Development and Validation of a Predictor Equation to Detect Hypertensive Risk Population

Abstract

Background: Primary prevention model has been the major arena of treatment modality in the modern medicine. Strategizing towards this, a predictor equation to identify the risk population of hypertensives was computed in this study.

Method: Our study included 80 hypertensives and 40 normal subjects and it was a case control study. This study was done among both genders selected from Indian population. Strict inclusion and exclusion criterion were framed.Parameters such as height, weight, body mass index, systolic blood pressure, diastolic blood pressure and total leucocyte count were estimated. The controls were age and sex matched and selected from the normal population.

Result: Statistical Discriminant analysis was done using our data to derive an equation to identify the risk population of hypertension. The stepwise discriminant analysis identified four variables: Diastolic blood pressure, Total count, Weight and Age as significant contributing factors for hypertension. The discriminant function correctly assigned 79 out of 80 Cases (98.8% accuracy), and 38 out of 40 Controls (95% accuracy), the overall accuracy of prediction in assigning a person as a hypertensive or normal was 97.5%.

Conclusion: Applying translational significance to research is of utmost important and the ease-of-use prediction formula is the need of the hour. This formula enhances identification of risk population of hypertensives in a simple clinic set up and its importance is ameliorated with the total count used in the formula, emphasizing the patho-inflammatory state in early stages of hypertension.