Multivariate prediction of major adverse cardiac events after 9914 percutaneous coronary interventions in the north west of England. Issue 5 (13th September 2005)

• Record Type: Journal Article
• Authors: Grayson, A D; Moore, R K; Jackson, M; Rathore, S; Sastry, S; Gray, T P; Schofield, I; Chauhan, A; Ordoubadi, F F; Prendergast, B; Stables, R H
• Other Names: group-author.
• Is Part Of: Heart. Volume 92:Issue 5(2006)
• Page Start: 658
• Page End: 663
• Publication Date: 2005-09-13
• Subjects: AHA, American Heart Association -- CABG, coronary artery bypass grafting -- CCAD, Central Cardiac Audit Database -- MACE, major adverse cardiac events -- MI, myocardial infarction -- NHS, National Health Service -- NWQIP, North West Quality Improvement Programme in Cardiac Interventions -- NYHA, New York Heart Association -- PCI, percutaneous coronary intervention -- ROC, receiver operating characteristic; major adverse cardiac events -- percutaneous coronary interventions -- risk prediction; Heart -- Diseases -- Treatment -- Periodicals; Cardiology -- Periodicals; 616.12
• DOI: 10.1136/hrt.2005.066415
• Languages: English
• ISSNs: 1355-6037

Abstract

Abstract : Objective: To develop a multivariate prediction model for major adverse cardiac events (MACE) after percutaneous coronary interventions (PCIs) by using the North West Quality Improvement Programme in Cardiac Interventions (NWQIP) PCI Registry. Setting: All NHS centres undertaking adult PCIs in north west England. Methods: Retrospective analysis of prospectively collected data on 9914 consecutive patients undergoing adult PCI between 1 August 2001 and 31 December 2003. A multivariate logistic regression analysis was undertaken, with the forward stepwise technique, to identify independent risk factors for MACE. The area under the receiver operating characteristic (ROC) curve and the Hosmer-Lemeshow goodness of fit statistic were calculated to assess the performance and calibration of the model, respectively. The statistical model was internally validated by using the technique of bootstrap resampling. Main outcome measures: MACE, which were in-hospital mortality, Q wave myocardial infarction, emergency coronary artery bypass graft surgery, and cerebrovascular accidents. Results: Independent variables identified with an increased risk of developing MACE were advanced age, female sex, cerebrovascular disease, cardiogenic shock, priority, and treatment of the left main stem or graft lesions during PCI. The ROC curve for the predicted probability of MACE was 0.76, indicating a good discrimination power. The prediction equation was well calibrated, predicting well at all levels of risk. Bootstrapping showed that estimates were stable. Conclusions: A contemporaneous multivariate prediction model for MACE after PCI was developed. The NWQIP tool allows calculation of the risk of MACE permitting meaningful risk adjusted comparisons of performance between hospitals and operators.