Article

Preoperative electrocardiograms: patient factors predictive of abnormalities.

Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, Boston, MA 02115, USA.
Anesthesiology (Impact Factor: 6.17). 06/2009; 110(6):1217-22. DOI: 10.1097/ALN.0b013e31819fb139
Source: PubMed

ABSTRACT Age is often the sole criterion for determining the need for preoperative electrocardiograms. However, screening electrocardiograms have not been shown to add value above clinical information. This study was designed to determine whether it is possible to target electrocardiograms ordering to patients most likely to have an abnormality that would affect management and if age alone is predictive of significant electrocardiograms abnormalities.
A list was developed of electrocardiograms abnormalities considered significant enough to impact management, as well as a list of patient factors believed to increase cardiovascular risk. electrocardiograms in all patients over 50 yr of age presenting for preoperative evaluation during a 2-month period were reviewed.
A total of 1,149 electrocardiograms were reviewed, with 89 patients (7.8%) having at least one significant abnormality. These patients were compared with a group of 195 patients who had electrocardiograms that did not contain significant abnormalities. Patients at higher risk of having a significantly abnormal electrocardiograms that would potentially affect management were those older than 65 yr of age or who had a history of heart failure, high cholesterol, angina, myocardial infarction, or severe valvular disease. Five patients (0.44%) had an abnormal electrocardiograms in the absence of risk factors. The sensitivity of the model is 87.6%.
Age greater than 65 yr remains an independent predictor for significant preoperative electrocardiograms abnormalities. The specific clinical risk factors that were found have a high sensitivity and identified all but 0.44% of patients with electrocardiograms abnormalities that may affect preoperative management.

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Available from: Lawrence C Tsen, Jun 02, 2015
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