Atherosclerotic heart disease is the number one cause of death. Methods of detecting coronary artery disease prior to fatal events are needed so that appropriate measures can be taken to reduce risk. Anatomic studies have established that coronary calcification is invariably located near areas of advanced atherosclerotic disease. A direct relation between the extent of coronary calcification and the severity of stenotic lesions or frequency of myocardial infarction is consistently observed in autopsy series. The more extensive the calcification, the more frequent and more severe the degree of stenosis. This relationship is recognized in all age groups and both sexes, but is more marked in younger patients.
CT and in particular, electron-beam CT (EBCT) is the most sensitive radiographic method to detect coronary artery calcification. The value of EBCT can be summarized as follows:
Absence of Detectable Coronary Artery Calcification EBCT*
Does not absolutely rule out the presence of atherosclerotic plaque, including unstable plaque
Highly unlikely in the presence of significant luminal obstructive disease
Observation made in the majority of patients who have had both angiographically normal coronary arteries and EBCT scanning
Testing is gender independent
May be consistent with a low risk of a cardiovascular event in the next 2-5 years
Presence of Detectable Coronary Artery Calcification EBCT*
Confirms the presence of coronary atherosclerotic plaque
The greater the amount of calcification (i.e., calcium area or calcium score), the greater the likelihood of obstructive disease, but there is no one-to-one relation, and findings may not be site specific
Total amount of calcification correlates best with total amount of atherosclerotic plaque, although the true "plaque burden" is underestimated
A high calcium score may be consistent with moderate to high risk of a cardiovascular event within the next 2-5 year
Prediction of Coronary Heart Disease For the prior probability of coronary artery disease, the above model uses age, gender and clinical presentation. Other predictive models could be used for prior probability. Based on data from the Framingham Study, predictive models have been derived from the blood pressure, total cholesterol, LDL cholesterol, and HDL cholesterol, diabetes, smoking, gender and age. To calculate risk based on these models choose one of the following.
From 6 participating centers, EBCT used in 709 patients (427 with angiographic significant disease). Likelihood ratios (95% confidence interval) calculated from data provided in Table 2.
Note that in older subjects, the presence of calcium does not raise the likelihood of significant coronary artery disease as much as it does in younger patients. Conversely note that the absence of calcium markedly decreases the likelihood of coronary artery disease in the older patient population.
Likelihood ratios for coronary artery calcification and significant coronary artery disease (>70% stenosis)
From 5 institutions, EBCT used in 491 symptomatic patients (211 (43%) with angiographic disease). Likelihood ratios (95% confidence interval) calculated from data provided in Table 2. As with Budoff, the absence of calcium does not rule out disease. The presence of calcium is most helpful in the younger subjects
Prevalence of Coronary Artery Disease in Symptomatic Patients
Likelihood ratios in (), adapted from Diamond and Forrester
Nonanginal Chest Pain
Atypical Angina
Typical Angina
Age
Men
Women
Men
Women
Men
Women
30-39
5.2 (0.05)
0.8 (0.008)
21.8 (0.28)
4.2 (0.04)
69.7 (2.3)
25.8 (0.35)
40-49
14.1 (0.16)
2.8 (0.03)
46.1 (0.86)
13.3 (0.15)
87.3 (6.9)
55.2 (1.23)
50-59
21.5 (0.27)
8.4 (0.09)
58.9 (1.43)
32.4 (0.48)
92 (11.5)
79.4 (3.85)
60-69
28.1 (0.39)
18.6 (0.23)
67.1 (2.0)
54.4 (1.19)
54.4 (1.19)
90.6 (9.64)
Typical angina: discomfort
1) in the anterior chest, neck, shoulders, jaw, or arms,
2) precipitated by physical exertion or psychic stress,
3) relieved by rest or nitroglycerin within minutes.
Atypical angina: 2 of 3 features
Nonanginal chest pain: < 2 features
The prevalence of disease is higher in men and increases with age. Patients with symptoms, especially typical angina increases the likelihood of malignancy. These relationships may be explored using the calculator.
After a two-week trial, a Sedgwick County, Kansas, jury returned a verdict in favor of the surviving spouse and two children of a 37-year-old assembly line worker. The jury found the defendant physician at fault for damages of $750,000. There is a big difference between a doctor who goes through the motions of collecting facts and ordering tests, and one who truly understands the significance of those facts and the implications of the test results. The plaintiff experienced classic angina. At the Emergency Room MI was excluded leaving angina (myocardial ischemia) at the top of the differential diagnosis. The defendant-internist admitted the patient for further evaluation. A stress test was performed and was negative. On the basis of a normal stress test, the physician explained that nothing in the test indicated ischemia. Whatever caused the chest pain was not related to the heart. Seven days the plaintiff collapsed and died at work. At autopsy, all three major coronary arteries evidenced significant obstruction. At trial, the defendant's position, which had support in the literature, was that the hospital evaluation was appropriate and complete, and a negative treadmill test after 12 minutes of exercise justified discharging the patient back to normal activity. Plaintiffs' position was that, while the defendant went through all of the proper motions, collected most of the important information, and did an acceptable test, he had a fundamental and dangerous lack of understanding the information from the test. The defendant did not understand the principle of Bayes Theorem. Bayes Theorem is part of the medical standard of care. The physician who understands the limitations of the treadmill stress test and the principles of Bayesian analysis is never justified in reassuring a patient that typical angina is not caused by coronary artery disease. In every case where a diagnosis is missed, justified on the basis of a test result, it is important to find out what the sensitivity and specificity of the test is, and how Bayesian analysis comes into play to determine the posttest likelihood of disease, notwithstanding a negative test result.
Information provided is not intended to be medical or technical advice. The information given at this site is for educational purposes only and is not sufficient for medical decisions. I disclaim any liability for the acts of any physicians or any other individual who receives any information on any medical procedure through this web site. I accept no legal responsibility for any injury and/or damage to persons or property from any of the suggestions or material discussed herein.