The effects of plasma exchange in patients with ANCA-associated vasculitis: an updated systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To assess the effects of plasma exchange on important outcomes in anti-neutrophil cytoplasm antibody (ANCA)-associated vasculitis (AAV). DESIGN: Systematic review and meta-analysis of randomised controlled trials. ELIGIBILITY CRITERIA: Randomised controlled trials investigating effects of plasma exchange in patients with AAV or pauci-immune rapidly progressive glomerulonephritis and at least 12 months' follow-up. INFORMATION SOURCES: Prior systematic reviews, updated by searching Medline, Embase, and CENTRAL to July 2020. RISK OF BIAS: Reviewers independently identified studies, extracted data, and assessed the risk of bias using the Cochrane Risk of Bias tool. SYNTHESIS OF RESULTS: Meta-analyses were conducted using random effects models to calculate risk ratios and 95% confidence intervals. Quality of evidence was summarised in accordance with GRADE methods. Outcomes were assessed after at least12 months of follow-up and included all-cause mortality, end stage kidney disease (ESKD), serious infections, disease relapse, serious adverse events, and quality of life. RESULTS: Nine trials including 1060 participants met eligibility criteria. There were no important effects of plasma exchange on all-cause mortality (relative risk 0.90 (95% CI 0.64 to 1.27), moderate certainty). Data from seven trials including 999 participants that reported ESKD demonstrated that plasma exchange reduced the risk of ESKD at 12 months (relative risk 0.62 (0.39 to 0.98), moderate certainty) with no evidence of subgroup effects. Data from four trials including 908 participants showed that plasma exchange increased the risk of serious infections at 12 months (relative risk 1.27 (1.08 to 1.49), moderate certainty). The effects of plasma exchange on other outcomes were uncertain or considered unimportant to patients. LIMITATIONS OF EVIDENCE: There is a relative sparsity of events, and treatment effect estimates are therefore imprecise. Subgroup effects at the participant level could not be evaluated. INTERPRETATION: For the treatment of AAV, plasma exchange has no important effect on mortality, reduces the 12 month risk of ESKD, but increases the risk of serious infections. FUNDING: No funding was received. REGISTRATION: This is an update of a previously unregistered systematic review and meta-analysis published in 2014.
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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 | 0.018 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.041 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".