PT  - JOURNAL ARTICLE
AU  - A D Grayson
AU  - R K Moore
AU  - M Jackson
AU  - S Rathore
AU  - S Sastry
AU  - T P Gray
AU  - I Schofield
AU  - A Chauhan
AU  - F F Ordoubadi
AU  - B Prendergast
AU  - R H Stables
TI  - Multivariate prediction of major adverse cardiac events after 9914 percutaneous coronary interventions in the north west of England
AID  - 10.1136/hrt.2005.066415
DP  - 2006 May 01
TA  - Heart
PG  - 658--663
VI  - 92
IP  - 5
4099  - http://heart.bmj.com/content/92/5/658.short
4100  - http://heart.bmj.com/content/92/5/658.full
SO  - Heart2006 May 01; 92
AB  - 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.