Why have meta‐analyses of randomized controlled trials of the association between non‐white‐blood‐cell‐reduced allogeneic blood transfusion and postoperative infection produced discordant results?
Bibliographic record
Abstract
Intention-to-treat analyses of randomized controlled trials (RCTs) of the association between non-white-blood-cell (WBC)-reduced allogeneic blood transfusion (ABT) and postoperative infection were reported as the reason why meta-analyses of RCTs of this association have produced discordant results. We examined three possible reasons for disagreements between meta-analyses: (i) sources of medical heterogeneity and integration of RCTs despite extreme heterogeneity; (ii) reliance on as-treated (vs. intention-to-treat) comparisons; and (iii) inclusion (or not) of the three most recent RCTs. When nine RCTs reported up to 2002 were combined despite extreme heterogeneity, both intention-to-treat and as-treated comparisons found an association between non-WBC-reduced ABT and postoperative infection [summary odds ratio (OR) = 1.38, 95% confidence interval (CI) 1.03-1.85, P < 0.05; and summary OR = 1.56, 95% CI 1.06-2.31, P < 0.05, respectively]. When 12 RCTs reported up to 2005 were integrated despite extreme heterogeneity, both intention-to-treat and as-treated comparisons found no association of non-WBC-reduced ABT with postoperative infection (summary OR = 1.24, 95% CI 0.98-1.56, P > 0.05; and summary OR = 1.31, 95% CI 0.98-1.75, P > 0.05, respectively). In both analyses, the separate integration of four RCTs transfusing red blood cells (RBCs) or whole blood filtered after storage showed an association between non-WBC-reduced ABT and postoperative infection, whereas the separate integration of six (or nine) RCTs, reported through 2002 or 2005, and transfusing prestorage-filtered RBCs showed no association, whether intention-to-treat or as-treated comparisons were used. Thus, the published meta-analyses have produced discordant results because they did (or did not) investigate medical sources of heterogeneity and did (or did not) include the most recent RCTs. Intention-to-treat and as-treated comparisons produced concordant results.
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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 | 0.292 | 0.574 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".