Effects of different fibrinogen concentrations on blood loss and coagulation parameters in a pig model of coagulopathy with blunt liver injury
Bibliographic record
Abstract
INTRODUCTION: The early application of fibrinogen could potentially reverse haemodilution-induced coagulopathy, although the impact of varying concentrations of fibrinogen to reverse dilutional coagulopathy has not been studied in vivo. We postulated that fibrinogen concentration is correlated with blood loss in a pig model of coagulopathy with blunt liver injury. METHODS: Coagulopathy was induced in 18 anaesthetized pigs (32 +/- 1.6 kg body weight) by replacing 80% of blood volume with hydroxyethylstarch 130/0.4 and Ringer's lactated solution, and re-transfusion of erythrocytes. Animals were randomly assigned to receive either 70 mg kg-1 (F-70) or 200 mg kg-1 (F-200) fibrinogen or placebo before inducing blunt liver injury using a force of 225 +/- 26 Newton. Haemodynamics, coagulation parameters and blood loss were monitored for 2 hours. After death, histological examination of internal organs was performed to assess the presence of emboli and the equality of liver injury. RESULTS: Plasma dilution caused severe coagulopathy. Measured by thromboelastography fibrinogen restored coagulation dose-dependently. Total blood loss was significantly lower and survival better in both fibrinogen groups as compared to controls (P < 0.05). Between the F-70 (1317 +/- 113 ml) and the F-200 group (1155 +/- 232 ml) no significant difference in total blood loss could be observed, despite improved coagulation parameters in the F-200 group (P < 0.05). Microscopy revealed even injury pattern and no (micro) thrombi for either group. CONCLUSIONS: Restoring fibrinogen with 70 or 200 mg kg-1 after severe dilutional coagulopathy safely improved coagulation and attenuated blood loss after experimental blunt liver trauma. The higher dosage of fibrinogen was not associated with a further reduction in blood loss.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".