BACKGROUND. The red cell distribution width (RDW) is associated with health outcomes. Whether non-RDW risk information is contained in RBC sizes is unknown. This study evaluated the association of the percentage of extreme macrocytic RBCs (%Macro, RBC volume > 120 fl) and microcytic RBCs (%Micro, RBC volume < 60 fl) and the RDW–size distribution (RDW-sd) with mortality and morbidity. METHODS. Patients (females, n = 165,770; males, n = 100,210) at Intermountain Healthcare were studied if they had a hematology panel between May 2014 and September 2016. Adjusted sex-specific associations of %Macro/%Micro and RDW-sd with mortality and 33 morbidities were evaluated. RESULTS. Among females with fourth-quartile values of %Macro quartile and %Micro (referred to throughout as 4/4), there was an average of 7.2 morbidities versus 2.9 in the lowest risk (LR1) categories, 1/1, 1/2, 2/1, and 2/2 (P < 0.001). Among males, those in the 4/4 category had 8.0 morbidities, while those in the LR1 had 3.4 (P < 0.001). Cox regressions found %Macro/%Micro (4/4 vs. LR1, females: hazard ratio [HR] = 1.97 [95% CI = 1.53, 2.54]; males: HR = 2.17 [CI = 1.72, 2.73]), RDW-sd (quartile 4 vs. 1, females: HR = 1.33 [CI = 1.04, 1.69]; males: HR = 1.41 [CI = 1.10, 1.80]), and RDW (quartile 4 vs. 1, females: HR = 1.59 [CI = 1.26, 2.00]; males: HR = 1.23 [CI = 0.99, 1.52]) independently predicted mortality. Limitations include that the observational design did not reveal causality and unknown confounders may be unmeasured. CONCLUSIONS. Concomitantly elevated %Macro and %Micro predicted the highest mortality risk and the greatest number of morbidities, revealing predictive ability of RBC volume beyond what is measured clinically. Mechanistic investigations are needed to explain the biological basis of these observations. FUNDING. This study was supported by internal Intermountain Heart Institute funds and in-kind support from Sysmex America Inc.
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
Usage data is cumulative from September 2022 through September 2023.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.