Hu Peter, Galvagno Samuel M, Sen Ayan, Dutton Richard, Jordan Sean, Floccare Douglas, Handley Christopher, Shackelford Stacy, Pasley Jason, Mackenzie Colin
University of Maryland Department of Anesthesiology, Baltimore, MD.
University of Maryland Department of Anesthesiology, Baltimore, MD.
Air Med J. 2014 Jan-Feb;33(1):27-33. doi: 10.1016/j.amj.2013.09.003.
In most trauma registries, prehospital trauma data are often missing or unreliable because of the difficult dual task consigned to prehospital providers of recording vital signs and simultaneously resuscitating patients. The purpose of this study was to test the hypothesis that the analysis of continuous vital signs acquired automatically, without prehospital provider input, improves vital signs data quality, captures more extreme values that might be missed with conventional human data recording, and changes Trauma Injury Severity Scores compared with retrospectively compiled prehospital trauma registry data.
A statewide vital signs collection network in 6 medevac helicopters was deployed for prehospital vital signs acquisition using a locally built vital signs data recorder (VSDR) to capture continuous vital signs from the patient monitor onto a memory card. VSDR vital signs data were assessed by 3 raters, and intraclass correlation coefficients were calculated to test interrater reliability. Agreement between VSDR and trauma registry data was compared with the methods of Altman and Bland including corresponding calculations for precision and bias.
Automated prehospital continuous VSDR data were collected in 177 patients. There was good agreement between the first recorded vital signs from the VSDR and the trauma registry value. Significant differences were observed between the highest and lowest heart rate, systolic blood pressure, and pulse oximeter from the VSDR and the trauma registry data (P< .001). Trauma Injury Severity Scores changed in 12 patients (7%) when using data from the VSDR.
Real-time continuous vital signs monitoring and data acquisition can identify dynamic prehospital changes, which may be missed compared with vital signs recorded manually during distinct prehospital intervals. In the future, the use of automated vital signs trending may improve the quality of data reported for inclusion in trauma registries. These data may be used to develop improved triage algorithms aimed at optimizing resource use and enhancing patient outcomes.
在大多数创伤登记系统中，由于院前急救人员面临记录生命体征和同时对患者进行复苏这一双重艰巨任务，院前创伤数据常常缺失或不可靠。本研究的目的是检验以下假设：自动获取的连续生命体征分析（无需院前急救人员输入）可提高生命体征数据质量，捕捉到更多传统人工数据记录可能遗漏的极值，并与回顾性汇编的院前创伤登记数据相比改变创伤严重度评分。
在6架医疗后送直升机上部署了一个全州范围的生命体征收集网络，使用本地制造的生命体征数据记录器（VSDR）进行院前生命体征采集，将患者监护仪上的连续生命体征记录到存储卡上。3名评估人员对VSDR生命体征数据进行评估，并计算组内相关系数以检验评估者间的可靠性。将VSDR数据与创伤登记数据之间的一致性与奥特曼和布兰德的方法进行比较，包括精度和偏差的相应计算。
收集了177例患者的院前自动连续VSDR数据。VSDR首次记录的生命体征与创伤登记值之间具有良好的一致性。VSDR与创伤登记数据在最高和最低心率、收缩压及脉搏血氧饱和度方面存在显著差异（P<0.001）。使用VSDR数据时，12例患者（7%）的创伤严重度评分发生了变化。
实时连续生命体征监测和数据采集可识别院前动态变化，与在不同院前时间段手动记录的生命体征相比，这些变化可能会被遗漏。未来，使用自动生命体征趋势分析可能会提高纳入创伤登记系统报告的数据质量。这些数据可用于开发改进的分诊算法，旨在优化资源利用并改善患者预后。
