Abstract

Crohn's disease (CD) is a chronic illness that affects both the pediatric and adult populations with an increasing worldwide prevalence. We aim to identify a large, single-center cohort of patients with CD using natural language processing (NLP) in combination with codified data and extract surgical rates and medication usage from the electronic medical record (EMR). Patients with CD were identified from the entire Cleveland Clinic EMR using ICD codes and CD-specific terms identified by NLP to fit a logistic regression model. Cohorts were developed for pediatric-onset (younger than 18 years) and adult-onset (18 years and older) CD. Surgeries were identified using current procedural terminology (CPT) codes and NLP. Crohn's disease-related medications were extracted using physician orders in the EMR. Patients with pediatric-onset (n = 2060) and adult-onset (n = 4973) CD were identified from 2000 to 2017 with a positive predictive value of 98.5%. Rate of CD-related abdominal surgery over time was significantly higher in adult-onset compared with pediatric-onset CD (10-year surgery rate 49.9% vs 37.7%, respectively; P < 0.001). Treatment with biologics was significantly higher in pediatric vs adult-onset CD cohorts (63.6% vs 49.2%; P < 0.001). The overall rate of CD-related abdominal surgery was significantly higher in those who received <6 months of a biologic compared with ≥6 months of a biologic for both cohorts (pediatric 64.1% vs 39.1%, P ≤ 0.001; adult 69.3% vs 56.5%, P ≤ 0.001). Additionally, 60.9% in pediatric-onset CD and 43.5% in adult-onset CD treated with ≥6 months of biologic therapy have not required abdominal surgery. On multivariable analysis, perianal surgery was a significant risk factor for abdominal surgery in both cohorts. We used a combination of codified and NLP data to establish the largest, North American, single-center EMR cohort of pediatric- and adult-onset CD patients and determined that biologics are associated with lower rates of surgery over time, potentially altering the natural history of the disease.

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