Staff T, Eken T, Wik L, Røislien J, Søvik S
Department of Research, Norwegian Air Ambulance Foundation, Holterveien 24, PO Box 94, 1441 Drøbak, Norway; Norwegian National Centre for Prehospital Emergency Medicine, Division of Emergencies and Critical Care, Oslo University Hospital, PO Box 4956 Nydalen, 0424 Oslo, Norway.
Injury. 2014 Jan;45(1):9-15. doi: 10.1016/j.injury.2012.11.010. Epub 2012 Dec 4.
Current literature on motor vehicle accidents (MVAs) has few reports regarding field factors that predict the degree of injury. Also, studies of mechanistic factors rarely consider concurrent predictive effects of on-scene patient physiology. The New Injury Severity Score (NISS) has previously been found to correlate with mortality, need for ICU admission, length of hospital stay, and functional recovery after trauma. To potentially increase future precision of trauma triage, we assessed how the NISS is associated with physiologic, demographic and mechanistic variables from the accident site.
Using mixed-model linear regression analyses, we explored the association between NISS and pre-hospital Glasgow Coma Scale (GCS) score, Revised Trauma Score (RTS) categories of respiratory rate (RR) and systolic blood pressure (SBP), gender, age, subject position in the vehicle, seatbelt use, airbag deployment, and the estimated squared change in vehicle velocity on impact ((Δv)(2)). Missing values were handled with multiple imputation.
We included 190 accidents with 353 dead or injured subjects (mean NISS 17, median NISS 8, IQR 1-27). For the 307 subjects in front-impact MVAs, the mean increase in NISS was -2.58 per GCS point, -2.52 per RR category level, -2.77 per SBP category level, -1.08 for male gender, 0.18 per year of age, 4.98 for driver vs. rear passengers, 4.83 for no seatbelt use, 13.52 for indeterminable seatbelt use, 5.07 for no airbag deployment, and 0.0003 per (km/h)(2) velocity change (all p<0.002).
This study in victims of MVAs demonstrated that injury severity (NISS) was concurrently and independently predicted by poor pre-hospital physiologic status, increasing age and female gender, and several mechanistic measures of localised and generalised trauma energy. Our findings underscore the need for precise information from the site of trauma, to reduce undertriage, target diagnostic efforts, and anticipate need for high-level care and rehabilitative resources.
当前关于机动车事故（MVA）的文献中，很少有关于预测损伤程度的现场因素的报道。此外，对机械因素的研究很少考虑现场患者生理状况的并发预测作用。先前已发现新损伤严重程度评分（NISS）与死亡率、入住重症监护病房的需求、住院时间以及创伤后的功能恢复相关。为了潜在地提高未来创伤分诊的准确性，我们评估了NISS与事故现场的生理、人口统计学和机械变量之间的关联。
使用混合模型线性回归分析，我们探讨了NISS与院前格拉斯哥昏迷量表（GCS）评分、修订创伤评分（RTS）中呼吸频率（RR）和收缩压（SBP）类别、性别、年龄、车内乘客位置、安全带使用情况、安全气囊展开情况以及撞击时车辆速度的估计平方变化（(Δv)(2)）之间的关联。缺失值采用多重填补法处理。
我们纳入了190起事故中的353名死亡或受伤受试者（NISS均值为17，中位数为8，四分位数间距为1 - 27）。对于307名前碰撞MVA中的受试者，NISS的平均增加量为：每降低1分GCS评分为 -2.58，每降低1级RR类别为 -2.52，每降低1级SBP类别为 -2.77，男性为 -1.08，每增加1岁为0.18，驾驶员相对于后排乘客为4.98，未使用安全带为4.83，无法确定安全带使用情况为13.52，未展开安全气囊为5.07，每变化1（km/h）(2)速度为0.0003（所有p < 0.002）。
这项针对MVA受害者的研究表明，损伤严重程度（NISS）同时且独立地由院前生理状态差、年龄增加和女性性别以及局部和全身创伤能量的几种机械测量指标所预测。我们的研究结果强调了从创伤现场获取精确信息的必要性，以减少分诊不足、确定诊断重点，并预测对高级护理和康复资源的需求。
