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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**

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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


Background
BACKGROUND In-Hospital Mortality following Percutaneous Coronary Interventions using the National Cardiovascular Data Registry

  • 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.


Background1
Background In-Hospital Mortality following Percutaneous Coronary Interventions using the National Cardiovascular Data Registry

  • 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.


0.1 In-Hospital Mortality following Percutaneous Coronary Interventions using the National Cardiovascular Data Registry

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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

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C-index=0.90

Estimated risk of death (%)

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CP1246788-1


Statistical methods
Statistical Methods In-Hospital Mortality following Percutaneous Coronary Interventions using the National Cardiovascular Data Registry

  • 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.


Statistical methods cont
Statistical Methods (Cont.) In-Hospital Mortality following Percutaneous Coronary Interventions using the National Cardiovascular Data Registry

  • 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.


Patient characteristics by in hospital mortality in the ncdr
Patient Characteristics by In-Hospital Mortality in the NCDR In-Hospital Mortality following Percutaneous Coronary Interventions using the National Cardiovascular Data Registry

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


Frequency of the Risk, based on the MCRS of Patients Undergoing PCI

%

Frequency (%)

Risk Score


Discrimination of the MCRS Undergoing PCI

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



O vs e in hospital mortality with recalibrated quadratic mcrs internal validation sample 433 045

70% original MCRS prediction equation

65%

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Observed Mortality (%)

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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


Summary and conclusions
Summary and Conclusions original MCRS prediction equation

  • 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.


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