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[Models for calculating risks as a tool in screening for cardiovascular diseases].

T E Bryndorf1, H H Petersen, A Baastrup

  • 1Bispebjerg Hospital, København.

Ugeskrift for Laeger
|April 16, 1990
PubMed
Summary

Assessing ischemic heart disease risk models showed moderate agreement between American, British, and Swedish approaches. Researchers suggest caution in risk scoring, recommending focus on established factors like cholesterol and smoking.

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Area of Science:

  • Cardiology
  • Epidemiology
  • Preventive Medicine

Background:

  • Ischemic heart disease (IHD) risk assessment is crucial for preventive cardiology.
  • Multiple risk prediction models exist, varying in their epidemiological basis and factors considered.
  • Validation of these models on local populations is essential for effective screening.

Purpose of the Study:

  • To evaluate and compare the performance of three distinct risk calculation models for ischemic heart disease.
  • To assess the agreement between American, British, and Swedish risk scoring systems using local patient data.
  • To determine the utility and limitations of current risk assessment models in a clinical screening setting.

Main Methods:

  • A screening study involving 462 participants was conducted.

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  • Risk models were applied to a subgroup of 275 individuals under 65 years old.
  • Plasma cholesterol levels and smoking habits were key data points collected.

    • Main Results:

    • Moderate agreement was observed between the three risk calculation models, with correlation coefficients ranging from 0.75 to 0.89.
    • The study identified 92 individuals (out of 275) with elevated cholesterol or significant smoking.
    • Discrepancies suggest potential limitations in the pathogenetic basis of some model factors.

    Conclusions:

    • Current risk scoring models for ischemic heart disease demonstrate moderate agreement but should be used cautiously.
    • The established causal links between IHD, cholesterol, and smoking support targeted screening and intervention for these factors alone.
    • Further research may be needed to refine risk prediction models based on pathogenetic understanding.