Literature DB >> 23500304

Pre-procedural estimate of individualized bleeding risk impacts physicians' utilization of bivalirudin during percutaneous coronary intervention.

Seshu C Rao1, Adnan K Chhatriwalla, Kevin F Kennedy, Carole J Decker, Elizabeth Gialde, John A Spertus, Steven P Marso.   

Abstract

OBJECTIVES: This study sought to assess whether incorporation of routine bleeding risk estimates affected the utilization of bivalirudin during percutaneous coronary intervention (PCI).
BACKGROUND: Bivalirudin use during PCI has been shown to reduce bleeding complications. However, a risk-treatment paradox exists, in which patients at highest risk for bleeding are least likely to receive bivalirudin. Whether routine estimation of individualized bleeding risk can affect physicians' use of bivalirudin is unknown.
METHODS: PCI data from a single health system between 2007 and 2011 were analyzed. Beginning in July 2009, individualized bleeding risk estimates were provided immediately preceding PCI. Using a pre-post design, we compared bivalirudin use before and after this implementation, for patients across 3 strata of bleeding risk (<1%, 1% to 3%, and >3%).
RESULTS: Data from 6,491 PCI procedures were analyzed. Overall, bivalirudin use increased in the post-implementation period (26.9% vs. 34.2%, p < 0.001). Bivalirudin use increased in intermediate (27% to 35%, p < 0.001) and high bleeding risk patients (25% to 43%, p < 0.001), and decreased in low-risk patients (30% to 25%, p = 0.014). During the same period, bleeding complications decreased in intermediate-risk (3.4% to 1.8%, p = 0.009) and high-risk (6.9% to 3.7%, p = 0.005) patients and remained unchanged in low-risk patients (1.1% to 1.0%, p = 0.976).
CONCLUSIONS: There was an increase in bivalirudin use and a lower incidence of bleeding after the incorporation of individualized bleeding risk estimates into clinical practice. This implementation led to a reversal of the risk-treatment paradox, through a rational increase in bivalirudin use in patients at intermediate and high bleeding risk and decreased use in lower-risk patients.
Copyright © 2013 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23500304     DOI: 10.1016/j.jacc.2013.02.017

Source DB:  PubMed          Journal:  J Am Coll Cardiol        ISSN: 0735-1097            Impact factor:   24.094


  10 in total

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Authors:  Benjamin S Wessler; Lana Lai Yh; Whitney Kramer; Michael Cangelosi; Gowri Raman; Jennifer S Lutz; David M Kent
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2015-07-07

2.  Understanding physician-level barriers to the use of individualized risk estimates in percutaneous coronary intervention.

Authors:  Carole Decker; Linda Garavalia; Brian Garavalia; Elizabeth Gialde; Robert W Yeh; John Spertus; Adnan K Chhatriwalla
Journal:  Am Heart J       Date:  2016-05-26       Impact factor: 4.749

3.  Precision medicine to improve use of bleeding avoidance strategies and reduce bleeding in patients undergoing percutaneous coronary intervention: prospective cohort study before and after implementation of personalized bleeding risks.

Authors:  John A Spertus; Carole Decker; Elizabeth Gialde; Philip G Jones; Edward J McNulty; Richard Bach; Adnan K Chhatriwalla
Journal:  BMJ       Date:  2015-03-24

4.  Hospital variability in use of anticoagulant strategies during acute myocardial infarction treated with an early invasive strategy.

Authors:  Suzanne V Arnold; Shu-Xia Li; Karen P Alexander; John A Spertus; Brahmajee K Nallamothu; Jeptha P Curtis; Mikhail Kosiborod; Aakriti Gupta; Tracy Y Wang; Haiqun Lin; Kumar Dharmarajan; Kelly M Strait; Timothy J Lowe; Harlan M Krumholz
Journal:  J Am Heart Assoc       Date:  2015-06-15       Impact factor: 5.501

5.  Separating signal from noise: the challenge of identifying useful biomarkers in sepsis.

Authors:  Russell J McCulloh; John A Spertus
Journal:  Crit Care       Date:  2014-03-17       Impact factor: 9.097

6.  Validated contemporary risk model of acute kidney injury in patients undergoing percutaneous coronary interventions: insights from the National Cardiovascular Data Registry Cath-PCI Registry.

Authors:  Thomas T Tsai; Uptal D Patel; Tara I Chang; Kevin F Kennedy; Frederick A Masoudi; Michael E Matheny; Mikhail Kosiborod; Amit P Amin; William S Weintraub; Jeptha P Curtis; John C Messenger; John S Rumsfeld; John A Spertus
Journal:  J Am Heart Assoc       Date:  2014-12       Impact factor: 5.501

7.  Bleeding outcomes after non-emergency percutaneous coronary intervention in the very elderly.

Authors:  Vimalraj Bogana Shanmugam; Dennis T Wong; Hashrul Rashid; James D Cameron; Yuvaraj Malaiapan; Peter J Psaltis
Journal:  J Geriatr Cardiol       Date:  2017-10       Impact factor: 3.327

8.  A random forest based risk model for reliable and accurate prediction of receipt of transfusion in patients undergoing percutaneous coronary intervention.

Authors:  Hitinder S Gurm; Judith Kooiman; Thomas LaLonde; Cindy Grines; David Share; Milan Seth
Journal:  PLoS One       Date:  2014-05-09       Impact factor: 3.240

9.  Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study.

Authors:  Chenxi Huang; Karthik Murugiah; Shiwani Mahajan; Shu-Xia Li; Sanket S Dhruva; Julian S Haimovich; Yongfei Wang; Wade L Schulz; Jeffrey M Testani; Francis P Wilson; Carlos I Mena; Frederick A Masoudi; John S Rumsfeld; John A Spertus; Bobak J Mortazavi; Harlan M Krumholz
Journal:  PLoS Med       Date:  2018-11-27       Impact factor: 11.069

10.  Reversing the "Risk-Treatment Paradox" of Bleeding in Patients Undergoing Percutaneous Coronary Intervention: Risk-Concordant Use of Bleeding Avoidance Strategies Is Associated With Reduced Bleeding and Lower Costs.

Authors:  Amit P Amin; Samantha Miller; Brandon Rahn; Mary Caruso; Andrew Pierce; Katrine Sorensen; Howard Kurz; Alan Zajarias; Richard Bach; Jasvindar Singh; John M Lasala; Hemant Kulkarni; Patricia Crimmins-Reda
Journal:  J Am Heart Assoc       Date:  2018-11-06       Impact factor: 5.501

  10 in total

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