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A prediction model for coronary artery diseases in elder patients undergoing operations for rheumatic heart valve disease: Establishment and assessment / 第二军医大学学报
Academic Journal of Second Military Medical University ; (12): 706-709, 2011.
Article in Chinese | WPRIM | ID: wpr-840029
ABSTRACT

Objective:

To screen the risk factors for coronary artery diseases (CAD) before undergoing operation for rheumatic heart valve disease(RHVD) in elder patients and to establish a logistic model for predicting CAD, so as to guide the selection of coronary angiography.

Methods:

A total of 585 elder patients who underwent routine coronary angiography before heart valve operations for RHVD during 1998-2009 were analyzed in the present study. Logistic regression was employed to screen the risk factors for CAD and to establish a bootstrap logistic regression model, with P<0.05 used for identifying the low-risk patients. The receiver operating characteristic (ROC) curves were used to compare the diagnosis efficacies of the established model and other similar models.

Results:

It was found that the independent predictors of CAD in elder RHVD patients included age, male sex, angina, hypertension, and hypercholesterolemia. A predicting logistic model was successfully established. According to the model, 155 patients were designated as low risk, with 4 (2.6%) complicated with single-vessel disease CAD. The model showed better discrimination efficacy compared with the existing ones, with the area under the ROC curve being 0.793.

Conclusion:

We have successfully established a predicting model for CAD in elder patients undergoing operation for RHVD, which may help to screen CAD in elder patients before receiving heart valve operations for RHVD.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study / Risk factors Language: Chinese Journal: Academic Journal of Second Military Medical University Year: 2011 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study / Risk factors Language: Chinese Journal: Academic Journal of Second Military Medical University Year: 2011 Type: Article