Localization of pain in suspected acute myocardial infarction in relation to final diagnosis, age and sex, and site and type of infarction

Objectives: cribe the localization of pain in consecutive patients admitted to the coronary care unit for possible acute myocardial infarction (AMI) and to relate it to the development of AMI, age, and gender. : ctive evaluation. g: enska Hospital, covering half the area of the city of Gِteborg, with half a million inhabitants. ts: undred three consecutive patients admitted to the coronary care unit for possible AMI between 24 and 87 years old with a mean age of 64 years. e Measures: zations of pain according to a self-constructed figure. Patients were approached between 1 and 14 days after onset of symptoms and asked to describe the localization of pain according to the figure, including nine positions on the chest, left and right arm, neck, and back. s: veloped in 50% of patients during the first 3 days in hospital. Patients in whom AMI developed localized their pain to an extent similar to those without AMI in seven of nine chest areas. However, patients with AMI reported pain in the upper right square of the chest more frequently (p<0.001) and in the middle left square of the chest less frequently (p<0.01) than did patients without AMI. Pain in both the right (p<0.001) and left arms (p<0.01) was more frequently reported by patients who had AMI. Among patients with AMI, women reported pain in the neck (p<0.05) and in the back (p<0.01) more frequently than did men. Compared with elderly patients, younger patients reported pain more frequently in the left arm (p<0.01), right arm (p<0.01), and neck (p<0.05). sions: consecutive patients with possible AMI admitted to the coronary care unit, patients who had confirmed AMI reported pain in both arms more frequently than did patients without AMI. However, both groups described their chest surface distribution of pain similarly in the majority of positions, thereby indicating that the localization of chest pain is of limited use in predicting which patients will eventually have AMI.