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比较两种不同凝血算法在严重创伤患者中异体血液制品和凝血因子使用方面的效果:一项回顾性、多中心、观察性研究。

Comparison of two different coagulation algorithms on the use of allogenic blood products and coagulation factors in severely injured trauma patients: a retrospective, multicentre, observational study.

机构信息

Institute of Anaesthesiology, University and University Hospital Zürich, Raemistrasse 100, 8091, Zürich, Switzerland.

Department of Anaesthesiology and Intensive Care, Cantonal Hospital Lucerne, Spitalstrasse 16, 6000, Luzern, Switzerland.

出版信息

Scand J Trauma Resusc Emerg Med. 2018 Jan 8;26(1):4. doi: 10.1186/s13049-017-0463-0.

DOI:10.1186/s13049-017-0463-0
PMID:29310686
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5759800/
Abstract

BACKGROUND

At the University Hospital Zurich (USZ) and the Cantonal Hospital of Lucerne (LUKS) an individualized goal-directed coagulation and transfusion algorithm was introduced and implemented before 2012 (Coagulation algorithm of the USZ: USZ-Alg; of the LUKS: LUKS-Alg). Main differences between both algorithms are: 1) A target haematocrit-range of 0.21-0.24 (USZ-Alg) vs. a lower haematocrit limit only (LUKS-Alg). 2) Blind coagulation-package in selected cases (LUKS-Alg only). 3) Factor XIII substitution is considered earlier according to the USZ-Alg. The Aim of this study was to analyse the impact of two different coagulation algorithms on the administration of allogeneic blood products, coagulation factors, the frequency of point of care measurements and haemoglobin level during resuscitation in trauma patients.

METHODS

This retrospective, multicentre, observational study included all adult trauma patients with an injury severity score (ISS) ≥ 16 primarily admitted to the USZ or the LUKS in the period of 2012 to 2014. Referred patients and patients with missing/incomplete records of the initial treatment at the emergency department (ED) were excluded. Two propensity score matched groups were created using a non-parsimonious logistic regression to account for potential differences in patient and trauma epidemiology.

RESULTS

A total of 632 patients meeting the inclusion criteria were admitted to the two hospitals: 428 to the USZ and 204 to the LUKS. Two Propensity score matched groups (n = 172 per group) were created. Treatment with USZ-Alg compared with LUKS-Alg resulted in a lower number of patients receiving RBC transfusion (11.6% vs. 29.7%, OR 3.2, 95% CI 1.8-5.7, p < 0.001) and lower amount of RBC transfusion (0.5 SD 1.9 vs. 1.5 SD 3.9, p < 0.001). The different treatment algorithms resulted in lower mean haemoglobin levels in the USZ during resuscitation (8.0 SD 1.7 vs. 9.4 SD 1.8 g/dl, p < 0.001) and at admission to the ICU (8.3 SD 1.2 vs. 10.6 SD 1.9 g/dl, p < 0.001. Blood gas analyses to monitor treatment and haematocrit were made more frequently in the USZ (1.4 SD 0.8 vs. 1.0 SD 0.7 measurements per hour, p = 0.004).

CONCLUSION

A goal-directed coagulation algorithm including a target haematocrit-range including frequent and repeated haematocrit measurement may lead to less transfusion of RBC compared to only a lower haematocrit limit, when treating severely traumatized patients.

摘要

背景

在苏黎世大学医院(USZ)和卢塞恩州立医院(LUKS),在 2012 年之前引入并实施了个体化目标导向的凝血和输血算法(USZ 的凝血算法:USZ-Alg;LUKS 的凝血算法:LUKS-Alg)。两个算法之间的主要区别在于:1)目标血细胞比容范围为 0.21-0.24(USZ-Alg)与仅较低的血细胞比容下限(LUKS-Alg)。2)在某些情况下使用盲目凝血包(仅 LUKS-Alg)。3)根据 USZ-Alg,更早考虑使用凝血因子 XIII 替代物。本研究的目的是分析两种不同的凝血算法对接受异体输血、凝血因子、在复苏过程中即时检测的频率以及血红蛋白水平的影响。

方法

这是一项回顾性、多中心、观察性研究,纳入了 2012 年至 2014 年期间在 USZ 或 LUKS 因创伤严重程度评分(ISS)≥16 而首次入院的所有成年创伤患者。排除了转院患者和急诊科(ED)初始治疗记录缺失/不完整的患者。使用非简约逻辑回归创建了两个倾向评分匹配组,以考虑患者和创伤流行病学的潜在差异。

结果

共有 632 名符合纳入标准的患者被收治到这两家医院:428 名患者到 USZ,204 名患者到 LUKS。创建了两个倾向评分匹配组(每组 172 名)。与 LUKS-Alg 相比,使用 USZ-Alg 治疗导致接受 RBC 输血的患者人数减少(11.6%比 29.7%,OR 3.2,95%CI 1.8-5.7,p<0.001),RBC 输血量减少(0.5 SD 1.9 比 1.5 SD 3.9,p<0.001)。不同的治疗算法导致 USZ 在复苏期间的平均血红蛋白水平较低(8.0 SD 1.7 比 9.4 SD 1.8 g/dl,p<0.001),在 ICU 入院时也较低(8.3 SD 1.2 比 10.6 SD 1.9 g/dl,p<0.001)。USZ 中更频繁地进行血气分析以监测治疗和血细胞比容(每小时 1.4 SD 0.8 比 1.0 SD 0.7 次测量,p=0.004)。

结论

与仅设定较低的血细胞比容下限相比,治疗严重创伤患者时,包括目标血细胞比容范围和频繁重复血细胞比容测量的目标导向凝血算法可能导致更少的 RBC 输血。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6084/5759800/d60863f575a6/13049_2017_463_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6084/5759800/41735aadafe2/13049_2017_463_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6084/5759800/b317d3af98a3/13049_2017_463_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6084/5759800/d60863f575a6/13049_2017_463_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6084/5759800/41735aadafe2/13049_2017_463_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6084/5759800/b317d3af98a3/13049_2017_463_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6084/5759800/d60863f575a6/13049_2017_463_Fig3_HTML.jpg

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