Cost‐effectiveness evaluation of the <scp>PROPPR</scp> trial transfusion protocols
Bibliographic record
Abstract
BACKGROUND: There have been no prior investigations of the cost effectiveness of transfusion strategies for trauma resuscitation. The Pragmatic, Randomized, Optimal Platelet and Plasma Ratios (PROPPR) study was a Phase III multisite, randomized trial in 680 subjects comparing the efficacy of 1:1:1 transfusion ratios of plasma and platelets to red blood cells with the 1:1:2 ratio. We hypothesized that 1:1:1 transfusion results in an acceptable incremental cost-effectiveness ratio, when estimated using patients' age-specific life expectancy and cost of care during the 30-day PROPPR trial period. STUDY DESIGN AND METHODS: International Classification of Diseases, Ninth Revision codes were prospectively collected, and subjects were matched 1:2 to subjects in the Healthcare Utilization Program State Inpatient Data to estimate cost weights. We used a decision tree analysis, combined with standard costs and estimated years of expected survival to determine the cost effectiveness of the two treatments. RESULTS: The 1:1:1 group had higher overall costs for the blood products but were more likely to achieve hemostasis and decreased hemorrhagic death by 24 hours (p = 0.006). For every 100 patients treated in the 1:1:1 group, eight more achieved hemostasis than in the 1:1:2 group. At 30 days, the total hospital cost per 100 patients was $5.6 million in the 1:1:1 group compared with $5.0 million in the 1:1:2 group. For each 100 patients, the 1:1:1 group had 218.5 more years of life expectancy. This was at a cost of $2994 per year gained. CONCLUSION: The 1:1:1 transfusion ratio in severely injured hemorrhaging trauma patients is a very cost-effective strategy for increasing hemostasis and decreasing trauma deaths.
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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 | 0.019 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".