Predictive model of recurrent ischemic stroke: model development from real-world data

Area of Science:

• Neurology
• Epidemiology
• Clinical Research

Background:

• Established correlations exist between risk factors and ischemic stroke (IS) recurrence.
• The dynamic nature of IS recurrence hazard over time requires further investigation.
• Understanding baseline hazard and secondary prevention's impact is crucial for managing IS recurrence.

Purpose of the Study:

• To quantify the hazard of recurrent IS with no influence from variable predictors.
• To assess the impact of secondary prevention on the hazard of recurrent IS.
• To model the time-dependent hazard of recurrent ischemic stroke.

Main Methods:

• Utilized data from 7,697 patients with a first IS from the Malaysian National Neurology Registry (2009-2016).
• Developed a time-to-recurrent IS model using NONMEM version 7.5.
• Selected the best-fitting Gompertz hazard model based on maximum likelihood estimation, clinical plausibility, and visual predictive checks.

Main Results:

• 333 patients (4.32%) experienced recurrent IS within 7.37 years.
• The hazard of recurrent IS was 0.238 within the first 6 months, decreasing to 0.001 thereafter.
• Hyperlipidemia, hypertension, and ischemic heart disease increased IS recurrence hazard, while antiplatelets reduced it.

Conclusions:

• The magnitude of recurrent IS hazard varies significantly over time.
• Concomitant risk factors and secondary prevention strategies influence the time-dependent hazard of recurrent IS.
• This study quantifies the evolving risk of recurrent stroke, informing clinical practice.