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Association of standard clinical and laboratory variables with red blood cell distribution width
Patrícia O Guimarães1, Jie-Lena Sun1, Kristian Kragholm1
1Duke Clinical Research Institute, Duke University Medical Center, Durham, NC.
Insights
High red blood cell distribution width (RDW) predicts poor outcomes in heart patients. However, known clinical factors explain little of the RDW variation, suggesting unknown factors influence risk.
Area of Science:
- Cardiovascular Medicine
- Hematology
- Clinical Epidemiology
Background:
- Red blood cell distribution width (RDW) is a strong predictor of clinical outcomes in patients with coronary artery disease and heart failure.
- The underlying factors contributing to this predictive association remain largely unknown.
Purpose of the Study:
- To investigate the association between RDW and adverse clinical outcomes (death, myocardial infarction) in patients undergoing coronary angiography.
- To identify clinical factors associated with variations in RDW using multivariable regression analysis.
Main Methods:
- Cox proportional hazards modeling was used to assess the association between RDW and outcomes in 6,447 individuals from the MURDOCK Study.
- Multiple linear regression with R(2) model selection identified clinical factors related to RDW variation.
Main Results:
- RDW was independently associated with increased risk of death (aHR 1.13 per 1% increase) and death or myocardial infarction (aHR 1.12).
- A multivariable model including 18 variables explained only 21% of the variation in RDW, despite assessing 27 clinical and laboratory measures.
Conclusions:
- While RDW strongly predicts adverse outcomes in cardiovascular patients, routine clinical factors explain limited variation.
- Further research into the latent factors influencing RDW is needed to understand its prognostic role and identify potential therapeutic targets.
Background:
Red blood cell distribution width (RDW) strongly predicts clinical outcomes among patients with coronary disease and heart failure. The factors underpinning this association are unknown.
Methods:
In 6,447 individuals enrolled in the Measurement to Understand the Reclassification of Disease of Cabarrus/Kannapolis (MURDOCK) Study who had undergone coronary angiography between 2001 and 2007, we used Cox proportional hazards modeling to examine the adjusted association between RDW and death, and death or myocardial infarction (MI). Multiple linear regression using the R(2) model selection method was then used to identify clinical factors associated with variation in RDW.
Results:
Median follow-up was 4.2 (interquartile range 2.3-5.9) years, and the median RDW was 13.5% (interquartile range 12.9%-14.3%, clinical laboratory reference range 11.5%-14.5%). Red blood cell distribution width was independently associated with death (adjusted hazard ratio 1.13 per 1% increase in RDW, 95% CI 1.09-1.17), and death or MI (adjusted hazard ratio 1.12, 95% CI 1.08-1.16). Twenty-seven clinical characteristics and laboratory measures were assessed in the multivariable linear regression model; a final model containing 18 variables explained only 21% of the variation in RDW.
Conclusions:
Although strongly associated with death and death or MI, only one-fifth of the variation in RDW was explained by routinely assessed clinical characteristics and laboratory measures. Understanding the latent factors that explain variation in RDW may provide insight into its strong association with risk and identify novel targets to mitigate that risk.
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