Time To Event And Disease Progression Modelling In Ischemic Stroke Using Pharmacometrics Approach - Abdelhamid, Elhefnawy Marwa Elsaeed (2023)
Hyperglycemia (HG) during acute stroke has been associated with worse outcomes, including unfavourable functional outcomes. A better understanding and awareness of HG patterns and the potential risk factors associated with HG, predictors of poor outcomes among patients with HG during an acute ischemic stroke (AIS), would help to guide acute stroke management and prevention of poor outcomes. Phase I in this thesis aimed to assess the predictors of HG during AIS, and predictors of unfavourable functional outcomes according to HG pattern among patients with HG during AIS. While phase II in this thesis aimed to quantify the rate of blood glucose (BG) changes over the first 72 hours of AIS among patients with HG by developing disease progression models using a pharmacometrics approach. From the acute state of ischemic stroke (IS), we are directing the study to the chronic phase of the IS. Recurrent stroke is another vital outcome parameter included in the goal of stroke management. Three time-to-event (TTE) models of recurrent IS after the index IS were developed in phase III to estimate the baseline hazard of recurrent IS during different time intervals. The data for phase I and phase II was extracted retrospectively from patients’ medical records. Data of patients with AIS admitted to Hospital Sultanah Nur Zahirah (HSNZ), Kuala Terengganu, Malaysia, from January 2017 to December 2020 were included in these phases.