Restrictive compared with liberal red cell transfusion strategies in cardiac surgery: a meta-analysis
Bibliographic record
Abstract
AIMS: To determine whether a restrictive strategy of red blood cell (RBC) transfusion at lower haemoglobin concentrations is inferior to a liberal strategy of RBC transfusion at higher haemoglobin concentrations in patients undergoing cardiac surgery. METHODS AND RESULTS: We conducted a systematic review, meta-analysis, and trial sequential analysis of randomized controlled trials of the effect of restrictive and liberal RBC transfusion strategies on mortality within 30 days of surgery as the primary outcome. Secondary outcomes were those potentially resulting from anaemia-induced tissue hypoxia and transfusion outcomes. We searched the electronic databases MEDLINE, EMBASE, and the Cochrane Library until 17 November 2017. Thirteen trials were included. The risk ratio (RR) of mortality derived from 4545 patients assigned to a restrictive strategy when compared with 4547 transfused according to a liberal strategy was 0.96 [95% confidence interval (CI) 0.76-1.21, I2 = 0]. A restrictive strategy did not have a statistically significant effect on the risk of myocardial infarction (RR 1.01, 95% CI 0.81-1.26; I2=0), stroke (RR 0.93, 95% CI 0.68-1.27, I2 = 0), renal failure (RR 0.96, 95% CI 0.76-1.20, I2 = 0), or infection (RR 1.12, 95% CI 0.98-1.29, I2 = 0). Subgroup analysis of adult and paediatric trials did not show a significant interaction. At approximately 70% of the critical information size, the meta-analysis of mortality crossed the futility boundary for inferiority of the restrictive strategy. CONCLUSION: The current evidence does not support the notion that restrictive RBC transfusion strategies are inferior to liberal RBC strategies in patients undergoing cardiac surgery.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.044 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".