Optimum Accuracy of Massive Transfusion Protocol Activation: The Clinician’s View
Bibliographic record
Abstract
Background Massive transfusion protocols (MTP) aid in the efficient delivery of blood components to rapidly exsanguinating patients. Unfortunately, clinical gestalt and currently available clinical scoring systems lack the optimal accuracy to prevent blood product wastage (through over-activation), as well as individual patient morbidity and mortality (through under-activation). In order to help refine the MTP activation criteria and protocols, we surveyed clinicians on acceptable over- and under-activation rates for massive transfusions. Methods We surveyed Canadian content experts in their respective fields, using a snowball survey technique. Respondents were categorized into two groups: Group 1 was comprised of trauma and acute care specialists (TACS), while Group 2 was comprised of clinical and laboratory medicine specialists (CLMS). Between-group differences were examined using Fisher's exact test and the likelihood ratio. Statistical significance was set at p < 0.05. Results We received responses from 35 clinicians in the TACS group and 10 clinicians in the CLMS group. About half (45.7%) of respondents in the TACS group considered an MTP overactivation rate of 5% - 10% acceptable (vs. 60% of the CLMS group; not significant (NS)). Approximately one-third (34.2%) of the respondents in the TACS group considered an MTP under-activation rate of less than 5% acceptable, whereas the majority (60%) of respondents in the CLMS group considered an under-activation rate of less than 5% acceptable (NS). A significantly greater proportion of respondents in the TACS group felt that an anticipated need for > 20 units of packed red blood cells within the next 24 hours was an acceptable criterion for MTP activation. Respondents in the CLMS group were more likely to consider "poor communication" as a reason for blood component wastage. Conclusion Similarities in acceptable MTP over- and under-activation rates were noted across specialties. Collaboration between involved parties is necessary for MTP protocol development to improve patient outcomes and reduce blood wastage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".