Development of a Risk Model for Pediatric Hospital-Acquired Thrombosis: A Report from the Children's Hospital-Acquired Thrombosis Consortium

Abstract

Objective: To identify pertinent clinical variables discernible on the day of hospital admission that can be used to assess risk for hospital-acquired venous thromboembolism (HA-VTE) in children.

Study design: The Children's Hospital-Acquired Thrombosis Registry is a multi-institutional registry for all hospitalized participants aged 0-21 years diagnosed with a HA-VTE and non-VTE controls. A risk assessment model (RAM) for the development of HA-VTE using demographic and clinical VTE risk factors present at hospital admission was derived using weighted logistic regression and the least absolute shrinkage and selection (Lasso) procedure. The models were internally validated using 5-fold cross-validation. Discrimination and calibration were assessed using area under the receiver operating characteristic curve and Hosmer-Lemeshow goodness of fit, respectively.

Results: Clinical data from 728 cases with HA-VTE and 839 non-VTE controls, admitted between January 2012 and December 2016, were abstracted. Statistically significant RAM elements included age <1 year and 10-22 years, cancer, congenital heart disease, other high-risk conditions (inflammatory/autoimmune disease, blood-related disorder, protein-losing state, total parental nutrition dependence, thrombophilia/personal history of VTE), recent hospitalization, immobility, platelet count >350 K/μL, central venous catheter, recent surgery, steroids, and mechanical ventilation. The area under the receiver operating characteristic curve was 0.78 (95% CI 0.76-0.80).

Conclusions: Once externally validated, this RAM will identify those who are at low-risk as well as the greatest-risk groups of hospitalized children for investigation of prophylactic strategies in future clinical trials.

Keywords: children; risk assessment model; risk factor; risk prediction; venous thromboembolism.

Figure 1.

Reasons for exclusion of participants from the CHAT Registry to include in the risk assessment model development.

Figure 2.

Forest plot from Weighted Logistic Regression (variable selection from Lasso procedure). *PMH, past medical history **Other high risk factors include: inflammatory/autoimmune disease, hematologic disease, thrombophilia/history of VTE, total parental nutrition dependence and protein losing state