ICU Admission Tool for Congenital Heart Catheterization (iCATCH): A Predictive Model for High Level Post-Catheterization Care and Patient Management.

ABSTRACT

OBJECTIVES: Currently, there are no prediction tools available to identify patients at risk of needing high-complexity care following cardiac catheterization for congenital heart disease. We sought to develop a method to predict the likelihood a patient will require intensive care level resources following elective cardiac catheterization. DESIGN: Prospective single-center study capturing important patient and procedural characteristics for predicting discharge to the ICU. Characteristics significant at the 0.10 level in the derivation dataset (July 1, 2017 to December 31, 2019) were considered for inclusion in the final multivariable logistic regression model. The model was validated in the testing dataset (January 1, 2020 to December 31, 2020). The novel pre-procedure cardiac status (PCS) feature, collection started in January 2019, was assessed separately in the final model using the 2019 through 2020 dataset. SETTING: Tertiary pediatric heart center. PATIENTS All elective cases coming from home or non-ICU who underwent a cardiac catheterization from July 2017 to December 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 2,192 cases were recorded in the derivation dataset, of which 11% of patients ( n = 245) were admitted to the ICU, while 64% ( n = 1,413) were admitted to a medical unit and 24% ( n = 534) were discharged home. In multivariable analysis, the following predictors were identified 1) weight less than 5 kg and 5-9.9 kg, 2) presence of systemic illness, 3) recent cardiac intervention less than 90 days, and 4) ICU Admission Tool for Congenital Heart Catheterization case type risk categories (1-5), with C -statistics of 0.79 and 0.76 in the derivation and testing cohorts, respectively. The addition of the PCS feature fit into the final model resulted in a C -statistic of 0.79. CONCLUSIONS: The creation of a validated pre-procedural risk prediction model for ICU admission following congenital cardiac catheterization using a large volume, single-center, academic institution will improve resource allocation and prediction of capacity needs for this complex patient population.