Related Experiment Video
Updated: Jul 9, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Usefulness of PREDIC3T Case Type Risk Category in the CRISP Registry
Daisuke Kobayashi1, Elena K Amin2, Gareth J Morgan3
1Division of Cardiology, Department of Pediatrics, St. Louis Children's Hospital / Washington University School of Medicine, St. Louis, Missouri.
Abstract:
Procedural risk in Congenital Cardiac Catheterization (PREDIC3T) was recently reported as the contemporary procedure-type risk metric by the Congenital Cardiac Catheterization Project on Outcomes (C3PO) registry. The usefulness of this metric has not been evaluated elsewhere. The CRISP registry of Congenital Cardiovascular Interventional Study Consortium (CCISC) data set was analyzed. The study period was 14 years (2009 to 2022). The primary outcome was significant adverse event (SAE). Cases were assigned to the 6 PREDIC3T risk categories. Univariate and multivariable logistic regression models were used to evaluate the association between PREDIC3T and the primary outcome. The model discriminative performance was evaluated by the c-statistic. In a total of 64,419 enrolled cases, PREDIC3T case types were assigned in 59,822 cases (93%). The frequency for PREDIC3T category was 0 = 7,494 (12.5%), 1 = 16,932 (28.3%), 2 = 17,023 (28.5%), 3 = 9,885 (16.5%), 4 = 4,403 (7.4%), and 5 = 4,085 (6.8%). SAE was observed in 2,474 cases (4.1%). The SAE rates for category were 0 = 1.0%, 1 = 2.3%, 2 = 4.0%, 3 = 6.2%, 4 = 8.2%, and 5 = 9.0%. In a multivariable model, PREDIC3T case type risk category (odds ratios for category: 0 = 0.49, 1 = 1.00, 2 = 1.40, 3 = 2.06, 4 = 2.79, and 5 = 3.15; p <0.001) were significantly associated with SAE (c-statistic of 0.707) after adjusting for age, preprocedural inotropic support and systemic illness, low systemic saturation, high pulmonary vascular resistance, and the use of general anesthesia. The PREDIC3T case type risk category was associated with the risk of SAE in the CRISP registry data set and appeared to be a useful procedural risk classification tool.
More Related Videos
07:31Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
06:16Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
Published on: August 9, 2024
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Relative Risk
Receiver Operating Characteristic Plot
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...
Hazard Ratio
For example, in a clinical trial...
Critical Region, Critical Values and Significance Level
In hypothesis testing, a sample statistic is converted to a test statistic using z, t, or chi-square distribution. A critical region is an area under the curve in probability distributions demarcated by the critical value. When the test statistic falls in this region, it suggests that the null hypothesis must be rejected. As this region contains all those values of the...