本文已被：浏览 226次 下载 157次
投稿时间：2025-09-03 网络发布日期：2026-01-27
投稿时间：2025-09-03 网络发布日期：2026-01-27
中文摘要: 目的 探讨肌肉脂肪质量比（MFR）与2型糖尿病肾病（DKD）患者肾功能损伤的关系，为评估DKD进展风险提供客观依据。方法 采用横断面研究方法，纳入2023年5月至2025年5月南京医科大学附属无锡人民医院277例住院DKD患者。使用生物电阻抗法测量体成分指标，包括身体质量指数、MFR和骨骼肌质量指数；同步检测血肌酐（Scr）、血尿素氮（BUN）及尿微量白蛋白/肌酐比值（UACR），并依据慢性肾脏病流行病学协作组（CKD-EPI）公式计算估算肾小球滤过率（eGFR）。根据改善全球肾脏病预后组织（KDIGO）2022指南的CGA（病因-eGFR-白蛋白尿）分期系统，结合eGFR和UACR水平对患者进行风险分层分组：G1-2A2组［eGFR≥60 mL/（min·1.73 m2）且UACR 30~299 mg/g］、G1-2A3组［eGFR≥60 mL/（min·1.73 m2）且UACR≥300 mg/g］、G3A2组［eGFR 30~59 mL/（min·1.73 m2）且UACR 30~299 mg/g］、G3A3组［eGFR 30~59 mL/（min·1.73 m2）且UACR≥300 mg/g］及G4-5 A2-3组［eGFR<30 mL/（min·1.73 m2）且UACR≥30 mg/g］。采用Spearman相关分析体成分指标与肾功能参数的相关性，二元logistic回归分析肾功能受损［eGFR<60 mL/（min·1.73 m2）］的独立影响因素，并进一步建立多因素logistic回归模型评估MFR对DKD综合进展风险（基于CGA分期高危/极高危）的预测价值，并绘制受试者工作特征（ROC）曲线评估MFR对肾功能下降的预测效能。结果 随着肾功能恶化（从G1-2A2组至G4-5组），MFR呈降低趋势（P<0.01）。MFR与eGFR呈正相关（r=0.547，P<0.01），与Scr、BUN及UACR均呈负相关（r=-0.341、-0.328、-0.136，P<0.05）。多因素logistic回归分析显示，在校正年龄、病程及血脂等混杂因素后，标准化MFR（ZMFR）升高是肾功能受损的独立保护因素（Or=0.166，95%CI：0.098~0.280，P<0.01）；同时，ZMFR亦是DKD进展至高危阶段的独立保护因素（OR=0.621，95%CI：0.426~0.904，P=0.013）。ROC曲线分析显示，MFR预测肾功能下降［eGFR<60 mL/（min·1.73 m2）］的曲线下面积为0.813（P<0.01）。结论 MFR下降与DKD患者肾功能损伤独立相关，MFR升高是肾功能受损及CGA分期进展的独立保护因素，监测MFR变化有助于早期识别高危患者，并为DKD肌肉-脂代谢干预提供新思路。
Abstract:Objective To investigate the relationship between the muscle-to-fat ratio （MFR）and renal function impairment in patients with type 2 diabetic kidney disease（DKD），and to provide an objective basis for assessing the risk of DKD progression. Methods A cross- sectional study was conducted，involving 277 hospitalized DKD patients at Wuxi People’s Hospital Affiliated to Nanjing Medical University from May 2023 to May 2025. Body composition indicators，including body mass index（BMI），MFR，and skeletal muscle mass index（SMMI），were measured using bioelectrical impedance analysis（BIA）. Simultaneously，serum creatinine（Scr），blood urea nitrogen（BUN），andurinary microalbumin-to-creatinine ratio（UACR）were detected，and the estimated glomerular filtration rate（eGFR） was calculated using the Chronic Kidney Disease Epidemiology Collaboration（CKD?EPI）formula. According to the CGA （cause eGFR-albuminuria）staging system recommended by the Kidney Disease：Improving Global Outcomes（KDIGO）? 2020 guidelines，patients were stratified into risk groups based on combined eGFR and UACR levels：Group G1?2A2 ［eGFR≥60 mL/（min·1.73 m２ ）and UACR 30~299 mg/g］，Group G1-2A3［eGFR≥60 mL/（min·1.73 m２ ）and UACR≥ 300 mg/g］，Group G3A2［eGFR 30~59 mL/（min·1.73 m２ ）and UACR 30~299 mg/g］，Group G3A3［eGFR 30~59 mL/ （min·1.73 m２ ）and UACR≥300 mg/g］，and Group G4-5A2-3［eGFR＜30 mL/（min·1.73 m２ ）and UACR≥30 mg/g］. Spearman correlation analysis was used to examine the relationship between body composition indicators and renal function parameters. Binary logistic regression analysis was applied to identify independent influencing factors for renal impairment［eGFR<60 mL/（min·1.73 m２ ）］，and multivariate logistic regression was used to evaluate the predictive value of MFR for DKD progression risk based on CGA staging. Receiver operating characteristic（ROC）curves were plotted to assess the predictive efficacy of MFR for renal function decline. Results As renal function worsened（from the G1A1 group to the G3A group），MFR showed a decline trend（P<0.01）. MFR was positively correlated with eGFR（r= 0.547，P<0.01）and negatively correlated with Scr，BUN，and UACR（r=-0.341，-0.328，-0.136，P<0.05）. Multivariate logistic regression analysis indicated that standardized MFR（ZMFR）was an independent protective factor for renal impairment（OR=0.166，95%CI：0.098-0.280，P<0.01）after adjusting for confounding factors. Additionally，ZMFR was identified as an independent protective factor against the progression to high?risk DKD stages（95%OR=0.621，95%CI： 0.426- 0.904，P=0.013）. ROC analysis revealed that the area under the curve（AUC）for MFR in predicting renal function decline［eGFR<60 mL/（min·1.73 m2 ）］was 0.813（P<0.01）. Conclusion A decrease in MFR is independently associated with renal function impairment in DKD patients. An increase in MFR is an independent protective factor for renal impairment and the progression of CGA staging. Monitoring changes in MFR may help identify high- risk patients early and provide new insights into muscle?fat metabolism interventions for DKD.
keywords: Muscle-to-fat ratio Diabetic kidney disease Renal function impairment Cross-sectional study Bioelectrical impedance analysis
文章编号： 中图分类号：R587.2 文献标志码：A
基金项目:国家自然科学基金青年项目（82000685）
附件
| Author Name | Affiliation |
| CUI Siyuan，HU Yun，XU Xiang，LI Yang，ZHAO Han，ZHU Xiaowei | Department of Endocrinology,Wuxi People's Hospital Affiliated to Nanjing Medical University,Wuxi,Jiangsu 214000,China |
引用文本：
崔思远,胡蕴,徐湘,等.2型糖尿病肾病患者肌肉脂肪质量比与肾功能损伤的相关性[J].中国临床研究,2026,39(1):28-32,37.
崔思远,胡蕴,徐湘,等.2型糖尿病肾病患者肌肉脂肪质量比与肾功能损伤的相关性[J].中国临床研究,2026,39(1):28-32,37.