Individual prediction of motor vehicle accidents for patients with epilepsy

The objective of the study was to design a clinically useful tool to predict the risk of seizure-related motor vehicle accidents (MVAs) for people with epilepsy (PWE). Participants were patients who visited our epilepsy center in West China Hospital from October 2012 to October 2019 and were divided into a primary cohort and a validation cohort. Ultimately, we included 525 patients in the primary cohort and 86 patients in the validation cohort. Proportional hazard regression was performed to measure the prognostic factors of car accidents. The outcome was used to create a nomogram model. The final model had 7 factors, with a C-index of 0.85 (95% CI, 0.80-0.91), to predict the possibility of non-MVA for PWE. For the validation cohort, the C-index was 0.83 (95% CI, 0.72-0.95). This nomogram model can offer more individualized advice to PWE who are still driving by estimating the risk of car accidents. (C)2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

The study aimed to design a tool to predict seizure-related motor vehicle accident risks for people with epilepsy. By conducting proportional hazard regression, a nomogram model with 7 factors and a high C-index was created to provide personalized advice for patients.