Mandeep Singh; Eric D. Peterson*; Sarah Milford-Beland*; John S. Rumsfeld,# John A. Spertus**

1. Validation of Mayo Clinic Risk Adjustment Model for In-Hospital Mortality following Percutaneous Coronary Interventions using the National Cardiovascular Data Registry Mandeep Singh; Eric D. Peterson*; Sarah Milford-Beland*; John S. Rumsfeld,# John A. Spertus** Mayo Clinic, Rochester, DCRI* (S.M-B, E.P.), Mid America Heart Institute** (J.A.S.), Denver VA Medical Center# (J.S.R.) No Financial Disclosure or Conflict of Interest

2. BACKGROUND • Predictive models can assist patients and clinicians in decision-making and informed consent. • Existing PCI risk models include angiographic variables limiting routine clinical use. • Mayo Clinic Risk Score (MCRS) for in-hospital mortality is based on pre-procedural clinical and non-invasive assessment. • MCRS can potentially serve as a risk assessment aid to patients/physicians before coronary angiography for PCI.

3. Background • External validation of the MCRS is lacking • The NCDR cath-PCI registry presents an ideal opportunity to validate the MCRS • Study population: Index PCI for 309,351 patients in NCDR participating hospital between January 2004 and March 2006. • Outcome: In-hospital mortality during the hospital admission following PCI.

4. 0.1 0.5 80 70 30 60 40 20 10 50 4 3 2 1 5 90 70 60 30 40 50 80 20 10 11 40 60 80 20 1 2 3 4 5 6 7 8 9 0 Mayo Clinic Risk Score (MCRS) Mortality Points Score Age (yr) See below ____ Creatinine (mg/dL) See below ____ LV ejection See below ____fraction (%) Preprocedural shock 9 ____ MI within 24 hours 4 ____ CHF on presentation 3 ____(without AMIor shock) Peripheral 2 ____vascular disease Total score ____ C-index=0.90 Estimated risk of death (%) Risk score Age (yr) Creatinine (mg/dL) LV ejection fraction (%) 2 1 0 1 2 3 4 5 1 0 1 2 3 4 5 6 4 3 2 1 0 CP1246788-1

5. Statistical Methods • Using the MCRS equation, predicted probabilities of death were calculated for each patient in the NCDR population. • Patients with the same predicted mortality score were grouped together, and within each group, the observed (O) mortality rate was calculated. • The O vs. E (expected) mortality rates for these groups were plotted and we used H-L method for calibration • Model discrimination was assessed using ROC, or c-statistic, for the entire population and within pre-specified subgroups.

6. Statistical Methods (Cont.) • The analysis was refined to include recalibration of the MCRS equation using the ACC population • For this recalibrated model, patients with the same predicted mortality score were again grouped together. • O vs. E mortality rates were plotted. • Calibration: Hosmer-Lemeshow method. • Internal validation of the new model using NCDR PCI patients April 2006, March 2007.

7. Patient Characteristics by In-Hospital Mortality in the NCDR Variable Number (%) Mortality p Age <60Y 114,844 (37.12) 0.60 <0.0001 ≥80Y 34383 (11.11) 3.22 Congestive heart failure Yes 27003 (8.73) 5.25 <0.0001 No 282,321 (91.26) 0.84 Acute Myocardial infarction Yes 68116 (22.02) 3.44 <0.0001 No   241,128 (77.95) 0.60 Peripheral vascular disease Yes 36568 (11.82) 2.18 <0.0001 No 272,768 (88.17) 1.10 Cardiogenic shock Yes 6314 (2.04) 24.83 <0.0001 No 303,007 (97.95) 0.73 Renal failure Yes 16323 (5.28) 3.89 <0.0001 No 293,012 (94.72) 1.08

8. Frequency of the Risk, based on the MCRS of Patients Undergoing PCI % Frequency (%) Risk Score

9. Discrimination of the MCRS Group N MCRS (Min- Max) C-index Overall 309,351 0-25 0.884 Shock/ AMI 69920 4-25 0.873 Age <40 5627 1-21 0.938 Age 65+ 151517 0-25 0.858 CHF 27003 3-25 0.82 Creatinine <0.7 10491 1-20 0.797 Creatinine >1.2 66839 1-25 0.875 Multivessel Dx 150579 0-25 0.87 Female 104110 0-24 0.872 Diabetes 98081 0-24 0.878 CP1246782-7

10. Observed versus expected in-hospital mortality using the original MCRS prediction equation

11. 70% 65% 60% 55% 50% 45% 40% 35% Observed Mortality (%) 30% 25% 20% 15% 10% 5% 0% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% Predicted Mortality (%) O vs. E in-hospital mortality with recalibrated quadratic MCRS, internal validation sample (433,045) O=5,177; E=5,310 deaths (difference 2.5 per 100) c index= 0.885

12. Summary and Conclusions • External validation of the MCRS using NCDR confirms its broader applicability. • The MCRS has high discrimination for in-hospital mortality using 7 clinical/non-invasive variables. • Most variables can be obtained at the time of first visit. • This may help the operator to individualize the risk of procedural death from PCI, and to counsel patients at the time of PCI. • External validation of the new, recalibrated MCRS model is, however, required.