Exploring Factors Influencing Stroke Risk: Insights From a Predictive Analysis.

Abstract

Introduction Stroke is a serious medical condition characterized by the sudden interruption of blood flow to the brain, resulting in the death of brain cells. It is a leading cause of long-term disability and mortality worldwide. Stroke has some associated risk factors, both modifiable and non-modifiable ones.As for non-modifiable risk factors, these are age, gender (men are more vulnerable), and family history of stroke.The controllable or adjustable risk factors include hypertension (high blood pressure), diabetes, smoking, high cholesterol levels, obesity, and insulin resistance. Methods In our study, we collected data from 229 patients which were originally collected for clinical purposes and were retrospectively analyzed. These data contain features such assex and age, the presence of ischemic heart disease (IHD) or stroke history, and different blood sugar readings. These measurements include fasting blood sugar (FBS), postprandial blood sugar (PPBS), HbA1c%, and insulin levels (fasting and postprandial).Furthermore, cholesterol was also tested, such as total cholesterol, triglycerides (TGL), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and very low-density lipoprotein (VLDL). Surprisingly, stroke was observed in 24of the 205 patients. This contrast permits us to be concerned with the chance of the association between stroke and insulin levels. Given the imbalanced nature of our outcome variable (stroke occurrence), the primary analytical method will be logistic regression. Results In this cross-sectional study, we investigated the association between high insulin levels (both fasting and postprandial) and the occurrence of stroke within a dataset of 229 patients. Out of the 229 included cases, 102 individuals were female (44.5%) and 127 individuals were male (55.5%). Twenty-four cases have ischemic heart disease (10.5%). Among the analyzed cases, 24 individuals have a history of stroke. The average age of the sample is approximately 57 years ± 14.87. There was no significant difference between the males and females in most of the descriptive statistics. However, females experienced significantly higher levels of postprandial glucose level and significantly lower levels of postprandial insulin. According to our predictive model, we found that an increase in fasting insulin levels was linked to a lower risk of stroke occurrence. On the other hand, increasing insulin postprandial levels and age were associated with an increased risk of stroke. Conclusion Our study identified age, fasting insulin, and postprandial insulin as key factors influencing stroke risk. Higher fasting insulin levels were associated with reduced risk, while increased postprandial insulin and age were linked to higher risk. Blood glucose, cholesterol, and triglycerides had minor effects. Notably, higher total cholesterol and triglyceride levels were slightly associated with lower stroke occurrence. Further research with larger samples is needed for validation.