Heller A R, Salvador N, Frank M, Schiffner J, Kipke R, Kleber C
Department of Anesthesiology and Critical Care Medicine, Medical Faculty Carl Gustav Carus, TU-Dresden, Fetscherstrasse 74, 01307, Dresden, Germany.
DRF Air Rescue Base "Christoph 38", Dresden, Germany.
Anaesthesist. 2019 Feb;68(Suppl 1):15-24. doi: 10.1007/s00101-017-0352-y. Epub 2017 Aug 10.
Regarding survival and quality of life recent mass casualty incidents again emphasize the importance of early identification of the correct degree of injury/illness to enable prioritization of treatment amongst patients and their transportation to an appropriate hospital. The present study investigated existing triage algorithms in terms of sensitivity (SE) and specificity (SP) as well as its process duration in a relevant emergency patient cohort.
In this study 500 consecutive air rescue missions were evaluated by means of standardized patient records. Classification of patients was accomplished by 19 emergency physicians. Every case was independently classified by at least 3 physicians without considering any triage algorithm. Existing triage algorithms Primary Ranking for Initial Orientation in Emergency Medical Services (PRIOR), modified Simple Triage and Rapid Treatment (mSTaRT), Field Triage Score (FTS), Amberg-Schwandorf Algorithm for Triage (ASAV), Simple Triage and Rapid Treatment (STaRT), Care Flight, and Triage Sieve were additionally carried out computer based on each case, to enable calculation of quality criteria.
The analyzed cohort had an age of (mean ± SD) 59 ± 25 years, a NACA score of 3.5 ± 1.1 and consisted of 57% men. On arrival 8 patients were deceased. Consequently, 492 patients were included in the analysis. The distribution of triage categories T1/T2/T3 were 10%/47%/43%, respectively. The highest diagnostic quality was achieved with START, mSTaRT, and ASAV yielding a SE of 78% and a SP ranging from 80-83%. The subgroup of surgical patients reached a SE of 95% and a SP between 85-91%. The newly established algorithm PRIOR exerted a SE of 90% but merely a SP of 54% in the overall cohort thereby consuming the longest time for overall decision.
Triage procedures with acceptable diagnostic quality exist to identify the most severely injured. Due to its high rate of false positive results (over-triage) the recently developed PRIOR algorithm will cause overload of available resources for the severely injured within mass casualty incident missions. Non-surgical patients still are poorly identified by the available algorithms.
关于生存和生活质量，近期的大规模伤亡事件再次强调了早期准确识别损伤/疾病程度对于在患者中确定治疗优先级以及将他们转运至合适医院的重要性。本研究在一个相关的急诊患者队列中，对现有分诊算法的敏感性（SE）、特异性（SP）及其流程持续时间进行了调查。
在本研究中，通过标准化的患者记录对500次连续的空中救援任务进行了评估。患者分类由19名急诊医生完成。每个病例至少由3名医生独立分类，不考虑任何分诊算法。现有的分诊算法，如紧急医疗服务初始定位的初级排序（PRIOR）、改良的简单分诊与快速治疗（mSTaRT）、现场分诊评分（FTS）、安贝格 - 施万多夫分诊算法（ASAV）、简单分诊与快速治疗（STaRT）、Care Flight和分诊筛检法，也基于每个病例进行了计算机运算，以便计算质量标准。
分析的队列年龄为（平均±标准差）59±25岁，NACA评分为3.5±1.1，男性占57%。到达时8名患者已死亡。因此，492名患者被纳入分析。分诊类别T1/T2/T3的分布分别为10%/47%/43%。START、mSTaRT和ASAV实现了最高的诊断质量，敏感性为78%，特异性在80 - 83%之间。外科患者亚组的敏感性达到95%，特异性在85 - 91%之间。新建立的算法PRIOR在整个队列中的敏感性为90%，但特异性仅为54%，从而在总体决策上消耗了最长时间。
存在诊断质量可接受的分诊程序来识别最严重受伤的患者。由于其高假阳性率（过度分诊），最近开发的PRIOR算法将在大规模伤亡事件任务中导致重伤患者可用资源的过载。现有的算法对非手术患者的识别仍然较差。
