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Background: Atrial fibrillation (AF) is increasing in prevalence, and patients with a history of AF commonly undergo percutaneous coronary intervention (PCI). There is a paucity of contemporary data on the association between AF and clinical outcomes after PCI.Objectives: The study sought to evaluate the association between AF and in-hospital adverse outcomes using a large, prospective multicenter registry.Methods: Data for consecutive PCI cases from 47 hospitals performed between April 2011 and December 2014 were utilized for the analysis. Propensity-matched multivariate analysis was used to adjust for differences in baseline characteristics between patients with and without a history of AF.Results: Of 113,283 PCI cases during the study period, a history of AF was present in 13,912 patients (12%), which varied by institution (range 2.5% to 18.4%). At baseline, patients with a history of AF were older and were more likely to have comorbid congestive heart failure, cardiomyopathy, cerebrovascular disease, and chronic lung disease. Patients with a history of AF were more likely to have in-hospital complications, including in-hospital mortality (3% vs. 1%). In propensity-matched analysis, patients with a history of AF were more likely to be treated with a bare-metal stent (27% vs. 18%). In the propensity-matched model, AF remained independently associated with an increased risk of developing post-procedural bleeding (odds ratio [OR]: 1.32; 95% confidence interval [CI]: 1.15 to 1.52), heart failure (OR: 1.33; 95% CI: 1.17 to 1.52), cardiogenic shock (OR: 1.26; 95% CI: 1.08 to 1.48), and in-hospital mortality (OR: 1.41; 95% CI: 1.18 to 1.68).Conclusions: AF is common among patients undergoing PCI. AF is associated with older age, the presence of other comorbidities, and independently associated with in-hospital post-procedural heart failure, cardiogenic shock, and mortality. [ABSTRACT FROM AUTHOR]

Background Multiple equations exist to estimate glomerular filtration rate (GFR); however, there is no consensus on which is superior for risk classification in patients with chronic kidney disease (CKD) undergoing percutaneous coronary intervention (PCI). Objectives The goals of this study were to identify which equation to estimate GFR is superior for predicting adverse outcomes after PCI and to examine how equation selection would impact drug-dosing recommendations. Methods Estimated GFR (eGFR) was calculated with the Cockcroft-Gault, Modification of Diet in Renal Disease Study (MDRD), and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations for 128,805 patients undergoing PCI in the state of Michigan. Agreement between patient pre-PCI eGFR estimates and resultant CKD stage classifications, their ability to discriminate post-procedural in-hospital clinical outcomes, and the impact of equation choice on dosing recommendations for commonly used antiplatelet and antithrombotic medications were investigated. Results CKD-EPI best discriminated post-PCI mortality by receiver operator characteristic analysis. There was wide variability in eGFR, which persisted after grouping by CKD stages. Reclassification by CKD-EPI resulted in net reclassification index improvement for acute kidney injury and new requirement for dialysis. Equation choice affected drug-dosing recommendations, with the formulas agreeing for only 50.3%, 40.0%, and 34.3% of potentially impacted patients for eGFR cutoffs of <60, <50, and <30 ml/min/1.73 m 2 , respectively. Conclusions Different eGFR equations result in CKD stage reclassification that has major clinical implications for predicting adverse outcomes after PCI and drug-dosing recommendations. Our results support the use of CKD-EPI for risk stratification among patients undergoing PCI. [ABSTRACT FROM AUTHOR]

Objectives: The purpose of this study was to examine the incidence and outcomes of percutaneous coronary intervention (PCI) performed in patients who had not received pre-procedural aspirin. Background: Aspirin is an essential component of peri-PCI pharmacotherapy. Previous studies suggest that pre-procedural aspirin is not administered to a clinically significant number of patients undergoing PCI. Methods: We evaluated the incidence of PCIs performed without pre-procedural aspirin use among patients undergoing PCI from January 2010 through December 2011 at 44 hospitals in Michigan. Propensity-matched multivariate analysis was used to adjust for the nonrandom use of aspirin. Results: Our study population comprised 65,175 patients, of whom 4,640 (7.1%) did not receive aspirin within 24 h before undergoing PCI. Aspirin nonreceivers were more likely to have had previous gastrointestinal bleeding or to present with cardiogenic shock or after cardiac arrest. In the propensity-matched analysis, absence of aspirin before PCI was associated with a higher rate of death (3.9% vs. 2.8%; odds ratio: 1.89 [95% confidence interval: 1.32 to 2.71], p < 0.001) and stroke (0.5% vs. 0.1%; odds ratio: 4.24 [95% confidence interval: 1.49 to 12.11], p = 0.007) with no difference in need for transfusions. This association was consistent across multiple pre-specified subgroups. Conclusions: A significant number of patients do not receive aspirin before undergoing PCI. Lack of aspirin before PCI was associated with significantly increased in-hospital mortality and stroke. Our study results support the need for quality efforts focused on optimizing aspirin use before PCI. [Copyright &y& Elsevier]

Objectives: The aim of the study was to develop and validate a tool for predicting risk of contrast-induced nephropathy (CIN) in patients undergoing contemporary percutaneous coronary intervention (PCI). Background: CIN is a common complication of PCI and is associated with adverse short- and long-term outcomes. Previously described risk scores for predicting CIN either have modest discrimination or include procedural variables and thus cannot be applied for pre-procedural risk stratification. Methods: Random forest models were developed using 46 pre-procedural clinical and laboratory variables to estimate the risk of CIN in patients undergoing PCI. The 15 most influential variables were selected for inclusion in a reduced model. Model performance estimating risk of CIN and new requirement for dialysis (NRD) was evaluated in an independent validation data set using area under the receiver-operating characteristic curve (AUC), with net reclassification improvement used to compare full and reduced model CIN prediction after grouping in low-, intermediate-, and high-risk categories. Results: Our study cohort comprised 68,573 PCI procedures performed at 46 hospitals between January 2010 and June 2012 in Michigan, of which 48,001 (70%) were randomly selected for training the models and 20,572 (30%) for validation. The models demonstrated excellent calibration and discrimination for both endpoints (CIN AUC for full model 0.85 and for reduced model 0.84, p for difference <0.01; NRD AUC for both models 0.88, p for difference = 0.82; net reclassification improvement for CIN 2.92%, p = 0.06). Conclusions: The risk of CIN and NRD among patients undergoing PCI can be reliably calculated using a novel easy-to-use computational tool (https://bmc2.org/calculators/cin). This risk prediction algorithm may prove useful for both bedside clinical decision making and risk adjustment for assessment of quality. [Copyright &y& Elsevier]