Using rotational thromboelastometry clot firmness at 5 minutes (ROTEM <sup>®</sup> EXTEM A5) to predict massive transfusion and in‐hospital mortality in trauma: a retrospective analysis of 1146 patients
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Bibliographic record
Abstract
are increasingly used to guide transfusion of blood products. The EXTEM assay maximum clot firmness (MCF) is a ROTEM measure available after 25-29 min used to guide early decisions. EXTEM A10, the clot firmness at 10 min, is an accepted early surrogate, but investigators differ on whether A5, the clot firmness at 5 min, is acceptable. We re-examined this in a retrospective observational analysis of 1146 trauma patients in one centre who had ROTEM data recorded. A5 and A10 both correlated well with maximum clot firmness, with Pearson coefficients of r = 0.92 and r = 0.96, respectively. The correlations of A5, A10 and maximum clot firmness with requirement for massive transfusion were all similarly high, with c-stats of 0.87, 0.89 and 0.90, respectively. The correlations with mortality were also similar but weaker, with c-stats of 0.67, 0.69 and 0.69, respectively. Using a previously validated cut-off of A5 < 35 mm to predict massive transfusion gave a sensitivity of 95%, specificity 83%, positive predictive value 9.3% and negative predictive value 100%. Using a value of A5 < 29 mm, for a pragmatic positive predictive value of 20%, gave a sensitivity of 67%, specificity 95% and negative predictive value 99%. Whether aiming for a high sensitivity or a strong predictive value, A5 was non-inferior to A10 and actually missed fewer cases needing massive transfusion. A5 has similar utility to both A10 and maximum clot firmness as an early measure of clot firmness, and a low A5 value is strongly predictive of the need for massive transfusion.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.000 | 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 it