Abstract

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. This is a prospective observational single-center study. Tertiary care referral children's hospital cardiac ICU. 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. 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). 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.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.