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Contemporary Predictors of Procedural Mortality Among Patients Undergoing PCI: Results From National Cardiovascular Data Registry (NCDR) Eric D Peterson,

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Presentation on theme: "Contemporary Predictors of Procedural Mortality Among Patients Undergoing PCI: Results From National Cardiovascular Data Registry (NCDR) Eric D Peterson,"— Presentation transcript:

1 Contemporary Predictors of Procedural Mortality Among Patients Undergoing PCI: Results From National Cardiovascular Data Registry (NCDR) Eric D Peterson, David Dai, Elizabeth R DeLong, Sunil V Rao, Matthew T Roe, Kalon K L Ho, Mandeep Singh, John S Rumsfeld, Richard E Shaw, William S Weintraub, Ralph G Brindis, John A Spertus on behalf of the NCDR Registry Participants

2 Disclosure Statement Research support provided by the American College of Cardiology National Cardiovascular Data Registry

3 Background Prior models have estimated risks of percutaneous coronary intervention (PCI) mortality. Yet, these have limitations : –Representing older patient populations –Selected centers or regions –Limited number of procedures –Incomplete clinical or angiographic detail –Failed to develop user-friendly formats

4 Objectives We propose to use the ACC-NCDR PCI database, the nations largest interventional data repository to: Develop a contemporary PCI mortality risk model for those receiving primary PCI and elective procedures Internally validate the NCDR PCI model –overall and among selected sub-populations Determine the incremental prognostic value of angiographic factors beyond pre-cath risk factors Develop user-friendly PCI risk score for bedside risk estimation

5 Methods: Populations Development Sample –302,958 PCI at 470 participating NCDR centers –Jan, 2004 – March, 2006 (v3 data only) –Divided into development (60%) and 1 st validation (40%) 2nd Validation Sample –285,440 PCI at 608 participating NCDR centers –April, 2006 – April, 2007 (v3 data only) Exclusions –Not first PCI (57%) –Transfer out (1%) –Missing 2+ candidate variables (<1%)

6 Methods (2) Model Development –Multivariate logistic regression –Backward selection from 34 candidate variables including demographics, risk factors, cardiac status, cath lab visit, and PCI procedures Model Validation –Model discrimination measured using c-index (ranging from 0.5 for chance discrimination to 1.0 for perfect prediction) –Model calibration examined by comparing average observed and predicted values within risk groups

7 Patient Clinical Characteristics (1) Development (181,775) 1 st validation (121,183) 2 nd validation (285,440) Age63.9± ±12.1 Female33.4%33.3% Caucasian87.2%87.1%85.6% BMI (kg/m 2 )29.6± ± ±6.3 Prior MI (>7days)29.1% 27.3% Prior CHF10.1%10.0%9.9% Diabetes – Non-insulin21.5%21.7%22.3% – Insulin10.0% 10.3%

8 Patient Clinical Characteristics (2) Development (181,775) 1 st validation (121,183) 2 nd validation (285,440) Mean GFR* (+/-SD)73.6± ± ±28.1 Dialysis Dependent1.6%1.5% Cerebral Vascular Disease10.9%11.1% Peripheral Vascular Disease11.7% 11.9% Chronic Lung Disease16.0% 15.8% Prior PCI35.1%35.4%36.6% NYHA Class IV18.3% 18.8% Cardiogenic Shock1.9%1.8%1.7% * Glomerular Filtration Rate (GRF) assessed by MDRD formula

9 Procedural Characteristics Development (181,775) 1 st validation (121,183) 2 nd validation (285,440) LVEF52.7±13 PCI Status - Elective49.3% 50.2% - Urgent36.1%35.6%34.7% - Emergency14.4%14.5%15.0% - Salvage 0.2% Highest Risk Lesion -pLAD18.2% -Left Main 1.7% 1.8% -Total Occlusion11.0%10.7%14.9% Multivessel PCI14.0%13.9%14.1%

10 In Hospital Mortality

11 Full and Pre-Cath Risk Models Full Model Precath Simple Model LabelO.R.95% CI Wald Chi-Sq O.R.95% CI Wald Chi-Sq Cardiogenic Shock GFR for STEMI Age (for age>70) Age (for age<=70) PCI Status-Salvage STEMI § PCI Status- Emerg. STEMI § PCI Status- Urgent STEMI § NYHA Class IV for STEMI Chronic Lung Disease Peripheral Vascular Disease Previous History - CHF Full model includes: Prior PCI, PreOp IABP, Ejection Fraction, Coronary Lesion >= 50%: Subacute Thrombosis, Total pre-procedure Occlusion, Diabetes treatment, SCAI Lesion Class 2 or 3, BMI for STEMI/non STEMI, Prior Dialysis for STEMI/non STEMI, Highest risk status for non-STEMI, NYHA Class IV for NSTEMI Per 10 unit increase. § Versus Elective

12 PCI Risk Score System Age <6060,<70 70,< Cardiogenic ShockNoYes 025 Prior CHFNoYes 05 PVD NoYes 05 CLD NoYes 04 GFR NYHA Class 4 NoYes 0 4 PCI Status (STEMI) Elective UrgentEmergent Salvage PCI Status (Other) Elective UrgentEmergent Salvage PointsMortality 00.0% 50.1% 100.1% 150.2% 200.3% 250.6% 301.1% 352.0% 403.6% 456.3% % % % % % % 8081.% % % % %

13 Discrimination: C-Indices SampleFull ModelRisk Score N C-Index C-Index Development181, st Validation121, nd validation285, Subgroups STEMI 39, Other 245, Women 95, Men 190, Age>70 92, Age<=70 193, Diabetes92, No Diabetes192,

14 Calibration for Full Model

15 Events by Clinical Risk Groups in Validation Sample Full ModelRisk Score

16 Limitations Voluntary participation Limited auditing of data source Only internal validation of model No core lab angiographic readings No data on functional status Outcomes limited in in-hospital mortality

17 Conclusions We developed a highly predictive contemporary mortality model for PCI Angiographic variables add modestly to risk assessment Model accurate in –Overall, 75, women vs men, DM vs not, –STEMI vs other –Low vs high risk groups

18

19 Hospital Characteristics Development (181,775) 1 st validation (121,183) 2 nd validation (285,440) Number of Beds463±221463±220454±225 Location - Rural12.6% 12.1% - Urban61.0%61.3%61.2% Teaching60.1%60.0%54.6% Region - West14.1%14.3%16.2% - Northeast9.0%9.9%10.4% - Midwest36.9%36.7%35.8% - South36.5%36.8%37.6% Mean Annual PCI Volume 1151± ± ±807


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