Improvement of the performance of survival prediction in the ageing blunt trauma population: A cohort study

被引:6
作者
de Munter, Leonie [1 ]
ter Bogt, Nancy C. W. [2 ]
Polinder, Suzanne [3 ]
Sewalt, Charlie A. [3 ]
Steyerberg, Ewout W. [3 ,4 ]
de Jongh, Mariska A. C. [1 ,5 ]
机构
[1] Elisabeth TweeSteden Hosp ETZ Ziekenhuis, Dept Trauma TopCare, Tilburg, Netherlands
[2] Network Emergency Care Euregio, Enschede, Netherlands
[3] Erasmus MC, Dept Publ Hlth, Rotterdam, Netherlands
[4] Leiden Univ, Med Ctr, Dept Biomed Data Sci, Leiden, Netherlands
[5] Network Emergency Care Brabant, Brabant Trauma Registry, Tilburg, Netherlands
关键词
PHYSICAL STATUS CLASSIFICATION; ISOLATED HIP-FRACTURES; SEVERITY-SCORE TRISS; MORTALITY; INJURY; COMORBIDITY; MODELS; AGE; VALIDATION; FRAILTY;
D O I
10.1371/journal.pone.0209099
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Introduction The overestimation of survival predictions in the ageing trauma population results in negative benchmark numbers in hospitals that mainly treat elderly patients. The aim of this study was to develop and validate a modified Trauma and Injury Severity Score (TRISS) for accurate survival prediction in the ageing blunt trauma population. Methods This retrospective study was conducted with data from two Dutch Trauma regions. Missing values were imputed. New prediction models were created in the development set, including age (continuous or categorical) and Anesthesiologists Physical Status (ASA). The models were externally validated. Subsets were created based on age (>= 75 years) and the presence of hip fracture. Model performance was assessed by proportion explained variance (Nagelkerke R-2), discrimination (Area Under the curve of the Receiver Operating Characteristic, AUROC) and visually with calibration plots. A final model was created based on both datasets. Results No differences were found between the baseline characteristics of the development dataset (n = 15,530) and the validation set (n = 15,504). The inclusion of ASA in the prediction models showed significant improved discriminative abilities in the two subsets (e.g. AUROC of 0.52 [95% CI: 0.46, 0.58] vs. 0.74 [95% CI: 0.69, 0.78] for elderly patients with hip fracture) and an increase in the proportion explained variance (R-2 = 0.32 to R-2 = 0.35 in the total cohort). The final model showed high agreement between observed and predicted survival in the calibration plot, also in the subsets. Conclusions Including ASA and age (continuous) in survival prediction is a simple adjustment of the TRISS methodology to improve survival predictions in the ageing blunt trauma population. A new model is presented, through which even patients with isolated hip fractures could be included in the evaluation of trauma care.
引用
收藏
页数:12
相关论文
共 46 条
[1]  
[Anonymous], 2018, LAND TRAUM TOEL UITK
[2]  
[Anonymous], 2016, Abbreviated Injury Scale (c) 2005 Update 2008
[3]   Should patients with isolated hip fractures be included in trauma registries? [J].
Bergeron, E ;
Lavoie, A ;
Belcaid, A ;
Ratte, S ;
Clas, D .
JOURNAL OF TRAUMA-INJURY INFECTION AND CRITICAL CARE, 2005, 58 (04) :793-797
[4]   Improving the TRISS methodology by restructuring age categories and adding comorbidities [J].
Bergeron, E ;
Rossignol, M ;
Osler, T ;
Clas, D ;
Lavoie, A .
JOURNAL OF TRAUMA-INJURY INFECTION AND CRITICAL CARE, 2004, 56 (04) :760-767
[5]   A new approach to outcome prediction in trauma: A comparison with the TRISS model [J].
Bouamra, Omar ;
Wrotchford, Alan ;
Hollis, Sally ;
Vail, Andy ;
Woodford, Maralyn ;
Lecky, Fiona .
JOURNAL OF TRAUMA-INJURY INFECTION AND CRITICAL CARE, 2006, 61 (03) :701-710
[6]   Prediction modelling for trauma using comorbidity and "true' 30-day outcome [J].
Bouamra, Omar ;
Jacques, Richard ;
Edwards, Antoinette ;
Yates, David W. ;
Lawrence, Thomas ;
Jenks, Tom ;
Woodford, Maralyn ;
Lecky, Fiona .
EMERGENCY MEDICINE JOURNAL, 2015, 32 (12) :933-938
[7]   EVALUATING TRAUMA CARE - THE TRISS METHOD [J].
BOYD, CR ;
TOLSON, MA ;
COPES, WS .
JOURNAL OF TRAUMA-INJURY INFECTION AND CRITICAL CARE, 1987, 27 (04) :370-378
[8]   How well do pediatric anesthesiologists agree when assigning ASA physical status classifications to their patients? [J].
Burgoyne, Laura L. ;
Smeltzer, Matthew P. ;
Pereiras, Lilia A. ;
Norris, Angela L. ;
De Armendi, Alberto J. .
PEDIATRIC ANESTHESIA, 2007, 17 (10) :956-962
[9]  
Cinelli Scott M, 2009, Conn Med, V73, P261
[10]   Effect of Subjective Preoperative Variables on Risk-Adjusted Assessment of Hospital Morbidity and Mortality [J].
Cohen, Mark E. ;
Bilimoria, Karl Y. ;
Ko, Clifford Y. ;
Richards, Karen ;
Hall, Bruce Lee .
ANNALS OF SURGERY, 2009, 249 (04) :682-689