THE SEQUENTIAL TRAUMA SCORE - A NEW INSTRUMENT FOR THE SEQUENTIAL MORTALITY PREDICTION IN MAJOR TRAUMA

被引:31
作者
Huber-Wagner, S. [1 ]
Stegmaier, J. [1 ]
Mathonia, P. [1 ]
Paffrath, T. [2 ]
Euler, E. [1 ]
Mutschler, W. [1 ]
Kanz, K. -G. [1 ]
Lefering, R. [3 ]
机构
[1] Univ Munich, Munich Univ Dept Trauma Surg, Munich, Germany
[2] Univ Witten Herdecke, Cologne Merheim Med Ctr, Dept Trauma & Orthoped Surg, Cologne, Germany
[3] Univ Witten Herdecke, Cologne Merheim Med Ctr, IFOM Inst Res Operat Med, Cologne, Germany
关键词
Major trauma; outcome; prognosis; scoring; score; severely injured patients; polytrauma; dynamic score; ISS; TRISS; RISC; STS; INJURY SEVERITY SCORE; BRAIN-INJURY; IMPROVES ACCURACY; GERMAN SOCIETY; CARE; REGISTRY; HYPOTHERMIA; VALIDATION; SURGERY; SYSTEMS;
D O I
10.1186/2047-783X-15-5-185
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Background: There are several well established scores for the assessment of the prognosis of major trauma patients that all have in common that they can be calculated at the earliest rioting intensive care unit stay. We intended to develop a sequential trauma score (STS) that allows prognosis at several early stages based on the information that is available at a particular time. Study Design: In a retrospective, multicenter study using data derived from the Trauma Registry of the German Trauma Society (2002-2006), we identified the most relevant prognostic factors from the patients basic data (B), prehospital phase (A), early (B1), and late (B2) trauma room phase. Univariate and logistic regression models as well as score quality criteria and the explanatory power have been calculated. Results: A total of 2,354 patients with complete data were identified. From the patients basic data (P), logistic regression showed that age was a significant predictor of survival (AUC(model) (P), area under the curve = 0.63). Logistic regression of the prehospital data (A) showed that blood pressure, pulse rate, Glasgow coma scale (GCS), and anisocoria were significant predictors (AUC(model A) = 0.76; AUC(model) (P + A) = 0.82). Logistic regression of the early trauma room phase (B1) showed that peripheral oxygen saturation, GCS, anisocoria, base excess, and thromboplastin time to be significant predictors of survival (AUC(model) (B1) = 0.78; AUC(model P + A + B1) = 0.85). Multivariate analysis of the late trauma room phase (132) detected cardiac massage, abbreviated injury score (AIS) of the head >= 3, the maximum MS, the need for transfusion or massive blood transfusion, to be the most important predictors (AUC(model B2) = 0.84; AUC(final model P + A + B1 + B2) = 0.90). The explanatory power - a tool for the assessment of the relative impact of each segment to mortality - is 25% for P, 7% for A, 17% for B1 and 51% for B2. A spreadsheet for the easy calculation of the sequential trauma score is available at: www.sequential-trauma-score.com Conclusions: This score is the first sequential, dynamic score to provide a prognosis for patients with blunt major trauma at several points in time. With every additional piece of information the precision increases. The medical team has a simple, useful tool to identify patients at high risk and to predict the prognosis of an individual patient with major trauma very early, quickly and precisely.
引用
收藏
页码:185 / 195
页数:11
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