Initial assessment of chest pain

The aim of this paper is to show the procedure with the patient presenting with anginal chest pain during every day clinical routine. Out of all patient presenting with chest pain, only 5.1% are with acute coronary syndrome (ACS), while half of the patients does not have a cardiac cause of the pain. So, we need to distinguish cardiac pain, or we shall make an emphasis on ischemic, from other forms. This pain judged by the patient description can be dubbed Typical anginal pain, or on the other hand what it was called atypical anginal pain, or so called “pain equivalent” e.g. like dyspnea. The pre-test probability (PTP) assessment is done based on: 1. The circumstances of pain onset (like physical exertion or emotional stress). 2. Localization of the pain (retrosternal) 3. Circumstances of pain cessation (rest or nitroglycerin intake). Based on these three characteristics we are judging the type of the pain. So, if we have only one criterion-the pain is not anginal pain., 2 criteria is dubbed like so called atypical anginal pain. And if we have all three presents, then this pain is called typical anginal pain. On the other hand, the numeric value of pre-test probability puts the patient into low, intermediate or high-risk group for coronary artery disease (CAD). So, the patients from the low-risk group can be excluded from further investigation. Intermediate group patients are pushed towards non invasive tests for CAD (physical exercise test, physical or pharmacological imaging tests (stress echocardiography, myocardial perfusion imaging). The patients from the high-risk group, high likelihood of CAD can be directly referred to invasive angiographic imaging. Based on the chest pain and ECG changes it is necessary to differentiate, whether we have a patient with acute coronary syndrome in our office, which would require urgent hospital treatment, or it is a patient with chronic coronary syndrome which would not require urgent treatment. Modern concept of chronic coronary syndrome diagnostic is characterized by diagnostic algorithm which is actually based on the above mentioned pre-test probability for CAD likelihood.