TY - JOUR
T1 - Hospital-Associated Venous Thromboembolism in a Pediatric Cardiac ICU
T2 - A Multivariable Predictive Algorithm to Identify Children at High Risk
AU - Kerris, Elizabeth W.J.
AU - Sharron, Matthew
AU - Zurakowski, David
AU - Staffa, Steven J.
AU - Yurasek, Greg
AU - Diab, Yaser
N1 - Funding Information:
Dr. Kerris’ institution received funding from a Ruth L. Kirschstein National Research Service Award Institutional Research Training Grant awarded to the Children’s Research Institute Hematology Training Program by the National Heart, Lung and Blood Institute of the National Institutes of Health (NIH) (5T32HL110841-07), and she received support for article research from the NIH. The remaining authors have disclosed that they do not have any potential conflicts of interest. For information regarding this article, E-mail: ebjones@childrensnational.org
Publisher Copyright:
© 2020 Lippincott Williams and Wilkins. All rights reserved.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - Objectives: Critically ill children with cardiac disease are at significant risk for hospital-Associated venous thromboembolism, which is associated with increased morbidity, hospital length of stay, and cost. Currently, there are no widely accepted guidelines for prevention of hospital-Associated venous thromboembolism in pediatrics. We aimed to develop a predictive algorithm for identifying critically ill children with cardiac disease who are at increased risk for hospital-Associated venous thromboembolism as a first step to reducing hospital-Associated venous thromboembolism in this population. Design: This is a prospective observational single-center study. Setting: Tertiary care referral children's hospital cardiac ICU. Patients: Children less than or equal to18 years old admitted to the cardiac ICU who developed a hospital-Associated venous thromboembolism from December 2013 to June 2017 were included. Odds ratios and 95% CIs are reported for multivariable predictors. Measurements and Main Results: A total of 2,204 separate cardiac ICU encounters were evaluated with 56 hospital-Associated venous thromboembolisms identified in 52 unique patients, yielding an overall prevalence of 25 hospital-Associated venous thromboembolism per 1,000 cardiac ICU encounters. We were able to create a predictive algorithm with good internal validity that performs well at predicting hospital-Associated venous thromboembolism. The presence of a central venous catheter (odds ratio, 4.76; 95% CI, 2.0-11.1), sepsis (odds ratio, 3.5; 95% CI, 1.5-8.0), single ventricle disease (odds ratio, 2.2; 95% CI, 1.2-3.9), and extracorporeal membrane oxygenation support (odds ratio, 2.7; 95% CI, 1.2-5.7) were independent risk factors for hospital-Associated venous thromboembolism. Encounters with hospital-Associated venous thromboembolism were associated with a higher rate of stroke (17% vs 1.2%; p < 0.001). Conclusions: We developed a multivariable predictive algorithm to help identify children who may be at high risk of hospital-Associated venous thromboembolism in the pediatric cardiac ICU.
AB - Objectives: Critically ill children with cardiac disease are at significant risk for hospital-Associated venous thromboembolism, which is associated with increased morbidity, hospital length of stay, and cost. Currently, there are no widely accepted guidelines for prevention of hospital-Associated venous thromboembolism in pediatrics. We aimed to develop a predictive algorithm for identifying critically ill children with cardiac disease who are at increased risk for hospital-Associated venous thromboembolism as a first step to reducing hospital-Associated venous thromboembolism in this population. Design: This is a prospective observational single-center study. Setting: Tertiary care referral children's hospital cardiac ICU. Patients: Children less than or equal to18 years old admitted to the cardiac ICU who developed a hospital-Associated venous thromboembolism from December 2013 to June 2017 were included. Odds ratios and 95% CIs are reported for multivariable predictors. Measurements and Main Results: A total of 2,204 separate cardiac ICU encounters were evaluated with 56 hospital-Associated venous thromboembolisms identified in 52 unique patients, yielding an overall prevalence of 25 hospital-Associated venous thromboembolism per 1,000 cardiac ICU encounters. We were able to create a predictive algorithm with good internal validity that performs well at predicting hospital-Associated venous thromboembolism. The presence of a central venous catheter (odds ratio, 4.76; 95% CI, 2.0-11.1), sepsis (odds ratio, 3.5; 95% CI, 1.5-8.0), single ventricle disease (odds ratio, 2.2; 95% CI, 1.2-3.9), and extracorporeal membrane oxygenation support (odds ratio, 2.7; 95% CI, 1.2-5.7) were independent risk factors for hospital-Associated venous thromboembolism. Encounters with hospital-Associated venous thromboembolism were associated with a higher rate of stroke (17% vs 1.2%; p < 0.001). Conclusions: We developed a multivariable predictive algorithm to help identify children who may be at high risk of hospital-Associated venous thromboembolism in the pediatric cardiac ICU.
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U2 - 10.1097/PCC.0000000000002293
DO - 10.1097/PCC.0000000000002293
M3 - Article
C2 - 32343105
AN - SCOPUS:85085905285
VL - 21
SP - e362-e368
JO - Pediatric Critical Care Medicine
JF - Pediatric Critical Care Medicine
SN - 1529-7535
IS - 6
ER -