Case-control study reveals a four-variable discriminant model classifying ischemic cerebrovascular disease in men, highlighting key metabolic and vascular predictors.
Sixty-one men with ischemic thrombotic cerebrovascular disease (ITCVD) and 61 age-matched controls (±three years) were studied to select risk factors which would identify ITCVD-prone individuals from a healthy population. Numerous clinical and biochemical measurements were made on all subjects including a three-hour oral glucose tolerance test concomitant with the immunoreactive insulin response (IRI). The following parameters were selected as risk factors for ITCVD from the many variables assessed: elevated systolic blood pressure; triglycerides; uric acid; glucose one-hour, two-hour and three-hour levels; and IRI two-hour and three-hour levels. There is also a higher prevalence of abnormal lipoproteins (mostly type IV), abnormal EKG, and hypertension in ITCVD. A stepwise linear discriminant function analysis was used to select the risk factors which best separate and classify the ITCVD and control subjects. These primary risk factors are the IRI three-hour level, systolic blood pressure, abnormal lipoproteins, and glucose two-hour level. Utilizing only these four primary risk factors in a discriminant function, 84.4% of the subjects were correctly classified. The contribution of the other variables is minimal in the discriminant function, but they are applicable as individual risk factors of ITCVD.
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Gertler et al. (1972) studied this question.
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