Objectives

Lipid lowering therapy (LLT) of patients with FH has not been well described in Canada in part due to limitations of traditional administrative Canadian databases. The advent of electronic medical records (EMRs) and NLP methods represent a novel and efficient method for evidence generation. Using NLP tools for data extraction, we describe selected characteristics and treatment patterns of patients with FH in Canada.

Methods

EMRs of patients (n=445) with FH and with >1 physician visit between June 2016 to November 2019 with >1 year of follow up were queried using NLP of structured and unstructured data to extract demographic and clinical variables. Extraction of patient files occurred in cardiology (95% of patients) and internal medicine (5% of patients) practices (n=53) across 4 Canadian provinces. An explicitly stated diagnosis of FH in the EMR was required for patients to be eligible.

Results

Patients had a mean (SD) age of 55(12) years; 10.8% were ≥70 years; 53.5% were female. Mean BP was 128/78 mm Hg. Hypertension and diabetes were present in 37% and 9% of patients. Statins, ezetimibe, and PCSK9i were documented in 47%, 18%, and 3% of patients, respectively (baseline). Statin intolerance was documented in 21% of patients. LDL-C values were available in 77% of patients at baseline with a mean of 3.8 (1.6) mmol/L. 75% of patients had LDL-C >2.5mmol/L at baseline. Treatment modifications occurred in 31% of patients with uncontrolled LDL-C. Treatment modifications were as follows: addition/switching of statins (27%), ezetimibe (38%) and PCSK9i (15%). Despite changes in LLT, LDL-C remained above >2.5mmol/L in 52% of patients.

Conclusions

NLP was an effective method to efficiently identify and assess current treatment patterns of patients with FH. This study demonstrates that a significant number of patients with FH are not optimally treated despite the use of current available therapies.