Arq. Bras. Cardiol. 2020; 114(6): 992-994
Why We Build Models – From Clinical Cardiology Practice to Infectious Disease Epidemics
Francisco, 64 years old, comes to your office for a preventive health evaluation. He has a history of well-controlled hypertension and is otherwise well. His past medical history is unremarkable. No family history of cardiovascular disease or smoking and LDL-cholesterol (LDL-C) of 90 mg/dL. After discussing with the patient, you are unsure if this patient’s risk benefit profile would favor the use of statins. Instead of trusting your personal feelings, you decide to use the Framingham risk score (FRS) to decide if statins would be recommended. The calculated Framingham score is 8.1% and you decide not to initiate statins at this point.
One month later, Francisco returns to your office with typical angina on major exertion but has no signs of unstable disease. Once again, to avoid overconfidence on your initial impression, you decide to use the Diamond and Forrester (DF) chest pain prediction rule, which estimates the pretest probability of obstructive coronary artery disease (CAD). For a male at his age, the rule suggests a pretest probability of 94% (high probability), so you decide to request an invasive angiography in the outpatient setting.
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