Abstract 13196: The Prevalence and Prediction of Significant Coronary Artery Disease in Patients Referred for Valvular Heart Surgery
| Autor: | Jason M Lappe, Justin L Grodin, Yuping Wu, Corinne Bott-Silverman, Leslie Cho |
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| Rok vydání: | 2014 |
| Předmět: | |
| Zdroj: | Circulation. 130 |
| ISSN: | 1524-4539 0009-7322 |
| Popis: | Background: The guidelines recommend preoperative diagnostic coronary angiography (DCA) prior to valvular heart surgery (VHS) in men ≥35 years, premenopausal women with CAD risk factors ≥35 years, and postmenopausal women. Objectives: To determine the prevalence and risk factors for significant CAD in patients, without a prior history, undergoing DCA as a part of a preoperative evaluation for VHS. To create a risk prediction model to identify very-low risk patients. Methods: Patients undergoing DCA between 2/1/2004 and 10/1/2013 as a part of a preoperative evaluation for VHS were included. Significant CAD was defined as either ≥50% stenosis on DCA or the use of bypass grafting at the time of VHS. Multivariate analyses were used to determine risk factors for CAD. Patients were randomly split into derivation and validation cohorts. A nomogram was created to predict the risk of significant CAD, and the performance was assessed using a ROC curve. Results: We identified 5,360 patients (age 63±14 years, male 57%, diabetic 16%, hypertension 50%, hyperlipidemia 39%), of which 1,035 (19.3%) were found to have significant CAD. In multivariate analysis, age, gender, diabetes, renal dysfunction, hyperlipidemia and a family history of CAD were related to the presence of CAD (p Conclusions: In patients undergoing DCA prior to VHS, the prevalence of significant CAD is associated with demographics and traditional risk-factors, but not the specific dysfunctional valve. This data suggests there is a group with sufficiently low risk of significant CAD to merit non-invasive testing instead of DCA. The risk prediction nomogram created in this study can be used to identify patients with a very-low risk of significant CAD. |
| Databáze: | OpenAIRE |
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