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. 2010 May 4;55(18):1923-32.
doi: 10.1016/j.jacc.2010.02.005.

Contemporary mortality risk prediction for percutaneous coronary intervention: results from 588,398 procedures in the National Cardiovascular Data Registry

Eric D Peterson  1 , David Dai, Elizabeth R DeLong, J Matthew Brennan, Mandeep Singh, Sunil V Rao, Richard E Shaw, Matthew T Roe, Kalon K L Ho, Lloyd W Klein, Ronald J Krone, William S Weintraub, Ralph G Brindis, John S Rumsfeld, John A Spertus; NCDR Registry Participants
Affiliations

Contemporary mortality risk prediction for percutaneous coronary intervention: results from 588,398 procedures in the National Cardiovascular Data Registry

Eric D Peterson et al. J Am Coll Cardiol. .

Abstract

Objectives: We sought to create contemporary models for predicting mortality risk following percutaneous coronary intervention (PCI).

Background: There is a need to identify PCI risk factors and accurately quantify procedural risks to facilitate comparative effectiveness research, provider comparisons, and informed patient decision making.

Methods: Data from 181,775 procedures performed from January 2004 to March 2006 were used to develop risk models based on pre-procedural and/or angiographic factors using logistic regression. These models were independently evaluated in 2 validation cohorts: contemporary (n = 121,183, January 2004 to March 2006) and prospective (n = 285,440, March 2006 to March 2007).

Results: Overall, PCI in-hospital mortality was 1.27%, ranging from 0.65% in elective PCI to 4.81% in ST-segment elevation myocardial infarction patients. Multiple pre-procedural clinical factors were significantly associated with in-hospital mortality. Angiographic variables provided only modest incremental information to pre-procedural risk assessments. The overall National Cardiovascular Data Registry (NCDR) model, as well as a simplified NCDR risk score (based on 8 key pre-procedure factors), had excellent discrimination (c-index: 0.93 and 0.91, respectively). Discrimination and calibration of both risk tools were retained among specific patient subgroups, in the validation samples, and when used to estimate 30-day mortality rates among Medicare patients.

Conclusions: Risks for early mortality following PCI can be accurately predicted in contemporary practice. Incorporation of such risk tools should facilitate research, clinical decisions, and policy applications.

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Figures

Figure 1
Figure 1. Population Flow Diagram
Between January 2004 and March 2007, 600713 PCI admissions were recorded in the NCDR CathPCI Registry. Following exclusions, 588398 total patients were included in the overall model development and validation cohort.
Figure 2
Figure 2. a. Calibration for the Full Model among STEMI Patients in the Validation Sample b. Calibration for the Full Model among Patients without STEMI in the Validation Sample
Demonstrates observed versus predicted mortality estimates (and the 95% CI) for 10 equally sized risk groups of STEMI (2a) and NSTEMI (2b) patients, based on the full risk prediction model evaluated in the second validation sample.
Figure 2
Figure 2. a. Calibration for the Full Model among STEMI Patients in the Validation Sample b. Calibration for the Full Model among Patients without STEMI in the Validation Sample
Demonstrates observed versus predicted mortality estimates (and the 95% CI) for 10 equally sized risk groups of STEMI (2a) and NSTEMI (2b) patients, based on the full risk prediction model evaluated in the second validation sample.
Figure 3
Figure 3. Calibration of NCDR Bedside Risk Score in Validation Sample
Based on their predicted risk, patients are grouped into eight risk groups, using the full risk prediction model, and then plotted again the observed mortality rates for these in the second validation sample.
See this image and copyright information in PMC

Comment in

References

    1. Smith SC, Jr., Feldman TE, Hirshfeld JW, Jr., et al. ACC/AHA/SCAI 2005 guideline update for percutaneous coronary intervention: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (ACC/AHA/SCAI Writing Committee to Update the 2001 Guidelines for Percutaneous Coronary Intervention). J Am Coll Cardiol. 2006;47:e1–121. - PubMed
    1. Arnold SV DC, Ahmad H, Olabiyi O, Mundluru S, Reid K, Soto G, Gansert S, Spertus J. Converting the Informed Consent From a Perfunctory Process to an Evidence-Based Foundation for Patient Decision Making. Circulation: Cardiovascular Quality and Outcomes. 2008;1:21–28. - PubMed
    1. Curry LA, Nembhard IM, Bradley EH. Qualitative and mixed methods provide unique contributions to outcomes research. Circulation. 2009;119:1442–52. - PubMed
    1. Califf RM, Peterson ED, Gibbons RJ, et al. Integrating quality into the cycle of therapeutic development. J Am Coll Cardiol. 2002;40:1895–901. - PubMed
    1. Addala S, Grines CL, Dixon SR, et al. Predicting mortality in patients with ST-elevation myocardial infarction treated with primary percutaneous coronary intervention (PAMI risk score). Am J Cardiol. 2004;93:629–32. - PubMed

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