Objective: This study aimed to develop and validate a prognostic model for the 1-year risk of late poststroke epilepsy (PSE).
Materials and methods: We included patients initially diagnosed with ischemic stroke between 2003 and 2014 in a National Health Insurance claims-based cohort in Taiwan. Patients were further divided into development and validation cohorts based on their year of stroke diagnosis. Multivariable Cox regression with backward elimination was used to analyze the association between 1-year PSE and risk factors before and on stroke admission.
Results: In total, 1,684 (1.93%) and 725 (1.87%) ischemic stroke patients comprising the development and validation cohorts, respectively, experienced late PSE within 1 year after stroke. Seven clinical variables were examined to be independently associated with 1-year risk of PSE. We developed a risk score called "PSEiCARe" ranging from 0 to 16 points, comprising the following factors: prolonged hospital stay (>2 weeks, 1 point), seizure on admission (6 points), elderly patients (age ≥80 years, 1 point), intensive care unit stay on admission (3 points), cognitive impairment (dementia, 2 points), atrial fibrillation (2 points), and respiratory tract infection (pneumonia) on admission (1 point). Patients were further classified into low-, medium-, high-, and very-high-risk groups. The incidence (per 100 person-years) was 0.64 (95% CI: 0.56-0.71) for the low-risk, 2.62 (95% CI: 2.43-2.82) for the medium-risk, 10.3 (95% CI: 9.48-11.3) for the high-risk, and 28.2 (95% CI: 24.0-33.0) for the very-high-risk groups. Discrimination and calibration were satisfactory, with a Harrell's C of 0.762 in the development model and 0.792 in the validation model.
Conclusion: PSEiCARe is an easy-to-use prognostic score that integrates patient characteristics and clinical factors on stroke admission to predict 1-year PSE risk; it has the potential to assist individualized patient management and improve clinical practice, thereby preventing the occurrence of late PSE.
Keywords: claim analysis; population-based; poststroke epilepsy; prediction model; risk score.