Presentation is loading. Please wait.

Presentation is loading. Please wait.

Martial Hamon 1, Steven Marso 2, Sunil Rao 3, Marco Valgimigli 4, Freek Verheugt 5, Anthony Gershlick 6, Yamei Wang 8, Gabriel Steg 7, Efthymios Deliargyris.

Similar presentations


Presentation on theme: "Martial Hamon 1, Steven Marso 2, Sunil Rao 3, Marco Valgimigli 4, Freek Verheugt 5, Anthony Gershlick 6, Yamei Wang 8, Gabriel Steg 7, Efthymios Deliargyris."— Presentation transcript:

1 Martial Hamon 1, Steven Marso 2, Sunil Rao 3, Marco Valgimigli 4, Freek Verheugt 5, Anthony Gershlick 6, Yamei Wang 8, Gabriel Steg 7, Efthymios Deliargyris 8 Institutions: 1. Centre Hospitalier Universitaire de Caen, France. 2. Saint Luke's Mid America Heart Institute, University of Missouri–Kansas City, Kansas City, MO. 3. Duke Clinical Research Institute, Durham, NC. 4. Department of Interventional Cardiology, Cardiovascular Institute, University of Ferrara, Ferrara, Italy. 5. Radboud University Medical Centre, Nijmegen, the Netherlands. 6. University of Leicester, Glenfield Hospital, Leicester, United Kingdom. 7. INSERM U-698, AP-HP and Université Paris 7, Paris, France. 8. The Medicines Company, Parsippany NJ, USA. Comparison of bivalirudin versus heparin(s) during percutaneous coronary intervention in patients receiving prasugrel 1

2 Purpose ● Bivalirudin (BIV) has been established as Class I therapy in the ESC/EACTS guidelines for anticoagulation in PCI for moderate to high risk NSTE-ACS and STE-ACS patients. ● Antiplatelet agents are used as adjunctive agents with BIV or unfractionated or low molecular weight heparin (HEP) ± glycoprotein IIb/IIIa inhibitor (GPI) in PCI. ● Prasugrel (PRAS) is a recently introduced agent and thus little data is available regarding the use of PRAS with BIV. 2

3 Observational database background ● The Premier Perspective Database: ● A comprehensive repository of clinical, financial, and outcomes information that undergo routine quality and completeness checks including data verification, reconciliation, and validation ● Used by the FDA for drug surveillance and by CMS to evaluate next- generation payment models ● Over 5 million inpatient discharges and over 30 million hospital outpatient visits are recorded annually; approximately 1/6 of all US hospitalizations ● Potential to allow greater insight on comparative effectiveness issues

4 Premier analysis- patient population

5 Methods ● Using the Premier Perspective database, 6986 patients who underwent elective, urgent, or primary PCI between Q3 2009 and Q4 2010 from 166 US hospitals were identified. ● Patients were treated with either BIV (n=3377) or HEP± GPI (n=3609) on the day of PCI and given PRAS before or on the day of PCI. ● Outcomes of interest included bleeding, transfusion, death, and hospital length of stay. ● To control for patient and hospital level characteristics, a 1:1 propensity score matching analysis was performed (PSM1). ● PSM2 was performed to eliminate patients in whom the use of PRAS increases the risk of bleeding, (age> 75 years, prior stroke/TIA, low body weight, and CABG in the same hospitalization). ● Differences between the treatment groups before and after PSM were presented using descriptive statistics, including unadjusted odds ratio (OR) and 95% confidence interval (CI). 5

6 Baseline characteristics ● 6896 patients receiving bivalirudin or heparin+GPI for PCI ● Prasugrel was given on the day of PCI in both groups 6 BIV (N=3377)HEP±GPI (N=3609) Age 65-69562 (6.6%)492 (13.6%) Age 70-74323 (9.6%)281 (7.8%) Age 75-79136 (4.0%)102 (2.8%) Age ≥ 8064 (1.9%)55 (1.5%) Male2377 (70.4%)2720 (75.4%) Anemia260 (7.7%)297 (8.2%) CHF377 (11.2%)440 (12.2%) Diabetes1160 (34.4%)1188 (32.9%) Hyperlipidemia2501 ( 74.1%)2717 (75.3%) Hypertension2454 (72.7%)2501 (69.3%) Peripheral vascular disease203 ( 6.0%)182 ( 5.0%) Renal insufficiency345 (10.2%)339 ( 9.4%) Cardiogenic shock29 (0.9%)136 (3.8%) Stroke8 (0.2%)11 (0.3%) GPI on day of PCI0 (0%)2550 (70.7%) Primary diagnosis STEMI476 (14.1%)1339 (37.1%) NSTEMI612 (18.1%)864 (23.9%) Other CIHD1983 (58.7%)1104 (30.6%) Unknown AMI42 (1.2%)86 (2.4%) Unstable Angina15 (0.4%)4 (0.1%) Stable Angina1 ( 0.0%)2 (0.1%) Other248 (7.3%)210 (5.8%)

