1. Fibrinogen level on admission is a predictor for massive transfusion in patients with severe blunt trauma: Analyses of a retrospective multicentre observational study.
- Author
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Nakamura Y, Ishikura H, Kushimoto S, Kiyomi F, Kato H, Sasaki J, Ogura H, Matsuoka T, Uejima T, Morimura N, Hayakawa M, Hagiwara A, Takeda M, Kaneko N, Saitoh D, Kudo D, Maekawa K, Kanemura T, Shibusawa T, Hagihara Y, Furugori S, Shiraishi A, Murata K, Mayama G, Yaguchi A, Kim S, Takasu O, and Nishiyama K
- Subjects
- Adult, Aged, Biomarkers metabolism, Blood Pressure, Female, Hemorrhage etiology, Hemorrhage physiopathology, Humans, Injury Severity Score, Japan, Logistic Models, Male, Middle Aged, Predictive Value of Tests, Retrospective Studies, Wounds, Nonpenetrating complications, Wounds, Nonpenetrating metabolism, Wounds, Nonpenetrating physiopathology, Blood Transfusion methods, Blood Transfusion statistics & numerical data, Critical Care, Fibrinogen metabolism, Hemorrhage therapy, Patient Admission, Wounds, Nonpenetrating therapy
- Abstract
Introduction: In the early phase of trauma, fibrinogen (Fbg) plays an important role in clot formation. However, to the best of our knowledge, few studies have analysed methods of predicting the need for massive transfusion (MT) based on Fbg levels using multiple logistic regression. Therefore, the present study aimed to evaluate whether Fbg levels on admission can be used to predict the need for MT in patients with trauma., Methods: We conducted a retrospective multicentre observational study. Patients with blunt trauma with ISS ≥16 who were admitted to 15 tertiary emergency and critical care centres in Japan participating in the J-OCTET were enrolled in the present study. MT was defined as the transfusion of packed red blood cells (PRBC) ≥10 units or death caused by bleeding within 24h after admission. Patients were divided into non-MT and MT groups. Multiple logistic-regression analysis was used to assess the predictive value of the variables age, sex, vital signs, Glasgow Coma Scale (GCS) score, and Fbg levels for MT. We also evaluated the discrimination threshold of MT prediction via receiver operating characteristic curve (ROC) analysis for each variable., Results: Higher heart rate (HR; per 10 beats per minutes [bpm]), systolic blood pressure (SBP; per 10mm Hg), GCS, and Fbg levels (per 10mg/dL) were independent predictors of MT (odds ratio [OR] 1.480, 95% confidence interval [CI] 1.326-1.668; OR 0.851, 95% CI 0.789-0.914; OR 0.907, 95% CI 0.855-0.962; and OR 0.931, 95% CI 0.898-0.963, respectively). The optimal cut-off values for HR, SBP, GCS, and Fbg levels were ≥100 bpm (sensitivity 62.4%, specificity 79.8%), ≤120mm Hg (sensitivity 61.5%, specificity 70.5%), ≤12 points (sensitivity 63.3%, specificity 63.6%), and ≤190mg/dL (sensitivity 55.1%, specificity 78.6%), respectively., Conclusions: Our findings suggest that vital signs, GCS, and decreased Fbg levels can be regarded as predictors of MT. Therefore, future studies should consider Fbg levels when devising models for the prediction of MT., (Copyright © 2017 Elsevier Ltd. All rights reserved.)
- Published
- 2017
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