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Comorbid conditions and outcomes after percutaneous coronary intervention
M Singh1, C S Rihal, V L Roger
1Division of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota 55905, USA. singh.mandeep@mayo.edu
Insights
Adding comorbid conditions to the Mayo Clinic Risk Score (MCRS) significantly improves prediction of long-term mortality after percutaneous coronary intervention (PCI), but not in-hospital outcomes.
Area of Science:
- Cardiology
- Medical Informatics
- Public Health
Background:
- Percutaneous coronary intervention (PCI) is a common procedure for coronary artery disease.
- Accurate risk stratification is crucial for predicting outcomes after PCI.
- Existing risk models may not fully capture the impact of comorbid conditions on patient outcomes.
Purpose of the Study:
- To evaluate the added value of comorbid conditions in predicting in-hospital outcomes and long-term mortality following PCI.
- To assess the discriminatory ability of the Mayo Clinic Risk Score (MCRS) alone and when combined with a coronary artery disease (CAD)-specific index for comorbid conditions.
Main Methods:
- Retrospective chart review of 7659 patients undergoing 9032 PCIs at an academic medical center.
- Utilized the Mayo Clinic Risk Score (MCRS) and a CAD-specific index for comorbid conditions.
- Analyzed in-hospital major adverse cardiovascular events (MACE) and long-term all-cause mortality.
Main Results:
- The MCRS and CAD-specific index both correlated with increased in-hospital MACE.
- The MCRS alone had a c-statistic of 0.78 for in-hospital MACE; adding the CAD-specific index did not significantly improve this (c-statistic = 0.78, p=0.29).
- For long-term all-cause mortality, the MCRS model had a c-statistic of 0.69, which improved to 0.75 when the CAD-specific index was added (p<0.001).
Conclusions:
- Comorbid conditions, assessed by the CAD-specific index, provide significant prognostic information for long-term mortality after PCI.
- These comorbid conditions offer limited additional predictive value for in-hospital complications following PCI.
- Future risk stratification models for long-term PCI outcomes should incorporate health-status measures like comorbid conditions.
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.
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