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Hospital-Associated Venous Thromboembolism in a Pediatric Cardiac ICU: A Multivariable Predictive Algorithm to
Elizabeth W J Kerris1,2, Matthew Sharron1,2, David Zurakowski3
1Division of Critical Care Medicine, Department of Pediatrics, Children's National Hospital, Washington, DC.
Insights
Critically ill children with cardiac disease face high risks of hospital-associated venous thromboembolism (VTE). Researchers developed a predictive algorithm identifying high-risk pediatric cardiac ICU patients, aiding in VTE prevention strategies.
Area of Science:
- Pediatric Cardiology
- Critical Care Medicine
- Hematology
Background:
- Critically ill children with cardiac conditions are prone to hospital-associated venous thromboembolism (VTE).
- VTE in this population leads to increased morbidity, longer hospital stays, and higher costs.
- Current pediatric VTE prevention guidelines are lacking.
Purpose of the Study:
- To develop a predictive algorithm for identifying critically ill children with cardiac disease at high risk for hospital-associated VTE.
- To serve as a foundational step towards reducing VTE incidence in this vulnerable group.
Main Methods:
- Prospective observational single-center study conducted in a pediatric cardiac ICU.
- Analysis of 2,204 patient encounters from December 2013 to June 2017.
- Development of a multivariable predictive algorithm using identified risk factors.
Main Results:
- An overall prevalence of 25 hospital-associated VTE per 1,000 cardiac ICU encounters was observed.
- Independent risk factors for VTE included central venous catheter use, sepsis, single ventricle disease, and ECMO support.
- VTE encounters were associated with a significantly higher rate of stroke (17% vs 1.2%).
Conclusions:
- A multivariable predictive algorithm was successfully developed to identify high-risk pediatric cardiac ICU patients for hospital-associated VTE.
- This algorithm can aid clinicians in risk stratification and inform targeted VTE prevention strategies.
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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