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.
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.
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
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
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
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
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
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
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
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