OBJECTIVE: To investigate clinical implications of changes in red cell distribution width (RDW) and mean platelet volume (MPV) in patients with acute myocardial infarction. METHODS: A total of 127 patients (90 men and 37 women) were enrolled in this analysis, including 66 with acute myocardial infarction (AMI) and 61 with unstable angina (UA). The patients' baseline demographic and clinical data were compared between the two groups including age, hypertension, diabetes, smoking, BMI, blood biochemical profiles, cardiac functions and platelet and red blood cell parameters. The patients were further divided into subgroups according to the RDW 50% cumulative frequency, and the MPV, P-LCR, hsCRP, NT-proBNP, RBC, Dimer and MCV were compared. The correlations between platelet and erythrocyte test results were evaluated in both the AMI and UA patients. Regression analysis was performed to identify the factors affecting the RDW in the AMI group and a regression model was established. RESULTS: The platelet and red blood cell test results, P-LCR, MPV, and RDW differed significantly between AMI and UA groups (P<0.01 or 0.05). Correlation analysis showed a significant positive correlation between RDW and MPV in AMI group (r=0.34, P<0.01). Between the subgroups with different RDW 50% cumulative frequencies, MPV, P-LCR, hsCRP, D-Dimer, and NT-proBNP all differed significantly (P<0.05 or 0.01). In AMI group, with RDW as the dependent variable, we established a multivariate regression model of RDW=0.19MPV+10.83. CONCLUSION: RDW and MPV are closely correlated in patients with AMI. In multiple regression analysis, MPV can explain the changes in RDW in patients with AMI.
OBJECTIVE: To investigate clinical implications of changes in red cell distribution width (RDW) and mean platelet volume (MPV) in patients with acute myocardial infarction. METHODS: A total of 127 patients (90 men and 37 women) were enrolled in this analysis, including 66 with acute myocardial infarction (AMI) and 61 with unstable angina (UA). The patients' baseline demographic and clinical data were compared between the two groups including age, hypertension, diabetes, smoking, BMI, blood biochemical profiles, cardiac functions and platelet and red blood cell parameters. The patients were further divided into subgroups according to the RDW 50% cumulative frequency, and the MPV, P-LCR, hsCRP, NT-proBNP, RBC, Dimer and MCV were compared. The correlations between platelet and erythrocyte test results were evaluated in both the AMI and UA patients. Regression analysis was performed to identify the factors affecting the RDW in the AMI group and a regression model was established. RESULTS: The platelet and red blood cell test results, P-LCR, MPV, and RDW differed significantly between AMI and UA groups (P<0.01 or 0.05). Correlation analysis showed a significant positive correlation between RDW and MPV in AMI group (r=0.34, P<0.01). Between the subgroups with different RDW 50% cumulative frequencies, MPV, P-LCR, hsCRP, D-Dimer, and NT-proBNP all differed significantly (P<0.05 or 0.01). In AMI group, with RDW as the dependent variable, we established a multivariate regression model of RDW=0.19MPV+10.83. CONCLUSION: RDW and MPV are closely correlated in patients with AMI. In multiple regression analysis, MPV can explain the changes in RDW in patients with AMI.
Authors: Dariush Mozaffarian; Emelia J Benjamin; Alan S Go; Donna K Arnett; Michael J Blaha; Mary Cushman; Sandeep R Das; Sarah de Ferranti; Jean-Pierre Després; Heather J Fullerton; Virginia J Howard; Mark D Huffman; Carmen R Isasi; Monik C Jiménez; Suzanne E Judd; Brett M Kissela; Judith H Lichtman; Lynda D Lisabeth; Simin Liu; Rachel H Mackey; David J Magid; Darren K McGuire; Emile R Mohler; Claudia S Moy; Paul Muntner; Michael E Mussolino; Khurram Nasir; Robert W Neumar; Graham Nichol; Latha Palaniappan; Dilip K Pandey; Mathew J Reeves; Carlos J Rodriguez; Wayne Rosamond; Paul D Sorlie; Joel Stein; Amytis Towfighi; Tanya N Turan; Salim S Virani; Daniel Woo; Robert W Yeh; Melanie B Turner Journal: Circulation Date: 2015-12-16 Impact factor: 29.690
Authors: Nay Aung; Hua Zen Ling; Adrian S Cheng; Suneil Aggarwal; Julia Flint; Michelle Mendonca; Mohammed Rashid; Swan Kang; Susanne Weissert; Caroline J Coats; Toby Richards; Martin Thomas; Simon Woldman; Darlington O Okonko Journal: Int J Cardiol Date: 2013-01-22 Impact factor: 4.164
Authors: Muhammet Raşit Sayın; Nesimi Yavuz; Turgut Karabağ; Mehmet Ali Çetiner; İbrahim İlker Öz; Orhan Alper Güngördük; Mustafa Aydın Journal: Anatol J Cardiol Date: 2015-06-18 Impact factor: 1.596