7 Baseline characteristics ● Propensity score -matched populations 7 PSM 1PSM 2 BIV alone (N=2333) HEP±GPI (N=2333) BIV alone (N=2180) HEP±GPI (N=2180) Age 65-6915.2% 14.9%15.8% 16.4% Age 70-749.0%8.5%9.4% 9.0% Age 75-793.4%3.1%-- Age ≥ 801.5%2.0%-- Male71.5% 72.6% 73.1% Anemia8.4%7.9%7.4%7.3% CHF12.1%11.2%11.1% 11.3% Diabetes35.0%34.1% 35.4% 35.3% Hyperlipidemia74.5%75.5% 75.0% 75.9% Hypertension71.8%71.5%71.1%71.6% PVD 5.8% 6.0%5.0% Renal insuff10.0%9.8%8.8%9.1% Cardio shock1.2%1.5%1.1% 1.2% Stroke0.3%0.2%-- PSM 1= 1:1 propensity score matched; PSM 2= eliminates patients in whom the use of PRAS increases the risk of bleeding, (age> 75 years, prior stroke/TIA, low body weight, and CABG in the same hospitalization

8 Results 1-2: Clinically apparent bleeding ● In- hospital outcomes PopulationBIVHEP + GPIOR (95% CI) Overall population 4.0%6.0%0.65 (0.52, 0.81) PSM 14.4%5.4% 0.81 (0.62, 1.06) PSM 24.3%5.3% 0.79 (0.60, 1.05) BIV better HEP± GPI better PSM 1= 1:1 propensity score matched; PSM 2= eliminates patients in whom the use of PRAS increases the risk of bleeding, (age> 75 years, prior stroke/TIA, low body weight, and CABG in the same hospitalization

9 Clinically apparent bleeding requiring transfusion ● In- hospital outcomes PopulationBIVHEP + GPIOR (95% CI) Overall population 0.5%1.0% 0.52 (0.29, 0.91) PSM 10.4%0.9% 0.45 (0.21, 0.96) PSM 20.5%0.7% 0.67 (0.30, 1.48) BIV better HEP± GPI better PSM 1= 1:1 propensity score matched; PSM 2= eliminates patients in whom the use of PRAS increases the risk of bleeding, (age> 75 years, prior stroke/TIA, low body weight, and CABG in the same hospitalization

10 Results 3-5: Any transfusion ● In- hospital outcomes PopulationBIVHEP + GPIOR (95% CI) Overall population 1.4%2.5% 0.53 (0.37, 0.75) PSM 11.2%2.2% 0.53 (0.34, 0.85) PSM 21.1%1.8% 0.57 (0.34, 0.96) BIV better HEP ± GPI better PSM 1= 1:1 propensity score matched; PSM 2= eliminates patients in whom the use of PRAS increases the risk of bleeding, (age> 75 years, prior stroke/TIA, low body weight, and CABG in the same hospitalization

11 Death ● In- hospital outcomes PopulationBIVHEP + GPIOR (95% CI) Overall population 0.4%1.0% 0.43 (0.23, 0.79) PSM 10.6%0.7% 0.76 (0.37, 1.58) PSM 20.4%0.6% 0.75 (0.31, 1.78) BIV better HEP ± GPI better PSM 1= 1:1 propensity score matched; PSM 2= eliminates patients in whom the use of PRAS increases the risk of bleeding, (age> 75 years, prior stroke/TIA, low body weight, and CABG in the same hospitalization

12 Length of hospital stay 12 OverallPSM1PSM2 BIV N=3377 HEP±GPI N=3609 BIV N=2333 HEP±GPI N=2333 BIV N=2180 HEP±GPI N=2180 2.6 ± 2.83.2 ± 3.12.7 ± 2.82.9 ± 2.82.7 ± 2.62.9 ± 2.7 <0.0001 PSM 1= 1:1 propensity score matched; PSM 2= eliminatespatients in whom the use of PRAS increases the risk of bleeding, (age> 75 years, prior stroke/TIA, low body weight, and CABG in the same hospitalization

13 Conclusions ● In this analysis of real world data, patients receiving bivalirudin and prasugrel had fewer transfusions than with HEP ± GPI and a shorter length of hospital stay. 13


Download ppt "Martial Hamon 1, Steven Marso 2, Sunil Rao 3, Marco Valgimigli 4, Freek Verheugt 5, Anthony Gershlick 6, Yamei Wang 8, Gabriel Steg 7, Efthymios Deliargyris."

Similar presentations


Ads by Google