Regression Analysis of Sonographic Prediction of Cerebrovascular Accident in Nigeria

Abstract

The high mortality rate of cerebrovascular accidents (CVA) in Nigeria is due to its sudden onset and absence of prior awareness of risk factors. There is therefore the need to develop a predictive equation for the occurrence of stroke among subject. This study made up of 420 subjects, comprising 107 apparently healthy subjects and 313 patients with cardiovascular diseases. A cross section of 420 adults between ages 18years to 60years randomly selected under these categories was investigated. Anthropometric data, carotid artery dimensions and Doppler parameters were obtained on all the subjects. Data were analyzed using statistical tools, Pearson correlation analysis used to evaluate relationships. Regression analysis was used to generate a predictive model for estimation of CVA risk. The result show that apparently healthy subjects had the highest mean of the common carotid artery intima media thickness (CCA IMT) of 0.64mm 0.06mm while subjects at risk of cerebrovascular had 0.62m    0.07mm as the mean CCA IMT. The mean end diastolic velocity (EDV) of the apparently healthy subject was 13.96 ± 2.3 while the subjects at risk had 13.7 ± 25 as their mean EDV. The mean peak systolic velocity (PSV) of the apparently healthy subjects was -4.10 while the subjects at risk of cerebrovascular accident had – 1.73 as the mean PSV. Base on the findings there was a significant relationship among the obese, hypertensive, diabetic and apparently healthy subjects.