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 center.
Patients 7,659 patients who had 9,032 PCIs.
Interventions PCI performed at Mayo Clinic between January 1, 1999, and June 30, 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 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 23%. The rate of in-hospital major adverse cardiovascular events (MACE) increased with higher MCRS and CAD-specific index (Cochran-Armitage test, P<.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=.29). A total of 707 postdismissal deaths occurred after 7,253 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<.001), indicating significant improvement in the discriminatory ability.
Conclusions Addition of comorbid conditions to the MCRS adds significant prognostic information for postdismissal 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.
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