Normal range values for thromboelastography in healthy adult volunteers
Bibliographic record
Abstract
Thromboelastography (TEG) provides a functional evaluation of coagulation. It has characteristics of an ideal coagulation test for trauma, but is not frequently used, partially due to lack of both standardized techniques and normal values. We determined normal values for our population, compared them to those of the manufacturer and evaluated the effect of gender, age, blood type, and ethnicity. The technique was standardized using citrated blood, kaolin and was performed on a Haemoscope 5000 device. Volunteers were interviewed and excluded if pregnant, on anticoagulants or having a bleeding disorder. The TEG parameters analyzed were R, K, alpha, MA, LY30, and coagulation index. All volunteers outside the manufacturer's normal range underwent extensive coagulation investigations. Reference ranges for 95% for 118 healthy volunteers were R: 3.8-9.8 min, K: 0.7-3.4 min, alpha: 47.8-77.7 degrees, MA: 49.7-72.7 mm, LY30: -2.3-5.77%, coagulation index: -5.1-3.6. Most values were significantly different from those of the manufacturer, which would have diagnosed coagulopathy in 10 volunteers, for whom additional investigation revealed no disease (81% specificity). Healthy women were significantly more hypercoagulable than men. Aging was not associated with hypercoagulability and East Asian ethnicity was not with hypocoagulability. In our population, the manufacturer's normal values for citrated blood-kaolin had a specificity of 81% and would incorrectly identify 8.5% of the healthy volunteers as coagulopathic. This study supports the manufacturer's recommendation that each institution should determine its own normal values before adopting TEG, a procedure which may be impractical. Consideration should be given to a multi-institutional study to establish wide standard values for TEG.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".