Bleeding in Patients Undergoing Percutaneous Coronary Intervention
Open Access
- 1 June 2009
- journal article
- research article
- Published by Ovid Technologies (Wolters Kluwer Health) in Circulation: Cardiovascular Interventions
- Vol. 2 (3), 222-229
- https://doi.org/10.1161/circinterventions.108.846741
Abstract
Background— Bleeding in patients undergoing percutaneous coronary intervention (PCI) is associated with increased morbidity, mortality, length of hospitalization, and cost. We identified baseline clinical characteristics associated with bleeding complications after PCI and developed a simplified, clinically useful algorithm to predict patient risk. Methods and Results— Data were analyzed from 302 152 PCI procedures performed at 440 US centers participating in the National Cardiovascular Data Registry. As defined by the National Cardiovascular Data Registry, bleeding required transfusion, prolonged hospital stay, and/or a drop in hemoglobin >3.0 g/dL from any location, including percutaneous entry site, retroperitoneal, gastrointestinal, genitourinary, and other/unknown location. Bleeding complications occurred in 2.4% of patients. From the best-fitting model consisting of 15 clinical elements associated with post-PCI bleeding in a random 80% training cohort, we developed a parsimonious risk algorithm. Predictors of bleeding included age, gender, previous heart failure, glomerular filtration rate, peripheral vascular disease, no previous PCI, New York Heart Association/Canadian Cardiovascular Society Functional Classification class IV heart failure, ST-elevation myocardial infarction, non–ST-elevation myocardial infarction, and cardiogenic shock. The parsimonious model was validated in the remaining 20% of the population (c-statistic, 0.72) and in clinically relevant subgroups of patients. This simplified model was used to derive a clinical risk algorithm, with larger numbers corresponding with greater risk. In 3 categories, bleeding rates were greater in patients with higher estimates (≤7, 0.7%; 8 to 17, 1.8%; ≥18, 5.1%). Conclusions— This report identifies baseline clinical factors associated with bleeding and proposes a clinically useful algorithm to estimate bleeding risk. This model is potentially actionable in altering therapeutic decision making and improving outcomes in patients undergoing PCI.Keywords
This publication has 34 references indexed in Scilit:
- Bleeding and blood transfusion issues in patients with non-ST-segment elevation acute coronary syndromesEuropean Heart Journal, 2007
- Presentation of multivariate data for clinical use: The Framingham Study risk score functionsStatistics in Medicine, 2004
- Incidence, predictors, and prognostic implications of bleeding and blood transfusion following percutaneous coronary interventionsThe American Journal of Cardiology, 2003
- Predictors of major bleeding in acute coronary syndromes: the Global Registry of Acute Coronary Events (GRACE)European Heart Journal, 2003
- Predictors of length of stay after coronary stentingAmerican Heart Journal, 2001
- The American College of Cardiology-National Cardiovascular Data Registry™ (ACC-NCDR™): building a national clinical data repositoryJournal of the American College of Cardiology, 2001
- A More Accurate Method To Estimate Glomerular Filtration Rate from Serum Creatinine: A New Prediction EquationAnnals of Internal Medicine, 1999
- AddendumJournal of the American College of Cardiology, 1997
- Longitudinal data analysis using generalized linear modelsBiometrika, 1986
- VERIFICATION OF FORECASTS EXPRESSED IN TERMS OF PROBABILITYMonthly Weather Review, 1950