Benjamin D Horne1,2, Joseph B Muhlestein1,3, Sterling T Bennett4,5, Joseph Boone Muhlestein3, Brianna S Ronnow1, Heidi T May1, Tami L Bair1, Jeffrey L Anderson1,3. 1. Intermountain Heart Institute, Intermountain Medical Center, Salt Lake City, UT, USA. 2. Genetic Epidemiology Division, Department of Medicine, University of Utah, Salt Lake City, UT, USA. 3. Cardiology Division, Department of Medicine, University of Utah, Salt Lake City, UT, USA. 4. Intermountain Central Laboratory, Intermountain Medical Center, Salt Lake City, UT, USA. 5. Department of Pathology, University of Utah, Salt Lake City, UT, USA.
Abstract
BACKGROUND: The red cell distribution width (RDW) predicts mortality among many populations. RDW is calculated as the standard deviation (SD) of the red blood cell (RBC) volume divided by mean corpuscular volume (MCV). Because higher MCV also predicts mortality, we hypothesized that the RDW numerator (one SD of RBC volume or 1SD-RDW) predicts mortality more strongly than the RDW. MATERIAL AND METHODS: Adult subjects hospitalized during a contemporary clinical era (10/2005-1/2014, N = 135,963) and a historical era (1/1999-9/2005, N = 119,530) were studied. The RDW was obtained from the complete blood count (CBC), while 1SD-RDW was calculated (RDW multiplied by MCV and divided by 100). RESULTS: In univariable Cox regression (2005-2014 cohort), 1SD-RDW (quintile 5 vs. 1: hazard ratio [HR] = 8.38, 95% confidence interval [CI] = 7.94, 8.85; P < 0.001) was a superior predictor of mortality compared to RDW (quintile 5 vs. 1: HR = 4.78, CI = 4.57, 5.00; P < 0.001). This superiority remained after adjustment for age, sex, basic metabolic profile components and other CBC factors excluding MCV (1SD-RDW: HR = 2.41, CI = 2.28, 2.55; RDW: HR = 2.01, CI = 1.92, 2.11). Further adjustment for MCV strengthened the RDW association (HR = 2.14, CI = 2.04, 2.24; P < 0.001), becoming indistinct from 1SD-RDW (HR = 2.20, CI = 2.08, 2.33; P < 0.001). Findings were similar for the 1999-2005 cohort. CONCLUSIONS: The 1SD-RDW predicted mortality more strongly than RDW, suggesting that 1SD-RDW is superior to RDW as an individual risk predictor. Further, these results indicate that the dispersion of RBC volume and its mean are independent risk markers. Further research is required to understand the clinical value and mechanistic basis of these associations.
BACKGROUND: The red cell distribution width (RDW) predicts mortality among many populations. RDW is calculated as the standard deviation (SD) of the red blood cell (RBC) volume divided by mean corpuscular volume (MCV). Because higher MCV also predicts mortality, we hypothesized that the RDW numerator (one SD of RBC volume or 1SD-RDW) predicts mortality more strongly than the RDW. MATERIAL AND METHODS: Adult subjects hospitalized during a contemporary clinical era (10/2005-1/2014, N = 135,963) and a historical era (1/1999-9/2005, N = 119,530) were studied. The RDW was obtained from the complete blood count (CBC), while 1SD-RDW was calculated (RDW multiplied by MCV and divided by 100). RESULTS: In univariable Cox regression (2005-2014 cohort), 1SD-RDW (quintile 5 vs. 1: hazard ratio [HR] = 8.38, 95% confidence interval [CI] = 7.94, 8.85; P < 0.001) was a superior predictor of mortality compared to RDW (quintile 5 vs. 1: HR = 4.78, CI = 4.57, 5.00; P < 0.001). This superiority remained after adjustment for age, sex, basic metabolic profile components and other CBC factors excluding MCV (1SD-RDW: HR = 2.41, CI = 2.28, 2.55; RDW: HR = 2.01, CI = 1.92, 2.11). Further adjustment for MCV strengthened the RDW association (HR = 2.14, CI = 2.04, 2.24; P < 0.001), becoming indistinct from 1SD-RDW (HR = 2.20, CI = 2.08, 2.33; P < 0.001). Findings were similar for the 1999-2005 cohort. CONCLUSIONS: The 1SD-RDW predicted mortality more strongly than RDW, suggesting that 1SD-RDW is superior to RDW as an individual risk predictor. Further, these results indicate that the dispersion of RBC volume and its mean are independent risk markers. Further research is required to understand the clinical value and mechanistic basis of these associations.
Authors: Benjamin D Horne; Joseph B Muhlestein; Sterling T Bennett; Joseph Boone Muhlestein; Kurt R Jensen; Diane Marshall; Tami L Bair; Heidi T May; John F Carlquist; Matthew Hegewald; Stacey Knight; Viet T Le; T Jared Bunch; Donald L Lappé; Jeffrey L Anderson; Kirk U Knowlton Journal: JCI Insight Date: 2018-07-26
Authors: Denitza P Blagev; Dave S Collingridge; Susan Rea; Benjamin D Horne; Valerie G Press; Matthew M Churpek; Kyle A Carey; Richard A Mularski; Siyang Zeng; Mehrdad Arjomandi Journal: Front Med (Lausanne) Date: 2018-06-11
Authors: Denitza P Blagev; Dave S Collingridge; Susan Rea; Kyle A Carey; Richard A Mularski; Siyang Zeng; Mehrdad Arjomandi; Valerie G Press Journal: BMJ Open Respir Res Date: 2020-02