Aprotinin and the risk of death and renal dysfunction in patients undergoing cardiac surgery: a meta‐analysis of epidemiologic studies
Bibliographic record
Abstract
PURPOSE: Observational studies have reported conflicting results regarding aprotinin's risk of renal dysfunction and death. A meta-analysis was conducted to summarize results and explain variation of published epidemiologic studies on risks of renal dysfunction and death associated with aprotinin. METHODS: MEDLINE and EMBASE were systematically searched for non-experimental studies that reported risk of renal dysfunction or death with aprotinin use during cardiac surgery in adults. Random-effects meta-analyses were used to pool results across studies for each outcome. Stratified and meta-regression analyses were used to identify sources of heterogeneity. RESULTS: Eleven relevant studies were identified and included in the analysis, including 10 that reported renal dysfunction and seven that reported death. Aprotinin was associated with renal dysfunction (risk ratio (RR), 1.42; 95%CI 1.13-1.79) and long-term mortality (hazard ratio (HR) 1.22; 95%CI 1.08-1.39). Pooled estimates were lower for short-term mortality (RR 1.16; 95%CI 0.84-1.58) and renal failure requiring dialysis (RR 1.17; 95%CI 0.99-1.38). Cardiopulmonary bypass (CPB) time, which may be on the causal pathway, was a significant source of heterogeneity, with a 29% increased risk of renal dysfunction for every 10 minute increase in CPB time (p = 0.03). CONCLUSIONS: Despite some studies that reported no association between aprotinin and renal outcomes during cardiac surgery, the totality of epidemiologic evidence indicates an increased risk that cannot be fully explained by need for transfused red blood cells (RBCs). Epidemiologic studies also suggest an increased risk of long-term mortality associated with aprotinin as compared to various comparators used in these studies, although residual confounding cannot be ruled out.
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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 | 0.021 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.064 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".