Objective: To evaluate whether adding comorbid conditions to a risk model can help predict in-hospital outcome and long-term mortality after percutaneous coronary intervention (PCI).
Design: Retrospective chart review
Setting: Academic medical centre.
Patients: 7659 patients who had 9032 PCIs.
Interventions: PCI performed at Mayo Clinic between 1 January 1999 and 30 June 2004.
Main outcome measures: The Mayo Clinic Risk Score (MCRS) and the coronary artery disease (CAD)-specific index for determination of comorbid conditions in all patients.
Results: The mean (SD) MCRS score was 6.5 (2.9). The CAD-specific index was 0 or 1 in 46%, 2 or 3 in 30% and 4 or higher in 24%. The rate of in-hospital major adverse cardiovascular events (MACE) increased with higher MCRS and CAD-specific index (Cochran–Armitage test, p<0.001 for both models). The c-statistic for the MCRS for in-hospital MACE was 0.78; adding the CAD-specific index did not improve its discriminatory ability for in-hospital MACE (c-statistic = 0.78; likelihood ratio test, p = 0.29). A total of 707 deaths after dismissal occurred after 7253 successful procedures. The c-statistic for all-cause mortality was 0.69 for the MCRS model alone and 0.75 for the MCRS and CAD-specific indices together (likelihood ratio test, p<0.001), indicating significant improvement in the discriminatory ability.
Conclusions: Addition of comorbid conditions to the MCRS adds significant prognostic information for post-dismissal mortality but adds little prognostic information about in-hospital complications after PCI. Such health-status measures should be included in future risk stratification models that predict long-term mortality after PCI.
Statistics from Altmetric.com
Competing interests: None declared.
Ethics approval: The Mayo Clinic Institutional Review Board approved the study
See Editorial, p 1366
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