The effect of blood storage duration on in‐hospital mortality: a randomized controlled pilot feasibility trial
Bibliographic record
Abstract
BACKGROUND: Whether the duration of storage of blood has an impact on patient outcomes remains controversial. The objective was to determine feasibility of a comparative effectiveness trial to evaluate duration of storage of blood before transfusion on in-hospital mortality. STUDY DESIGN AND METHODS: A single-center randomized controlled trial was performed at an acute care hospital in Canada between June and December 2010, involving consecutive hospitalized patients needing blood transfusion. Patients (n=910) were randomly assigned in a 1:2 ratio to receive freshest available versus standard-issue (oldest available) blood. Four feasibility criteria were measured: proportion of eligible patients randomized, contrast in age of blood between treatment groups, real-time data acquisition, and trial impact on blood outdating. In-hospital mortality was also reported. RESULTS: A total of 1075 of 1129 patients (95.2%) were eligible and 910 of 1075 (84.7%) were randomized: 309 received freshest available blood (1157 units), and 601 received standard-age blood (2369 units). Contrast in mean age of the oldest blood transfused between groups was 14.6 days: 12.0 (standard deviation [SD], 6.8) days in the fresh arm and 26.6 (SD, 7.8) days in the standard arm. Weekly recruitment and event reporting were achieved for all patients. The blood outdate rate was 0.10%. In-hospital mortality was 10.5%: 35 deaths (11.3%) in the fresh arm and 61 deaths (10.1%) in the standard arm (odds ratio, 1.13; 95% confidence interval [CI], 0.73, 1.76). CONCLUSION: It is feasible to conduct a large comparative effectiveness trial comparing the effect of freshest available versus standard-issue blood on in-hospital mortality. The wide CI around the estimate for in-hospital mortality supports the need for a large trial.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".