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Record W2037595506 · doi:10.1186/1757-7241-21-29

Thrombelastography (TEG®): practical considerations on its clinical use in trauma resuscitation

2013· review· en· W2037595506 on OpenAlexaff
Luís Teodoro da Luz, Bartolomeu Nascimento, Sandro Rizoli

Bibliographic record

VenueScandinavian Journal of Trauma Resuscitation and Emergency Medicine · 2013
Typereview
Languageen
FieldMedicine
TopicTrauma, Hemostasis, Coagulopathy, Resuscitation
Canadian institutionsSt. Michael's HospitalHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsThrombelastographyCoagulopathyMedicineCryoprecipitateFibrinolysisThromboelastometryHyperfibrinolysisResuscitationIntensive care medicineThromboelastographyAnesthesiaFibrinogenSurgeryPlateletInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Thrombelastography is a laboratorial test that measures viscoelastic changes of the entire clotting process. There is growing interest in its clinical use in trauma resuscitation, particularly for managing acute coagulopathy of trauma and assisting decision making concerning transfusion. This review focuses on the clinical use of thrombelastography in trauma, with practical points to consider on its use in civilian and military settings. METHODS: A search in the literature using the terms "thrombelastography AND trauma" was performed in PUBMED database. We focused the review on the main clinical aspects of this viscoelastic method in diagnosing and treating patients with acute coagulopathy of trauma during initial resuscitation. RESULTS: Thrombelastography is not a substitute for conventional laboratorial tests such as INR and aPTT but offers additional information and may guide blood transfusion. Thrombelastography can be used as a point of care test but requires multiple daily calibrations, should be performed by trained personnel and its technique requires standardization. While useful partial results may be available in minutes, the whole test may take as long as other conventional tests. The most important data provided by thrombelastography are clot strength and fibrinolysis. Clot strength measure can establish whether the bleeding is due to coagulopathy or not, and is the key information in thrombelastography-based transfusion algorithms. Thrombelastography is among the few tests that diagnose and quantify fibrinolysis and thus guide the use of anti-fibrinolytic drugs and blood products such as cryoprecipitate and fibrinogen concentrate. It may also diagnose platelet dysfunction and hypercoagulability and potentially prevent inappropriate transfusions of hemostatic blood products to non-coagulopathic patients. CONCLUSIONS: Thrombelastography has characteristics of an ideal coagulation test for use in early trauma resuscitation. It has limitations, but may prove useful as an additional test. Future studies should evaluate its potential to guide blood transfusion and the understanding of the mechanisms of trauma coagulopathy.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.346
GPT teacher head0.482
Teacher spread0.136 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations155
Published2013
Admission routes1
Has abstractyes

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