USE OF ROTATIONAL THROMBOELASTOMETRY FOR OPTIMAL MANAGEMENT OF EARLY RESUSCITATION OF BLEEDING TRAUMA PATIENTS
Bibliographic record
Abstract
Early trauma-induced coagulopathy (TIC) is associated with uncontrollable bleeding, high transfusion requirements and mortality. Current management strategies of coagulopathic bleeding trauma patients are either guided by untimely laboratory tests (goal-directed) or blind transfusion protocols according to pre-established formulas (damage-control, 1:1:1). Both strategies have significant limitations that may account for the poor outcome of many patients. Viscoelastometric tests such as rotational thromboelastometry (ROTEM) are emerging technologies with potential to revolutionize resuscitation of rapidly bleeding trauma patients. This project aims to investigate the role of ROTEM in early trauma resuscitation, including TIC diagnosis, guiding blood transfusion and predicting 24h mortality. The overarching hypothesis is that ROTEM parameters measured immediately upon hospital admission, may predict increased transfusion requirements, including massive transfusion (MT), and 24h mortality, and thus could guide blood and blood product transfusions. In order to explore this hypothesis, a series of approaches have been performed. A systematic review and international consensus conference with a panel of renowned experts in trauma, critical care, hematology, and surgery were done. They established the ROTEM parameters and values used for the diagnosis of TIC, guidance of blood transfusion and prediction of 24h mortality. Next, patient data from two major Canadian trauma centers were obtained to develop and validate prediction models for assessing the risk of requiring blood and blood product transfusion (red blood cells (RBC), plasma, cryoprecipitate and platelets), massive transfusion (MT) and 24h mortality using ROTEM and readily available clinical variables. The systematic review and the consensus conference indicated that low clot amplitude was associated with transfusion requirements, MT and 24h mortality but exact ROTEM parameters values could not be determined due to equipment limitations (i.e. high coefficient of variability) and poor understanding of their physiologic meaning (i.e. meaning of hyper coagulability parameters). Similarly, patient data analysis demonstrated that low clot amplitude, both in extrinsic (EXTEM) and fibrinogen pathways (FIBTEM), along with clinical parameters, accurately predicted the need for plasma and cryoprecipitate transfusion, MT, and 24h mortality. ROTEM however, did not predict RBC or platelet transfusion. The results of our studies indicate that ROTEM may assist in the early diagnosis and guide timely management of bleeding coagulopathic injured patients. While our findings warrant future evaluations we speculate that ROTEM can guide blood transfusions, reduce inappropriate blood utilization and improve patient outcome (reduce mortality).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".