Clinical impact of red cell storage duration: an individual patient data meta-analysis
Bibliographic record
Abstract
• In an individual patient data meta analysis (n=33,549) there was no survival benefit from transfusing fresher compared to older RBC units • Findings support current blood inventory management policies and are applicable to most hospitalized adults Randomized trials reported no benefit from transfusion of red blood cell (RBC) units stored for shorter durations compared to standard care. However, there was insufficient evidence to exclude harms at extremes of storage age or explore subgroup differences. We therefore performed an individual patient data meta-analysis to determine the effect of fresher vs. older RBC transfusion on 28-day mortality in hospitalized adults. Individual patient data was sought from clinical trials that randomized more than 1000 adult patients. For the meta-analysis, we used a logistic regression model with a trial-specific fixed effect. Four studies provided individual data from 33,549 patients enrolled from March 2009 through December 2016 from 12 countries. After exclusions, 32,959 (98.2%) patients were included in the analysis. Patients received a median (IQR) of 2 (1 – 4) RBC units with a storage duration of 10 (7 – 15) days in the fresh and 23 (16 – 30) days in the older group. Death occurred in 1,446 of 12,236 patients (11.8%) in the fresher and 1,984 of 20,572 patients (9.6%) in the older group (odds ratio 1.06; 95% CI 0.98 to 1.14; p =0.124). No significant subgroup differences were identified. We found an association between receiving one and two or more RBCs ≤7 days and higher mortality (odds ratio 1.18, 95%CI 1.02 to 1.35; p =0.024 and 1.17, 95% CI 1.04 to 1.32; p =0.015, respectively), but not with any RBC ≥35 days. Adjusted analyses confirmed these findings. Our findings support current blood inventory management policies and are applicable to most hospitalized adults. ClinicalTrials.gov: NCT05482737
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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 | 0.017 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.068 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".