Cargando…

Monocyte–lymphocyte ratio is a valuable predictor for diabetic nephropathy in patients with type 2 diabetes

Diabetic nephropathy (DN) is serious threat to human health. Therefore, early prediction of its occurrence is important. This study aimed to assess the predictive significance of monocyte–lymphocyte ratio (MLR) for DN. A total of 301 patients with type 2 diabetes (T2D), including 212 T2D patients wi...

Descripción completa

Detalles Bibliográficos
Autores principales: Huang, Qinghua, Wu, Hui, Wo, Mingyi, Ma, Jiangbo, Fei, Xianming, Song, Yingxiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7220183/
https://www.ncbi.nlm.nih.gov/pubmed/32384513
http://dx.doi.org/10.1097/MD.0000000000020190
Descripción
Sumario:Diabetic nephropathy (DN) is serious threat to human health. Therefore, early prediction of its occurrence is important. This study aimed to assess the predictive significance of monocyte–lymphocyte ratio (MLR) for DN. A total of 301 patients with type 2 diabetes (T2D), including 212 T2D patients without diabetic-related complications and 99 DN patients, were enrolled. Peripheral white blood cells were measured before treatment to calculate MLR, and the risk factors and predictive significance for T2D and DN were assessed. T2D patients without diabetic-related complications had higher MLR than control patients (P < .01). However, MLR was significantly higher in DN patients than in T2D patients without diabetic-related complications (P < .001). According to MLR quartiles, higher MLR in DN patients was correlated with higher serum creatinine, estimated glomerular filtration rate, and urinary albumin excretion (UAE) levels (P < .01 or P < .001). Furthermore, MLR was positively correlated with UAE level (R(2) = 0.5973; P < .01) and an independent predictor for DN (odds ratio: 7.667; 95% confidence interval [CI]: 3.689–21.312; P < .001). The area under the receiver-operating characteristic (ROC) curve for MLR was 0.874 (95%CI: 0.830–0.918, P < .001). When the optimal cutoff value was 0.23, the sensitivity and specificity of MLR for DN prediction were 0.85 and 0.74, respectively. The present findings suggest that MLR is a powerful independent predictor for DN.