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Disease Markers
Volume 2016, Article ID 7304538, 13 pages
Research Article

Measurement of the Red Blood Cell Distribution Width Improves the Risk Prediction in Cardiac Resynchronization Therapy

1Heart and Vascular Center, Semmelweis University, Városmajor Utca 68, Budapest 1122, Hungary
2Third Department of Internal Medicine, Semmelweis University, Budapest, Hungary

Received 14 October 2015; Revised 7 December 2015; Accepted 24 December 2015

Academic Editor: Alberto Marra

Copyright © 2016 András Mihály Boros et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Objectives. Increases in red blood cell distribution width (RDW) and NT-proBNP (N-terminal pro-B-type natriuretic peptide) predict the mortality of chronic heart failure patients undergoing cardiac resynchronization therapy (CRT). It was hypothesized that RDW is independent of and possibly even superior to NT-proBNP from the aspect of long-term mortality prediction. Design. The blood counts and serum NT-proBNP levels of 134 patients undergoing CRT were measured. Multivariable Cox regression models were applied and reclassification analyses were performed. Results. After separate adjustment to the basic model of left bundle branch block, beta blocker therapy, and serum creatinine, both the RDW > 13.35% and NT-proBNP > 1975 pg/mL predicted the 5-year mortality (). In the final model including all variables, the RDW [HR = 2.49 (1.27–4.86); ] remained a significant predictor, whereas the NT-proBNP [HR = 1.18 (0.93–3.51); ] lost its predictive value. On addition of the RDW measurement, a 64% net reclassification improvement and a 3% integrated discrimination improvement were achieved over the NT-proBNP-adjusted basic model. Conclusions. Increased RDW levels accurately predict the long-term mortality of CRT patients independently of NT-proBNP. Reclassification analysis revealed that the RDW improves the risk stratification and could enhance the optimal patient selection for CRT.