A Retrospective Study Comparing the Effect of Conventional Coagulation Parameters Vs. Thromboelastography-Guided Blood Product Utilization in Patients With Major Gastrointestinal Bleeding
Bibliographic record
Abstract
Background: The use of thromboelastography (TEG) has demonstrated decreased blood product utilization in patients with specific etiologies of major gastrointestinal bleeding (GIB), such as variceal and non-variceal bleeding in cirrhosis patients; however, in a non-cirrhosis patient with GIB, there is far less evidence in the literature. Our retrospective study compares the effect of TEG-guided blood product utilization in patients with major GIB with all etiologies, including cirrhosis, admitted to medical intensive care unit (MICU). Methods: A retrospective chart review was conducted on patients admitted to the MICU of a tertiary academic medical center diagnosed with GIB using ICD-9/10 codes from 2014 to 2018. A total of 1,889 patients were identified, and validation criteria such as "GI or hepatology consult note", type and screen, pantoprazole, or octreotide drip" were used, which resulted in 997 patients, out of which 369 had a diagnosis of cirrhosis. Propensity score matching was done for baseline variables (age, sex, and race), ICU length of stay, hospital length of stay, ventilator days, and vasopressor use. As a result, 88 patients were included in the final analysis, with 44 in TEG and 44 in non-TEG group. A sub-group analysis was done in 46 patients with cirrhosis, 23 in TEG group and 23 in non-TEG group after propensity score matching. Results: There was significantly higher total blood volume (4,207 mL vs. 2,568 mL, P = 0.04) in the TEG group as compared to the non-TEG group, including total volume of cryoprecipitate (80 mL vs. 55 mL, P = 0.03) and total volume of platelet (543 mL vs. 327 mL, P = 0.03). In the cirrhosis sub-group, there was no significant difference in the amount of blood products transfused between the two groups. Conclusion: This study revealed that TEG is not superior to conventional coagulation parameters in limiting the volume of blood product transfusion in major GIB patients in ICU settings.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".