TEG Lysis Shutdown Represents Coagulopathy in Bleeding Trauma Patients: Analysis of the PROPPR Cohort
Bibliographic record
Abstract
BACKGROUND: Thrombelastography (TEG) fibrinolysis shutdown after trauma is associated with increased mortality due to hypercoagulability-associated organ failure. However, a lack of mechanistic data has precluded the development of novel interventions to treat shutdown. OBJECTIVES: To define the pathophysiology of TEG shutdown in severely injured, bleeding patients through secondary analysis of the PROPPR trial. METHODS: Fibrinolysis was characterized in PROPPR subjects using admission TEG lysis at 30 min (LY30) or plasmin-antiplasmin (PAP) levels. LY30 categories were low (<0.9%), moderate (0.9-2.9%), or high (≥ 3%). PAP was classified as low (<1,500 μg/L), moderate (1,500-20,000 μg/L), or high (>20,000 μg/L). Demographics, outcomes, admission TEG values, platelet count and function, standard coagulation tests, and coagulation proteins were compared. RESULTS: Five hundred forty-seven patients had TEG data and 549 patients had PAP data available. Low LY30 was associated with reduced platelet count and aggregation, poorer TEG clot formation, prolonged clotting times, and reduced fibrinogen and alpha2 antiplasmin. Compared to moderate PAP, low PAP subjects had similar platelet parameters, TEG values, fibrinogen, and alpha2 antiplasmin, but reduced tPA, and elevated PAI-1. D-Dimer values increased as PAP increased, however patients with low LY30 had elevated D-Dimer compared with moderate LY30 patients. Most low LY30 deaths were due to TBI (45%) and hemorrhage (42%) versus one of each cause (TBI, hemorrhage, MOF) in low PAP patients. CONCLUSIONS: Low TEG LY30 does not reflect shutdown of enzymatic fibrinolysis with hypercoagulability, but rather a coagulopathic state of moderate fibrinolysis with fibrinogen consumption and platelet dysfunction that is associated with poor outcomes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".