Related Experiment Video
Updated: Feb 5, 2026
Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
Published on: August 9, 2024
Validation and refinement of the catheterization RISk score for pediatrics (CRISP score): An analysis from the
Kevin D Hill1,2, Wei Du3,4, Gregory A Fleming1,2
1Department of Pediatrics, Duke University Medical Center, Durham, North Carolina.
Insights
The revised CRISP score (rCRISP) accurately predicts serious adverse events (SAEs) in pediatric catheterization. This pre-procedural risk model offers improved clinical utility for patient care.
Area of Science:
- Cardiovascular Interventional Medicine
- Pediatric Cardiology
- Medical Risk Prediction Models
Background:
- The original CRISP score estimates risk of serious adverse events (SAEs) in pediatric catheterization.
- External validation and potential refinement of the CRISP score are needed to enhance its clinical utility.
Purpose of the Study:
- To externally validate the existing CRISP score.
- To determine if a revised CRISP score (rCRISP) with pre-procedural data improves clinical utility for pediatric catheterization risk assessment.
Main Methods:
- A large dataset (n=29,830) of pediatric catheterization procedures was divided into development and validation sets.
- The CRISP score was refitted, and a revised score (rCRISP) using only pre-procedural data was developed.
- Model fit and risk prediction were compared using statistical criteria (AIC, BIC, N2LL, C-statistic, chi-square).
Main Results:
- Both CRISP and rCRISP scores demonstrated good prediction of SAEs, with observed-to-predicted ratios between 0.71 and 1.18.
- The rCRISP score, using entirely pre-procedural data, showed slightly less optimal model fit but comparable risk prediction to the original CRISP score.
- SAE frequency increased significantly across risk categories, from 1.08% to 27.34%.
Conclusions:
- The CRISP score is a reliable tool for predicting procedural risk in pediatric catheterization.
- The revised rCRISP score, utilizing solely pre-procedural data, offers comparable risk prediction and enhanced clinical utility.
Objectives:
To externally validate the CRISP score, and determine if refinements might improve clinical utility.
Background:
The CRISP score estimates risk of serious adverse events (SAEs) for pediatric catheterization.
Methods:
Pediatric (age < 18) procedures reported to the Congenital Cardiovascular Interventional Study Consortium registry from 05/08 to 09/17 (n = 29,830, 27 centers) were divided into a development dataset of 14,784 earlier procedures, and a validation dataset of 15,046 more recent procedures. The development dataset was used to refit the original CRISP model, and to develop a revised(r) CRISP score, consisting of entirely pre-procedurally collected data. The validation dataset was then used to compare model fit and risk prediction between CRISP, rCRISP and two existing risk scores using Akaike's (AIC), Schwarz's (BIC) Bayes Information Criteria, -log Likelihood (N2LL), area under the receiver operator curve and chi-square goodness-of-fit statistic (across 5 risk categories).
Results:
Overall 4.31% of patients experienced at least one SAE with frequency increasing from 1.08% in CRISP category 1 to 27.34% in category 5. Both CRISP and rCRISP (entirely pre-procedural) predicted risk of SAEs well, with observed to predicted ratios ranging from 0.71 to 1.18 across the 5 risk categories. Compared to the original CRISP score, rCRISP demonstrated less optimal model fit (higher AIC, BIC, and N2LL) but similar risk prediction (C-statistic = 0.71 vs. 0.70; chi-squared statistic = 6.77 vs. 6.85).
Conclusion:
The CRISP score accurately predicts procedural risk. With minor modifications, the revised version (rCRISP) performed well with arguably greater clinical utility as an entirely preprocedural risk model.
Related Concept Videos
01:06Introduction to z Scores
z scores...
01:05Introduction to z Scores
z scores...
01:17z Scores and Area Under the Curve
01:25Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT
01:07z Scores and Unusual Values
This score indicates how far a value is from the mean in terms of standard deviation. For example, if a data value has a z score of +1, the researcher can infer that the particular data value is one standard deviation above the mean. If another data...
01:21Cardiac Catheterization II: Right Heart Catheterization