BACKGROUND: The incremental predictive value of red cell distribution width (RDW) for major adverse cardiac events (MACEs) has not been fully investigated in patients with acute myocardial infarction (AMI). HYPOTHESIS: The aim of this study was to determine the incremental value of RDW to the established risk factors in predicting clinical outcomes after AMI. METHODS: Between November 2005 and January 2010, 1596 patients with AMI (1070 male; mean age, 64.5 ± 11.9 years) were analyzed in this study. Baseline levels of RDW were measured at the time of admission. The 12-month MACEs were defined as death and nonfatal MI. RESULTS: The RDW levels were significantly higher in patients with 12-month MACEs (13.8 ± 1.3% vs 13.3 ± 1.2%, P < 0.001). In a Cox proportional hazards model, RDW (hazard ratio [HR]: 1.19, P = 0.016) was an independent predictor for 12-month MACEs. Adding RDW to established risk factors and hemoglobin levels significantly improved prediction for 12-month MACEs, as shown by the net reclassification improvement (0.297; P = 0.012) and integrated discrimination improvement (0.0143; P = 0.042). The likelihood ratio test showed that RDW added incremental predictive value to the combination of hemoglobin and established risk factors (P = 0.005). Patients were categorized into 4 groups according to quartiles of RDW at baseline. Adjusted HRs for 12-month MACEs were 1 (RDW ≤12.6%, reference), 4.24 (RDW 12.7%-13.1%, P = 0.01), 4.36 (RDW 13.2%-13.9%, P = 0.008), and 6.18 (RDW 13.2%-13.9%, P = 0.001), respectively. CONCLUSIONS: In post-myocardial infarction patients, baseline RDW levels at admission could provide incremental predictive value to established risk factors for predicting 12-month MACEs.
BACKGROUND: The incremental predictive value of red cell distribution width (RDW) for major adverse cardiac events (MACEs) has not been fully investigated in patients with acute myocardial infarction (AMI). HYPOTHESIS: The aim of this study was to determine the incremental value of RDW to the established risk factors in predicting clinical outcomes after AMI. METHODS: Between November 2005 and January 2010, 1596 patients with AMI (1070 male; mean age, 64.5 ± 11.9 years) were analyzed in this study. Baseline levels of RDW were measured at the time of admission. The 12-month MACEs were defined as death and nonfatal MI. RESULTS: The RDW levels were significantly higher in patients with 12-month MACEs (13.8 ± 1.3% vs 13.3 ± 1.2%, P < 0.001). In a Cox proportional hazards model, RDW (hazard ratio [HR]: 1.19, P = 0.016) was an independent predictor for 12-month MACEs. Adding RDW to established risk factors and hemoglobin levels significantly improved prediction for 12-month MACEs, as shown by the net reclassification improvement (0.297; P = 0.012) and integrated discrimination improvement (0.0143; P = 0.042). The likelihood ratio test showed that RDW added incremental predictive value to the combination of hemoglobin and established risk factors (P = 0.005). Patients were categorized into 4 groups according to quartiles of RDW at baseline. Adjusted HRs for 12-month MACEs were 1 (RDW ≤12.6%, reference), 4.24 (RDW 12.7%-13.1%, P = 0.01), 4.36 (RDW 13.2%-13.9%, P = 0.008), and 6.18 (RDW 13.2%-13.9%, P = 0.001), respectively. CONCLUSIONS: In post-myocardial infarctionpatients, baseline RDW levels at admission could provide incremental predictive value to established risk factors for predicting 12-month MACEs.
Authors: Holger Reinecke; Torsten Trey; Jürgen Wellmann; Jan Heidrich; Manfred Fobker; Thomas Wichter; Michael Walter; Günter Breithardt; Roland M Schaefer Journal: Eur Heart J Date: 2003-12 Impact factor: 29.983
Authors: M Emdin; C Passino; C Michelassi; F Titta; A L'abbate; L Donato; A Pompella; A Paolicchi Journal: Eur Heart J Date: 2001-10 Impact factor: 29.983
Authors: Paul C Lee; Annapoorna S Kini; Chowdhury Ahsan; Edward Fisher; Samin K Sharma Journal: J Am Coll Cardiol Date: 2004-08-04 Impact factor: 24.094
Authors: Elizabeta Nemeth; Seth Rivera; Victoria Gabayan; Charlotte Keller; Sarah Taudorf; Bente K Pedersen; Tomas Ganz Journal: J Clin Invest Date: 2004-05 Impact factor: 14.808
Authors: Qi Liang; Xin-Jun Lei; Hong-Bing Li; Yang-Rong Yin; Jie Ren; Li-Hong Fan; Xin Huang; Zu-Yi Yuan Journal: Nan Fang Yi Ke Da Xue Xue Bao Date: 2017-08-20