TY - JOUR
T1 - A clinical tool for the prediction of venous thromboembolism in pediatric trauma patients
AU - Connelly, Christopher R.
AU - Laird, Amy
AU - Barton, Jeffrey S.
AU - Fischer, Peter E.
AU - Krishnaswami, Sanjay
AU - Schreiber, Martin A.
AU - Zonies, David H.
AU - Watters, Jennifer M.
N1 - Publisher Copyright:
Copyright 2016 American Medical Association. All rights reserved.
Copyright:
Copyright 2016 Elsevier B.V., All rights reserved.
PY - 2016/1
Y1 - 2016/1
N2 - IMPORTANCE Although rare, the incidence of venous thromboembolism (VTE) in pediatric trauma patients is increasing, and the consequences of VTE in children are significant. Studies have demonstrated increasing VTE risk in older pediatric trauma patients and improved VTE rates with institutional interventions. While national evidence-based guidelines for VTE screening and prevention are in place for adults, none exist for pediatric patients, to our knowledge. OBJECTIVES To develop a risk prediction calculator for VTE in children admitted to the hospital after traumatic injury to assist efforts in developing screening and prophylaxis guidelines for this population. DESIGN, SETTING, AND PARTICIPANTS Retrospective review of 536 423 pediatric patients 0 to 17 years old using the National Trauma Data Bank from January 1, 2007, to December 31, 2012. Five mixed-effects logistic regression models of varying complexity were fit on a training data set. Model validity was determined by comparison of the area under the receiver operating characteristic curve (AUROC) for the training and validation data sets from the original model fit. A clinical tool to predict the risk of VTE based on individual patient clinical characteristics was developed from the optimal model. MAIN OUTCOME AND MEASURE Diagnosis of VTE during hospital admission. RESULTS Venous thromboembolism was diagnosed in 1141 of 536 423 children (overall rate, 0.2%). The AUROCs in the training data set were high (range, 0.873-0.946) for each model, with minimal AUROC attenuation in the validation data set. A prediction tool was developed from a model that achieved a balance of high performance (AUROCs, 0.945 and 0.932 in the training and validation data sets, respectively; P = .048) and parsimony. Points are assigned to each variable considered (Glasgow Coma Scale score, age, sex, intensive care unit admission, intubation, transfusion of blood products, central venous catheter placement, presence of pelvic or lower extremity fractures, and major surgery), and the points total is converted to a VTE risk score. The predicted risk of VTE ranged from 0.0%to 14.4%. CONCLUSIONS AND RELEVANCE We developed a simple clinical tool to predict the risk of developing VTE in pediatric trauma patients. It is based on a model created using a large national database and was internally validated. The clinical tool requires external validation but provides an initial step toward the development of the specific VTE protocols for pediatric trauma patients.
AB - IMPORTANCE Although rare, the incidence of venous thromboembolism (VTE) in pediatric trauma patients is increasing, and the consequences of VTE in children are significant. Studies have demonstrated increasing VTE risk in older pediatric trauma patients and improved VTE rates with institutional interventions. While national evidence-based guidelines for VTE screening and prevention are in place for adults, none exist for pediatric patients, to our knowledge. OBJECTIVES To develop a risk prediction calculator for VTE in children admitted to the hospital after traumatic injury to assist efforts in developing screening and prophylaxis guidelines for this population. DESIGN, SETTING, AND PARTICIPANTS Retrospective review of 536 423 pediatric patients 0 to 17 years old using the National Trauma Data Bank from January 1, 2007, to December 31, 2012. Five mixed-effects logistic regression models of varying complexity were fit on a training data set. Model validity was determined by comparison of the area under the receiver operating characteristic curve (AUROC) for the training and validation data sets from the original model fit. A clinical tool to predict the risk of VTE based on individual patient clinical characteristics was developed from the optimal model. MAIN OUTCOME AND MEASURE Diagnosis of VTE during hospital admission. RESULTS Venous thromboembolism was diagnosed in 1141 of 536 423 children (overall rate, 0.2%). The AUROCs in the training data set were high (range, 0.873-0.946) for each model, with minimal AUROC attenuation in the validation data set. A prediction tool was developed from a model that achieved a balance of high performance (AUROCs, 0.945 and 0.932 in the training and validation data sets, respectively; P = .048) and parsimony. Points are assigned to each variable considered (Glasgow Coma Scale score, age, sex, intensive care unit admission, intubation, transfusion of blood products, central venous catheter placement, presence of pelvic or lower extremity fractures, and major surgery), and the points total is converted to a VTE risk score. The predicted risk of VTE ranged from 0.0%to 14.4%. CONCLUSIONS AND RELEVANCE We developed a simple clinical tool to predict the risk of developing VTE in pediatric trauma patients. It is based on a model created using a large national database and was internally validated. The clinical tool requires external validation but provides an initial step toward the development of the specific VTE protocols for pediatric trauma patients.
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U2 - 10.1001/jamasurg.2015.2670
DO - 10.1001/jamasurg.2015.2670
M3 - Article
C2 - 26422678
AN - SCOPUS:84955282950
SN - 2168-6254
VL - 151
SP - 50
EP - 57
JO - JAMA Surgery
JF - JAMA Surgery
IS - 1
ER -