Massive Blood Transfusion for Trauma Score to Predict Massive Blood Transfusion in Trauma.
| Autor: | Akaraborworn O; Division of Trauma and Critical Care, Department of Surgery, Faculty of Medicine, Prince of Songkla University, Hat Yai, Thailand., Siribumrungwong B; Division of Vascular and Endovascular Surgery, Department of Surgery, Faculty of Medicine, Thammasat University Hospital, Khlong Nueng, Pathum Thani, Thailand., Sangthong B; Division of Trauma and Critical Care, Department of Surgery, Faculty of Medicine, Prince of Songkla University, Hat Yai, Thailand., Thongkhao K; Division of Trauma and Critical Care, Department of Surgery, Faculty of Medicine, Prince of Songkla University, Hat Yai, Thailand. |
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| Jazyk: | angličtina |
| Zdroj: | Critical care research and practice [Crit Care Res Pract] 2021 Feb 24; Vol. 2021, pp. 3165390. Date of Electronic Publication: 2021 Feb 24 (Print Publication: 2021). |
| DOI: | 10.1155/2021/3165390 |
| Abstrakt: | Background: Massive blood loss is the most common cause of immediate death in trauma. A massive blood transfusion (MBT) score is a prediction tool to activate blood banks to prepare blood products. The previously published scoring systems were mostly developed from settings that had mature prehospital systems which may lead to a failure to validate in settings with immature prehospital systems. This research aimed to develop a massive blood transfusion for trauma (MBTT) score that is able to predict MBT in settings that have immature prehospital care. Methods: This study was a retrospective cohort that collected data from trauma patients who met the trauma team activation criteria. The predicting parameters included in the analysis were retrieved from the history, physical examination, and initial laboratory results. The significant parameters from a multivariable analysis were used to develop a clinical scoring system. The discrimination was evaluated by the area under a receiver operating characteristic (AuROC) curve. The calibration was demonstrated with Hosmer-Lemeshow goodness of fit, and an internal validation was done. Results: Among 867 patients, 102 (11.8%) patients received MBT. Four factors were associated with MBT: a score of 3 for age ≥60 years; 2.5 for base excess ≤-10 mEq/L; 2 for lactate >4 mmol/L; and 1 for heart rate ≥105 /min. The AuROC was 0.85 (95% CI: 0.78-0.91). At the cut point of ≥4, the positive likelihood ratio of the score was 6.72 (95% CI: 4.7-9.6, p < 0.001), the sensitivity was 63.6%, and the specificity was 90.5%. Internal validation with bootstrap replications had an AuROC of 0.83 (95% CI: 0.75-0.91). Conclusions: The MBTT score has good discrimination to predict MBT with simple and rapidly obtainable parameters. Competing Interests: The authors declare that there are no conflicts of interest related to this research. (Copyright © 2021 Osaree Akaraborworn et al.) |
| Databáze: | MEDLINE |
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