Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia · 2026
Red cell distribution width predicts chronic kidney disease in elderly uncontrolled type 2 diabetic patients.
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Soliman Amin R, Sadek Khaled Marzouk, Soliman Haytham, Maamoun Hoda Abdelhamid
Аннотация
BACKGROUND: Red cell distribution width (RDW) is a hematological parameter routinely obtained as part of the complete blood count. RDW has emerged as a potential independent predictor of clinical outcome in patients with established cardiovascular disease. RDW is associated with inflammation, ineffective erythropoiesis, undernutrition, iron deficiency, and impaired renal function in patients with heart failure. It is also associated with increased morbidity and mortality risk. No published data are available regarding the use of RDW as a predictor of kidney disease in type 2 diabetic patients.
PATIENTS AND METHODS: We collected sociodemographic parameters, medical and diabetes history, and laboratory data at baseline from 650 elderly type 2 diabetics. RDW was measured as part of a standard complete blood count measurement. To assess if RDW predicts nephropathy risk, we used Cox proportional hazards regression.
RESULTS: During 34-month follow-up, 105 patients developed diabetic kidney disease as evident with either micro/macro albuminuria or a rise in serum creatinine. Mean age was 53 ± 11 years, 66.6% of the patients were males, 33% were smokers. Mortality was significantly higher in patients with high versus low (above vs. below median) RDW at baseline. RDW was a significant predictor of renal morbidity both in an univariate model (HR1 increase = 1.611: 95% confidence interval [CI]: 1.292-1.926) and also in a multivariate model (HR1increase = 1.526; 95% CI: 1.285-1.905) adjusting for several variables (gender, eGFR, HbA1c, CRP, and albumin). RDW was also found to be an independent predictor of kidney affection in elderly diabetics with higher HbA1c.
CONCLUSIONS: RDW independently predicts kidney disease in elderly patients with type 2 diabetes mellitus.
PATIENTS AND METHODS: We collected sociodemographic parameters, medical and diabetes history, and laboratory data at baseline from 650 elderly type 2 diabetics. RDW was measured as part of a standard complete blood count measurement. To assess if RDW predicts nephropathy risk, we used Cox proportional hazards regression.
RESULTS: During 34-month follow-up, 105 patients developed diabetic kidney disease as evident with either micro/macro albuminuria or a rise in serum creatinine. Mean age was 53 ± 11 years, 66.6% of the patients were males, 33% were smokers. Mortality was significantly higher in patients with high versus low (above vs. below median) RDW at baseline. RDW was a significant predictor of renal morbidity both in an univariate model (HR1 increase = 1.611: 95% confidence interval [CI]: 1.292-1.926) and also in a multivariate model (HR1increase = 1.526; 95% CI: 1.285-1.905) adjusting for several variables (gender, eGFR, HbA1c, CRP, and albumin). RDW was also found to be an independent predictor of kidney affection in elderly diabetics with higher HbA1c.
CONCLUSIONS: RDW independently predicts kidney disease in elderly patients with type 2 diabetes mellitus.