中国血液净化

中国血液净化 ›› 2014, Vol. 13 ›› Issue (10): 703-707.doi: 10.3969/j.issn.1671-4091.2014.10.007

• 临床研究 • 上一篇    下一篇

生物电阻抗技术用于腹膜透析患者营养评估的研究

杜琇1, 任红1 ,谢静远1 ,黄晓敏1 ,张春燕1 ,施咏梅2 ,陈楠1   

  1. 上海交通大学医学院附属瑞金医院1肾脏科 2临床营养科
  • 收稿日期:2014-07-28 修回日期:2014-08-04 出版日期:2014-10-12 发布日期:2014-10-21
  • 通讯作者: 任红 renhong66@126.com E-mail:renhong66@126.com
  • 基金资助:

    国家重点基础研究发展计划：2012CB517604；中华医学会临床医学科研专项基金：13030280413；国家自然科学基金青年项目：81300633

Nutritional assessment of peritoneal dialysis patients by bioelectrical impedance analysis

  • Received:2014-07-28 Revised:2014-08-04 Online:2014-10-12 Published:2014-10-21

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摘要： 目的营养不良是腹膜透析(PD)患者的重要并发症，但目前缺乏准确客观的评估方法。本研究旨在探讨生物电阻抗技术在评估PD 患者营养不良中的作用。方法入选上海交通大学附属瑞金医院肾脏科随访的透析时间大于3 个月的PD 患者，近期内无严重感染、手术、外伤或急性心脑血管事件，患者本人同意参加本研究。对入选患者进行营养不良-炎症评分(malnutrition inflammation score，MIS)。以MIS 评分分组，0～8 分为营养良好，≥9 分为营养不良。采用生物电阻抗技术测量患者身体成分，记录患者透析起始年龄、血白蛋白、超敏CRP、铁蛋白、肌酐、残余肾功能、Kt/V 等。分析MIS 评分与身体成分指标及生化指标的相关性，通过多线性回归及ROC 分析探讨身体成分指标评价营养不良的作用。结果入选PD 患者183 例(男/女:113/70)，进入透析平均年龄为51.9±16.15 岁，平均透析时间为23(10～46)月。其中肾小球肾炎123 例(67.2%)，糖尿病肾病14 例(7.7%)，高血压肾病17 例(9.3%)，其他26 例(14.2%)，原因不明3 例(1.6%)。营养良好142 例(77.6%)，营养不良41 例(22.4%)。相关性分析显示MIS 评分与年龄(r=0.249)、超敏CRP(r=0.285)、铁蛋白(r=0.168)、水肿指数(r=0.354)、ECW/BCM(r=0.358) 等正相关(P＜0.05),与BMI(r=-0.227)、平均动脉压(r=-0.254)、白蛋白(r=-0.208)、残余肾功能(r=-0.214)、身体细胞量(r=-0.270)等负相关(P＜0.05)。多元线性回归显示患者年龄大(Beta=0.172，P=0.038)、铁蛋白水平升高(Beta=0.226，P=0.001)、ECW/BCM(Beta=2.494，P=0.04)升高是营养不良的独立危险因素，而女性(Beta=-0.336，P=0.003)、骨骼肌增多(Beta=-0.592，P=1.79E-08)、体脂百分比高(Beta=- 0.183，P=0.041)是营养不良的保护因素。ROC 曲线分析显示，ECW/ BCM(AUC=0.726，0.635～0.818)、水肿指数(AUC=0.721，0.629～0.813)、骨骼肌(AUC=0.665，0.572～0.758)、体脂百分比(AUC=0.643，0.549～0.736)等电阻抗参数可以较好预测营养不良的发生。结论MIS 评分是腹膜透析(PD)患者营养评估的有效指标，采用该评分方法本中心PD 患者营养不良发生率为22.4%。生物电阻抗技术可用于PD 患者营养评估，其中ECW/BCM、水肿指数、骨骼肌和体脂百分比等参数对预测PD 患者营养不良尤为重要。

Abstract: Objective Malnutrition is a major complication in peritoneal dialysis (PD) patients. However, there are no efficient and accurate approaches for nutritional assessment in these patients so far. The aim of this study was to validate the bioelectrical impedance analysis (BIA) for malnutrition assessment in PD patients
and to analyze malnutrition in PD patients. Methods Clinically stable patients with PD for more than 3 months, willing to take part in this study, and without acute coronary syndrome, surgery, and intravenous antibiotics treatment for severe infection in recent days were recruited. Nutrition status was evaluated by malnutrition inflammation score (MIS) that consists of 10 items with a total score ranging from 0～30 points. Patients were divided into two groups, well- nutritional group (MIS 0～8) and malnutritional group (MIS≥9). BIA was performed to evaluate body composition of the PD patients. Clinical and laboratory data including age, residual renal function, Kt/V and nutritional biomarkers (albumin, hs-CRP, feritin and creatinine) at the beginning of PD were recorded. Results We recruited 183 PD patients (113 males and 70 females) with an average age of 51.9±16.15 years and an average PD period of 23 (10～46) months. The primary diseases for end-stage renal disease included glomerulonephritis (67.2%), diabetic nephropathy (7.7%), hypertensive nephropathy (9.3%), other diseases (14.2%) and unknown origin (1.6%). Forty-one patients (22.4%) had moderate to severe malnutrition evaluated by MIS. MIS level was positively correlated with age (r= 0.249), hs-CRP (r= 0.285), feritin (r=0.168), edema index (EI) (r=0.354) and ECW/BCM (r=0.358), and negatively correlated with BMI (r=-0.227), mean arterial pressure (r=-0.254), albumin (r=-0.208), residual renal function (r=-0.214) and body cell mass (r=-0.270). Multiple linear regression analysis found that elder (β=0.172, P=0.038), elevated feritin (β=0.226, P=0.001) and higher ECW/BCM (β=2.494, P=0.04) were the independent risk factors for
malnutrition; while female (β=-0.336, P=0.003), higher level of skeletal muscle (β=-0.592, P=1.79E-08), and higher percentage of body fat (β =-0.183, P=0.041) were the protect factors for malnutrition. ROC analysis showed that the BIA parameters including ECW/BCM, EI, skeletal muscle and body fat percentage could effectively predict malnutrition. Conclusion In this study, the malnutrition rate evaluated by MIS system was 22.4% in PD patients. BIA parameters including ECW/BCM, EI, skeletal muscle and body fat percentage are useful for the assessment of nutrition status in PD patients.