Performance of a diagnostic model for the presence of unruptured intracranial aneurysms in the general population

Abstract

AbstractBackgroundThe prevalence of unruptured intracranial aneurysms (UIAs) in the general population is 3%. Aneurysmal subarachnoid hemorrhage can be prevented by screening for UIAs followed by preventive treatment of identified UIAs. We developed a diagnostic model for presence of UIAs in the general population to help identify persons at high risk of having UIAs.MethodsBetween 2005-2015, middle aged and elderly participants from the population-based Rotterdam Study underwent brain magnetic resonance imaging at 1.5 Tesla, on which presence of incidental UIAs was evaluated. A multivariable logistic regression model with diagnostic markers sex, age, hypertension, smoking, hypercholesterolemia, diabetes, and alcohol, and their interactions, was developed. We corrected for overfitting using bootstrapping. Model performance was assessed with discrimination, calibration, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).Results5835 persons were included (55.0% women, mean age 64.9±10.9 years) with a 2.2% UIA prevalence. Sex, age, hypertension, smoking, diabetes, and interactions of sex with age, hypertension, and smoking were independent diagnostic markers. The resulting model had a c-statistic of 0.65 (95% confidence interval [CI] 0.60–0.68) and 56% sensitivity, 52% specificity, 98% PPV, and 3% NPV for UIA presence at a cut-off value of 4% prevalence. Because of interactions with sex, additional models for men and women separately were developed. The model for men had a c-statistic of 0.70 (95%CI 0.62–0.78) with age, hypertension, and smoking as diagnostic markers and comparable additional performance values as for the full model. The model for women had a c-statistic of 0.58 (95%CI 0.52–0.63) with smoking as the only diagnostic marker.ConclusionOur diagnostic model had insufficient performance to help identify persons at high risk of having UIAs in the general population. Rather, it provides insight in risk factors contributing to UIA risk and shows that these may be in part sex-specific.