摘要Background:It is currently unclear if fibrinogen is a risk factor for adverse events in patients receiving percutaneous coronary intervention (PCI) or merely serves as a marker of pre-existing comorbidities and other causal factors.We therefore investigated the association between fibrinogen levels and 2-year all-cause mortality,and compared the additional predictive value of adding fibrinogen to a basic model including traditional risk factors in patients receiving contemporary PCI.Methods:A total of 6293 patients undergoing PCI with measured baseline fibrinogen levels were enrolled from January to December 2013 in Fuwai Hospital.Patients were divided into three groups according to tertiles of baseline fibrinogen levels:low fibrinogen,＜2.98 g/L;medium fibrinogen,2.98 to 3.58 g/L;and high fibrinogen,≥3.58 g/L.Independent predictors of 2-year clinical outcomes were determined by multivariate Cox proportional hazards regression modeling.The increased discriminative value of fibrinogen for predicting all-cause mortality was assessed using the C-statistic and integrated discrimination improvement (IDI).Results:The 2-year all-cause mortality rate was 1.2％.It was significantly higher in the high fibrinogen compared with the low and medium fibrinogen groups according to Kaplan-Meier analyses (1.7％ vs.0.9％ and 1.7％ vs.1.0％,respectively;log-rank,P=0.022).Fibrinogen was significantly associated with all-cause mortality according to multivariate Cox regression (hazard ratio 1.339,95 ％ confidence interval:1.109-1.763,P =0.005),together with traditional risk factors including age,sex,diabetes mellitus,left ventricular ejection fraction,creatinine clearance,and low-density lipoprotein cholesterol.The area under the curve for all-cause mortality in the basic model including traditional risk factors was 0.776,and this value increased to 0.787 when fibrinogen was added to the model (IDI=0.003,Z=0.140,P=0.889).Conclusions:Fibrinogen is associated with 2-year all-cause mortality in patients receiving PCI,but provides no additional information over a model including traditional risk factors.