Predictive model of recurrent ischemic stroke: model development from real-world data - Elhefnawy, Marwa Elsaeed; Sheikh Ghadzi, Siti Maisharah; Albitar, Orwa; Tangiisuran, Balamurugan; Zainal, Hadzliana; Looi, Irene; Sidek, Norsima Nazifah; Aziz, Zariah Abdul; Harun, Sabariah Noor (Frontiers in Neurology, 2023)
Background: There are established correlation between factors and ischemic stroke (IS) recurrence, however does the hazard of recurrent IS change over time? What is predicted baseline hazard of IS recurrence if there is no influence of variable predictors? This study aimed to quantify the hazard of recurrent IS when the variable predictors set to zero and quantify the secondary prevention influence on the hazard of recurrent ischemic stroke. Methods: This was a population cohort study extracted data of 7697 patients with a history of first IS attack registered with National Neurology Registry of Malaysia from year 2009 to 2016. A time to recurrent IS model was developed using NONMEM version 7.5. Three baseline hazard models were fitted into the data. The best model was selected using maximum likelihood estimation, clinical plausibility and visual predictive checks. Results: Three hundred and thirty-three (4.32%) patients developed at least one recurrent IS within the maximum 7.37 years follow-up. Gompertz hazard model described the data well. The hazard of recurrent IS was predicted to be 0.238 within the first 6 months after the index IS and reduced to be 0.001 six months after the index attack. The presence of typical risk factors such as hyperlipidemia (HR, 2.22 (95%CI: 1.81-2.72)), hypertension (HR, 2.03(95%CI: 1.52-2.71)), and ischemic heart disease (HR,2.10(95%CI: 1.64-2.69)) accelerated the hazard of recurrence IS. While receiving antiplatelet (APLT) upon stroke decreased this hazard (HR,0.59(95%CI: 0.79-0.44)). Conclusion: The hazard of IS recurrence magnitude is different during different time intervals based on the concomitant risk factors and secondary prevention.