首页> 外文期刊>Journal of the American College of Surgeons >A multiple imputation model for imputing missing physiologic data in the national trauma data bank.
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A multiple imputation model for imputing missing physiologic data in the national trauma data bank.

机译:用于估算国家创伤数据库中缺少的生理数据的多重估算模型。

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BACKGROUND: Like most trauma registries, the National Trauma Data Bank (NTDB) is limited by the problem of missing physiologic data. Multiple imputation (MI) has been proposed to simulate missing Glasgow Coma Scale (GCS) scores, respiratory rate (RR), and systolic blood pressure (SBP). The aim of this study was to develop an MI model for missing physiologic data in the NTDB and to provide guidelines for its implementation. STUDY DESIGN: The NTDB 7.0 was restricted to patients admitted in 2005 with at least one anatomic injury code. A series of auxiliary variables thought to offer information for the imputation process was selected from the NTDB by literature review and expert opinion. The relation of these variables to physiologic variables and to the fact that they were missing was examined using logistic regression. The MI model included all auxiliary variables that had a statistically significant association with physiologic variables or with the fact that they were missing (Bonferroni-corrected p value <0.05). RESULTS: The NTDB sample included 373,243 observations. Glasgow Coma Scale, respiratory rate, and systolic blood pressure were missing for 20.3%, 3.9%, and 8.5% of data observations, respectively. The MI model included information on the following: gender, age, anatomic injury severity, transfer status, injury mechanism, intubation status, alcohol and drug test results, emergency department disposition, total length of stay, ICU length of stay, duration of mechanical ventilation, and discharge disposition. The MI model offered good discrimination for predicting the value of physiologic variables and the fact that they were missing (areas under the receiver operating characteristic curve between 0.832 and 0.999). CONCLUSIONS: This article proposes an MI model for imputing missing physiologic data in the NTDB and provides guidelines to facilitate its use. Implementation of the model should improve the quality of research involving the NTDB. The methodology can also be adapted to other trauma registries.
机译:背景:像大多数创伤登记处一样,国家创伤数据库(NTDB)受缺少生理数据的问题所限制。已提出多重插补(MI)以模拟缺少的格拉斯哥昏迷量表(GCS)评分,呼吸频率(RR)和收缩压(SBP)。这项研究的目的是为NTDB中缺少的生理数据建立一个MI模型,并为其实施提供指导。研究设计:NTDB 7.0仅限于2005年入院并具有至少一种解剖学损伤规范的患者。通过文献综述和专家意见,从NTDB中选择了一系列被认为可为插补过程提供信息的辅助变量。使用逻辑回归检验这些变量与生理变量之间的关系以及与它们缺失的事实之间的关系。 MI模型包括所有辅助变量,这些辅助变量与生理变量或缺少生理变量具有统计学上的显着关联(Bonferroni校正的p值<0.05)。结果:NTDB样本包括373,243个观测值。格拉斯哥昏迷量表,呼吸频率和收缩压分别缺失了20.3%,3.9%和8.5%的数据观察值。 MI模型包括以下信息:性别,年龄,解剖学损伤严重程度,转移状态,损伤机制,插管状态,酒精和药物测试结果,急诊科处置,总住院时间,ICU住院时间,机械通气时间,并放电处置。 MI模型为预测生理变量的值和它们缺失的事实提供了很好的判别(在接收器工作特性曲线下的区域,介于0.832和0.999之间)。结论:本文提出了一种用于估算NTDB中缺少的生理数据的MI模型,并提供了有助于其使用的指南。该模型的实施应提高涉及NTDB的研究质量。该方法还可以适用于其他创伤登记处。

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