Abstract 4137570: Atherosclerotic Cardiovascular Disease Risks in Children: An electronic health record data analytics approach

Background and Aims: There is little data on atherosclerotic cardiovascular disease (ASCVD) risk conditions, factors, and tiers in the pediatric population. This study aimed to develop and validate electronic health record (EHR) data analytic algorithms to attain the prevalence of 24 risk conditions, 7 factors, and 4 tiers in children in a rural community. Methods: This study included all the 495,902 subjects from 0 to 18 years at the Geisinger Medical Center from 2004 to 2022. The demographic and clinical data were collected using ICD-10 codes, clinical and laboratory data, and a dual-coded computational algorithm was developed based on the AHA guideline to derive the ASCVD risk conditions, factors, and tiers. To validate the EHR algorithms, the algorithm (rater 1) and a clinician (rater 2) extracted and analyzed the data from 40 randomly selected subjects from this cohort. Kendall’s coefficient of concordance (W) and Gwet’s agreement coefficient were used to evaluate algorithm and clinician agreement within the ASCVD tiers, conditions and factors, respectively. Results: High concordance was observed between algorithmic and clinician raters for risk tiers (W=80%), conditions (80-97%), and factors (49% for blood pressure, and 92% to 97% for the rest of the risk factors). In this cohort, the median age was 3.9 years, 51.0% were male, 80.6% were Non-Hispanic/Latino, and 88.1% were White. Overall, 15.5% (N = 76,945) were at-risk, 7.0% (N = 34,530) at moderate risk, and 4.2% (N = 20,761) at high risk for ASCVD, respectively. The most prevalent risk conditions were obesity (9.1%, N = 45,074), chronic inflammatory conditions (6.8%, N = 33,685), severe obesity (2.7%, N = 13,442), insulin resistance with comorbidities (2.7%, N = 13,397), and hypertension (2.1%, N = 10,436). The most prevalent risk factors were elevated BMI (27.4%, N = 135,904), blood pressure (12.5%, N = 62,015), and fasting lipid profile (8.7%, N = 43,100). Conclusion: Our EHR data analytics algorithm is in high agreement with the clinician rater. The high, moderate, and at-risk ASCVD risk tiers are prevalent in a large contemporary pediatric cohort at Geisinger. Both ASCVD risk conditions and factors are also prevalent, especially obesity, diabetes, hypertension, and hyperlipidemia. These findings suggest the further application and refinement of these algorithms to design innovative approaches for ASCVD risk reduction and prevention in children.