Development and Validation of a Prediction Model for Atrial Fibrillation Using Electronic Health Records

Abstract

Objectives: This study sought to determine whether the risk of atrial fibrillation AF can be estimated accurately by using routinely ascertained features in the electronic health record (EHR) and whether AF risk is associated with stroke.

Background: Early diagnosis of AF and treatment with anticoagulation may prevent strokes.

Methods: Using a multi-institutional EHR, this study identified 412,085 individuals 45 to 95 years of age without prevalent AF between 2000 and 2014. A prediction model was derived and validated for 5-year AF risk by using split-sample validation and model performance was compared with other methods of AF risk assessment.

Results: Within 5 years, 14,334 individuals developed AF. In the derivation sample (7,216 AF events of 206,042 total), the optimal risk model included sex, age, race, smoking, height, weight, diastolic blood pressure, hypertension, hyperlipidemia, heart failure, coronary heart disease, valvular disease, prior stroke, peripheral arterial disease, chronic kidney disease, hypothyroidism, and quadratic terms for height, weight, and age. In the validation sample (7,118 AF events of 206,043 total) the AF risk model demonstrated good discrimination (C-statistic: 0.777; 95% confidence interval [CI:] 0.771 to 0.783) and calibration (0.99; 95% CI: 0.96 to 1.01). Model discrimination and calibration were superior to CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology AF) (C-statistic: 0.753; 95% CI: 0.747 to 0.759; calibration slope: 0.72; 95% CI: 0.71 to 0.74), C₂HEST (Coronary artery disease / chronic obstructive pulmonary disease; Hypertension; Elderly [age ≥75 years]; Systolic heart failure; Thyroid disease [hyperthyroidism]) (C-statistic: 0.754; 95% CI: 0.747 to 0.762; calibration slope: 0.44; 95% CI: 0.43 to 0.45), and CHA₂DS₂-VASc (Congestive heart failure, Hypertension, Age ≥75 years, Diabetes mellitus, Prior stroke, transient ischemic attack [TIA], or thromboembolism, Vascular disease, Age 65-74 years, Sex category [female]) scores (C-statistic: 0.702; 95% CI: 0.693 to 0.710; calibration slope: 0.37; 95% CI: 0.36 to 0.38). AF risk discriminated incident stroke (n = 4,814; C-statistic: 0.684; 95% CI: 0.677 to 0.692) and stroke within 90 days of incident AF (n = 327; C-statistic: 0.789; 95% CI: 0.764 to 0.814).

Conclusions: A model developed from a real-world EHR database predicted AF accurately and stratified stroke risk. Incorporating AF prediction into EHRs may enable risk-guided screening for AF.

Keywords: atrial fibrillation; electronic health record; risk prediction; stroke.

Figure 1.. Flow diagram depicting patient inclusion.

AF = atrial fibrillation.

Figure 2.. Discrimination and calibration of scoring systems for predicting incident atrial fibrillation.

Panel A displays the C-statistic point estimate and 95% confidence interval for each of the three prediction models compared for predicting incident atrial fibrillation. Panels B-E display the predicted (x-axis) versus observed (y-axis) probability of incident atrial fibrillation for the EHR-derived score, CHARGE-AF score, C₂HEST, and CHA₂DS₂-VASc scores, respectively. For Panels B-E, the histograms represent the distribution of five-year predicted risk of atrial fibrillation. Perfect calibration is represented by the gray diagonal line through the origin. The black line corresponds to the observed calibration, and the orange line to the optimism-corrected calibration. Calibration slopes (and 95% confidence intervals) are depicted on the graphs. Calibration plots generated using the rms package (33). CHARGE-AF = Cohorts for Heart and Aging Research in Genomic Epidemiology Atrial Fibrillation; EHR = electronic health record.

Figure 3.. Cumulative incidence of atrial fibrillation and stroke stratified by five-year predicted risk of atrial fibrillation using EHR-derived score.

Cumulative incidence of A) atrial fibrillation, B) stroke, and C) stroke within 90 days of an atrial fibrillation diagnosis, stratified by five-year predicted risk of atrial fibrillation. Panel A includes all 206,043 individuals from the validation set, while panels B and C include 198,300 individuals without prevalent stroke.

Central Illustration.. Observed event rates stratified by predicted five-year risk.

Observed five-year incidence of atrial fibrillation, stroke, and stroke within 90 days of an atrial fibrillation diagnosis, stratified by percentage point increase in five-year predicted risk of atrial fibrillation. Five-year predicted risk of atrial fibrillation was rounded to the nearest whole number. Perfect correlation between predicted and observed atrial fibrillation incidence is represented by the gray line. Point estimates indicate observed five-year event risk, and bars represent 95% confidence intervals.