Mathis S, Kellermann S, Schmid S, Mutschlechner H, Raab H, Wenzel V, El Attal R, Kreutziger J
Klinik für Anästhesie und Intensivmedizin, Medizinische Universität Innsbruck, Anichstr. 35, 6020, Innsbruck, Österreich.
Anaesthesist. 2014 May;63(5):387-93. doi: 10.1007/s00101-014-2315-x. Epub 2014 Apr 10.
Many commonly available trauma scores predict mortality, but to evaluate the success of a certain therapy or for difficult scientific and epidemiological purposes this may be insufficient in the face of improved survival rates. For outcome analysis of multiple trauma patients, the extent of medical resources needed could be an additional outcome measurement. McPeek et al. developed a potential scoring system for elective surgery patients, which was recently modified for multiple trauma patients.
The current study investigated if the McPeek score could be prospectively used in multiple trauma patients and whether it could become an additional helpful tool in outcome assessment. Applicability was assessed by practical examples.
In this prospective single-centre study at the University Hospital of Innsbruck, Austria, between December 2008 and November 2010 multiple trauma patients (≥ 18 years) with an injury severity score (ISS) ≥ 17 were enrolled. Besides demographic data, prehospital vital parameters and diagnoses, all diagnoses from the trauma, mortality, length of stay in the intensive care unit and the hospital were recorded. The commonly used trauma scores ISS, revised trauma score (RTS), a severity characterization of trauma (ASCOT) and trauma and injury severity score (TRISS) were applied and an observed McPeek score was allocated following end of hospitalization. The McPeek scoring system was used according to the latest modifications. A correlation between trauma scores and the McPeek score was performed. The McPeek score was then predicted by a common trauma score using ordinal regression with the polytomous universal model (PLUM method). By subtracting the predicted from the observed McPeek scores the residual McPeek value was calculated and used for practical examples of outcome analysis with the McPeek scoring system.
Out of 406 identified multiple trauma patients during the study phase, 183 had to be excluded due to missing data (mainly prehospital or following transfer). A total of 223 patients (mean ISS 31.2, mean age 47.2 years) were enrolled and assigned to the population-based observed McPeek score (median 4.0). Correlation coefficients were Glasgow coma scale (GCS) 0.59, ISS 0.62, RTS 0.65, TRISS 0.74 and ASCOT 0.77 (p < 0.0001). The TRISS predicted the McPeek score best in ordinal regression (pseudo-R(2) = 0.944, p < 0.0001). The residual McPeek score (observed minus predicted) was used to illustrate the influence of the blood glucose level on admission and the influence of head injury on outcome of multiple injury patients in detail.
The modified McPeek score is applicable to multiple trauma patients to assess outcome for scientific or epidemiological purposes. Its main advantage is that it quantifies outcome independently of regional or national circumstances.
许多常用的创伤评分可预测死亡率，但面对生存率的提高，要评估某种治疗的成功率或用于复杂的科学及流行病学目的，这可能并不足够。对于多发伤患者的结局分析，所需医疗资源的程度可能是一项额外的结局衡量指标。麦克皮克等人针对择期手术患者开发了一种潜在的评分系统，该系统最近针对多发伤患者进行了修改。
本研究调查麦克皮克评分是否可前瞻性地用于多发伤患者，以及它是否能成为结局评估中一个额外有用的工具。通过实际例子评估其适用性。
在奥地利因斯布鲁克大学医院进行的这项前瞻性单中心研究中，纳入了2008年12月至2010年11月期间损伤严重程度评分（ISS）≥17的多发伤患者（≥18岁）。除了人口统计学数据、院前生命体征参数和诊断外，还记录了创伤的所有诊断、死亡率、重症监护病房和医院的住院时间。应用了常用的创伤评分ISS、修订创伤评分（RTS）、创伤严重程度特征化（ASCOT）和创伤与损伤严重程度评分（TRISS），并在住院结束后分配观察到的麦克皮克评分。麦克皮克评分系统根据最新修改进行使用。对创伤评分与麦克皮克评分之间进行相关性分析。然后使用多分类通用模型的有序回归（PLUM方法）通过常用创伤评分预测麦克皮克评分。通过从观察到的麦克皮克评分中减去预测值来计算残余麦克皮克值，并将其用于麦克皮克评分系统结局分析的实际例子。
在研究阶段确定的406例多发伤患者中，183例因数据缺失（主要是院前或转运后的数据）而被排除。共纳入223例患者（平均ISS 31.2，平均年龄47.2岁），并分配基于人群的观察到的麦克皮克评分（中位数4.0）。相关系数分别为格拉斯哥昏迷量表（GCS）0.59、ISS 0.62、RTS 0.65、TRISS 0.74和ASCOT 0.77（p<0.0001）。在有序回归中，TRISS对麦克皮克评分的预测最佳（伪R(2)=0.944，p<0.0001）。残余麦克皮克评分（观察值减去预测值）用于详细说明入院时血糖水平的影响以及头部损伤对多发伤患者结局的影响。
修改后的麦克皮克评分适用于多发伤患者，以用于科学或流行病学目的的结局评估。其主要优点是它独立于地区或国家情况对结局进行量化。
