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A risk scoring system for prediction of coronary heart disease based on multivariate analysis: development and
S P Zodpey1, H R Kulkarni, N D Vasudeo
1Department of Preventive and Social Medicine, Government Medical College, Nagpur.
Insights
A new risk scoring system effectively predicts coronary heart disease (CHD) risk. It identifies key factors like socioeconomic status, inactivity, diabetes, hypertension, and cholesterol for early prevention.
Area of Science:
- Cardiology
- Preventive Medicine
- Epidemiology
Background:
- Coronary heart disease (CHD) poses a significant public health challenge due to its multifactorial nature.
- Primordial prevention strategies are crucial for mitigating the growing burden of CHD.
- Existing risk assessment tools may require refinement for diverse populations.
Purpose of the Study:
- To develop and validate a novel risk scoring system for predicting coronary heart disease (CHD).
- To identify key modifiable and non-modifiable risk factors associated with CHD in a specific population.
- To establish a practical tool for early identification and prevention of CHD.
Main Methods:
- A pair-matched case-control study involving 154 cases and 154 matched controls.
- Analysis of various risk factors including socioeconomic status, lifestyle, medical history, and biochemical markers.
- Conditional multiple logistic regression and Receiver Operating Characteristic (ROC) curve analysis for risk factor identification and model validation.
Main Results:
- An additive risk scoring system was developed, identifying socioeconomic status, physical inactivity, diabetes mellitus, hypertension, and total serum cholesterol as significant predictors.
- Statistical weights were assigned to each factor: socioeconomic status (3), physical inactivity (5), diabetes mellitus (2), hypertension (4), and total serum cholesterol (5).
- A total score of 12 was determined as the cutoff point for increased CHD risk, with an initial predictive accuracy of 0.7962 (ROC AUC) and prospective validation accuracy of 0.6964.
Conclusions:
- The developed risk scoring system demonstrates promising predictive accuracy for coronary heart disease (CHD).
- The system highlights the importance of socioeconomic status, physical inactivity, diabetes, hypertension, and high cholesterol in CHD risk assessment.
- Further validation in large-scale population-based studies is recommended to assess its broader applicability and clinical utility.
Abstract:
Considering the multifactorial disposition and the need of primordial prevention of coronary heart disease (CHD), a risk scoring system for the prediction of CHD was devised at Govt Medical College, Nagpur, India. In this pair-matched case-control study of 154 cases and 154 age and sex matched controls, socioeconomic status, physical inactivity, family history of CHD, type A personality characteristic, cigarette smoking, alcohol consumption, body mass index, diabetes mellitus, hypertension, total serum cholesterol and oral contraceptive use (in women) were studied for association with CHD. The additive risk scoring system based on the results of conditional multiple logistic regression identified five factors, namely, socioeconomic status, physical inactivity, diabetes mellitus, hypertension and toal serum cholesterol with statistical weights of 3,5,2,4 and 5 respectively. On back-validation using receiver operating characteristic (ROC) curve, a total score of 12 was found to be the cut off point above which there was increased risk of CHD. The overall predictive accuracy of this system-equivalent to the area under the ROC curve-was 0.7962 (95% Confidence Interval 0.7468-0.8455). On prospective validation using a separate group of 140 cases and 140 controls, the predictive accuracy was found to be 0.6964 (95% Confidence Interval 0.6341-0.7587). Future studies need to assess the risk scoring system in population based studies.
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