Charlson Comorbidity Index Helps Predict the Risk of Mortality for Patients with Type 2 Diabetic Nephropathy

Overview

Journal J Zhejiang Univ Sci B

Specialties Biology
General Medicine

Date 2014 Jan 7

PMID 24390745

Citations 107

Authors

You-qun Huang

Rong Gou

Yong-Shu Diao

Qing-Hua Yin

Wen-xing Fan

Ya-Ping Liang

Yi Chen

Min Wu

Li Zang

Ling Li

Jing Zang

Lu Cheng

Ping Fu

Fang Liu

Affiliations

Soon will be listed here.

Abstract

Our intent is to examine the predictive role of Charlson comorbidity index (CCI) on mortality of patients with type 2 diabetic nephropathy (DN). Based on the CCI score, the severity of comorbidity was categorized into three grades: mild, with CCI scores of 1-2; moderate, with CCI scores of 3-4; and severe, with CCI scores ≥5. Factors influencing mortality and differences between groups stratified by CCI were determined by logistical regression analysis and one-way analysis of variance (ANOVA). The impact of CCI on mortality was assessed by the Kaplan-Meier analysis. A total of 533 patients with type 2 DN were enrolled in this study, all of them had comorbidity (CCI score >1), and 44.7% (238/533) died. The mortality increased with CCI scores: 21.0% (50/238) patients with CCI scores of 1-2, 56.7% (135/238) patients with CCI scores of 3-4, and 22.3% (53/238) patients with CCI scores ≥5. Logistical regression analysis showed that CCI scores, hemoglobin, and serum albumin were the potential predictors of mortality (P<0.05). One-way ANOVA analysis showed that DN patients with higher CCI scores had lower levels of hemoglobulin, higher levels of serum creatinine, and higher mortality rates than those with lower CCI scores. The Kaplan-Meier curves showed that survival time decreased when the CCI scores and mortality rates went up. In conclusion, CCI provides a simple, readily applicable, and valid method for classifying comorbidities and predicting the mortality of type 2 DN. An increased awareness of the potential comorbidities in type 2 DN patients may provide insights into this complicated disease and improve the outcomes by identifying and treating patients earlier and more effectively.

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