and 3-year survival rate of the recipients, incidence of antibody-mediated rejection (AMR), incidence of acute cellular rejection (ACR), incidence of postoperative diffuse intrahepatic biliary stricture and non-intrahepatic biliary tract complications among 4 groups (P all>0.05). The SUCRA value of ACR of (rituximab+ TPE/PP) group, rituximab group, (rituximab+ IVIG) group were 0.3562, 0.7767 and 0.7092, which were all higher than ABO-CLT group (P all>0.05). No small sample effect was observerd among the above desensitization therapies. Conclusions The desensitization therapeutic effects between rituximab combined with TPE/PP and rituximab combined with IVIG was similar. Rituximab combined with IVIG can be perforned for emergent ABO-ILT. Rituximab monotherapy is proper when there is sufficient time and economy burden. Key words: ABO-incompatible liver transplantation; Rituximab; Desensitization therapy; Neworkt-meta analysis
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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 | 0.016 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.052 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".