Accelerating availability of clinically-relevant parameter estimates from thromboelastogram point-of-care device.
Accelerating availability of clinically-relevant parameter estimates from thromboelastogram point-of-care device.
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DOI：
10.1097/ta.0000000000002608
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发表时间：
2020-05
期刊：
影响因子：
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通讯作者：
Clermont G
中科院分区：
文献类型：
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作者：
Pressly MA;Parker RS;Neal MD;Sperry JL;Clermont G
建模方法提供了一种新的方法来检测和预测创伤患者的凝血功能障碍。根据血栓弹力图（TEG）数据构建和测试的动态模型用于生成超过160，000个模拟RapidTEG的虚拟库。患者特异性参数为初始血小板计数、血小板活化率、血栓生长率和溶解率（分别为P（0）、k1、k2和k3）。收集了来自STAAMP（n=182例患者）和PAMPer（n=111例患者）临床试验的患者数据。共分析了873个RapidTEG。116个TEG指示最大振幅（MA）低于正常，466个TEG指示溶解百分比高于正常。将每个患者的TEG响应与TEG的虚拟库进行比较，以确定在每个指定的评估时间∈ {3，4，5，7.5，10，15，20分钟}内相对于患者TEG具有最小平方和误差的库轨迹。使用10个最近邻轨迹，使用来自动态模型的参数进行逻辑回归以预测患者TEG是否指示MA低于正常（< 50 mm）、MA后30分钟的溶解百分比（LY 30）是否大于3%和/或输血需要。该算法使用RapidTEG数据的初始3分钟预测异常MA值，中位AUC为0.95，并在10分钟内随着更多数据的增加而提高至0.98。分别基于4分钟和5分钟时的参数预测未来的血小板和浓缩红细胞输注，在显著更短的时间内提供了与传统TEG参数等效的预测。动态模型参数不能预测LY 30异常或未来新鲜冰冻血浆输注。该分析可以结合到TEG软件和工作流程中，以快速估计在TEG之后的最初几分钟内MA是否低于或高于阈值，沿着估计手头上有什么血液制品。治疗/护理管理：IV级：使用历史对照或具有一个以上阴性标准的前瞻性/回顾性研究。诊断测试
Modeling approaches offer a novel way to detect and predict coagulopathy in trauma patients. A dynamic model, built and tested on thromboelastogram (TEG) data, was used to generate a virtual library of over 160,000 simulated RapidTEGs. The patient-specific parameters are the initial platelet count, platelet activation rate, thrombus growth rate, and lysis rate (P(0), k1, k2, and k3, respectively). Patient data from both STAAMP (n=182 patients) and PAMPer (n=111 patients) clinical trials were collected. A total of 873 RapidTEGs were analyzed. 116 TEGs indicated maximum amplitude (MA) below normal and 466 TEGs indicated lysis percent above normal. Each patient’s TEG response was compared against the virtual library of TEGs to determine library trajectories having the least sum-of-squared error versus the patient TEG up to each specified evaluation time ∈ {3, 4, 5, 7.5, 10, 15, 20 minutes}. Using 10 nearest-neighbor trajectories, a logistic regression was performed to predict if the patient TEG indicated MA below normal (< 50 mm), lysis percent 30 minutes after MA (LY30) greater than 3%, and/or blood transfusion need using the parameters from the dynamic model. The algorithm predicts abnormal MA values using the initial 3 minutes of RapidTEG data with a median AUC of 0.95, and improves with more data to 0.98 by 10 minutes. Prediction of future platelet and packed red blood cell transfusion based on parameters at 4 and 5 minutes, respectively, provides equivalent predictions to the traditional TEG parameters in significantly less time. Dynamic model parameters could not predict abnormal LY30 or future fresh frozen plasma transfusion. This analysis could be incorporated into TEG software and workflow to quickly estimate if the MA would be below or above threshold value within the initial minutes following a TEG, along with an estimate of what blood products to have on hand. Therapeutic/Care Management: Level IV: Prospective/retrospective study using historical controls or having more than one negative criterion. Diagnostic Test