Thromboelastographic Study of Psychophysiological Stress
Bibliographic record
Abstract
Thromboelastography (TEG) is drawing more attention for clinical and laboratory studies of hemostasis. It has been applied to evaluate the effects of both psychological and physiological stress on whole blood coagulation from the onset of the coagulation cascade through clot formation, to the end with fibrinolysis. We conducted a comprehensive review on the applications of TEG for assessment of different stressors, ranging from physical exercise to emotional situations. The methodology is unique in terms of instrumentation, the methods to activate blood coagulation, the type of blood (citrated vs fresh blood), and study settings (in vitro vs in vivo vs clinical trials). Thromboelastography has most often been used to study the effects of physiological stress. The author's own work and future directions are discussed as well. The review would facilitate future development of TEG for evaluating hemostasis and potential pathological pathways in response to various forms of stress.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".