Demographic characteristics and comorbidities of patients with narcolepsy: a propensity-matched cohort study

Abstract

Study Objectives: Narcolepsy has a complex phenotype owing to differences in symptomatology, disease severity, and comorbidities. This is the first study to use aggregate electronic health record (EHR) data and natural language processing (NLP) algorithms to characterize the demographics and comorbidities of a large cohort of patients with narcolepsy. Methods: First-time Mayo Clinic patients (2000-2020) who had ≥1 narcolepsy-specific ICD-9/10 code and ≥1 disease-supportive statement in the clinical notes (identified using an NLP algorithm) were identified. A control cohort was propensity matched for birth year, age at first institutional encounter, sex, race, ethnicity, number of diagnosis codes, and mortality. Common comorbidities were compared and ranked between cohorts. Results: In the EHR database (N = 6 389 186 patients), 2057 patients with narcolepsy were identified (median age, 32 years; 59.6% female; 92.6% white; and 89.2% non-Hispanic) and propensity matched with a control cohort. Among the top 20 comorbidities occurring more frequently in the narcolepsy cohort compared with the control cohort (odds ratio [OR], 1.67-3.94; p