浙江大学医学院附属第二医院健康管理中心,浙江 杭州 310009
沈国丽,主管护师,研究方向:护理和健康管理,E-mail:2503044@zju.edu.cn
纸质出版日期:2023-01-20,
收稿日期:2022-07-04,
扫 描 看 全 文
沈国丽,邵敏,蔡如意等.EZSCAN风险评分在肾功能轻度损伤人群中的筛查价值[J].中山大学学报(医学科学版),2023,44(01):115-121.
SHEN Guo-li,SHAO Min,CAI Ru-yi,et al.Value of EZSCAN for Screening Mild Renal Impairment[J].Journal of Sun Yat-sen University(Medical Sciences),2023,44(01):115-121.
沈国丽,邵敏,蔡如意等.EZSCAN风险评分在肾功能轻度损伤人群中的筛查价值[J].中山大学学报(医学科学版),2023,44(01):115-121. DOI: 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).2023.0115.
SHEN Guo-li,SHAO Min,CAI Ru-yi,et al.Value of EZSCAN for Screening Mild Renal Impairment[J].Journal of Sun Yat-sen University(Medical Sciences),2023,44(01):115-121. DOI: 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).2023.0115.
目的
2
自主神经功能障碍是慢性肾脏病(CKD)患者常见严重的并发症,且在CKD早期就会发生。汗腺功能障碍已被视为自主神经功能紊乱的初始组成部分。通过反向离子电渗疗法和计时电流法测量电化学皮肤电导(ESC)来评估汗腺功能,可能会检测出健康体检人群中轻度肾功能不全的患者,以便给予早期干预与治疗,延缓肾功能进一步恶化。
方法
2
EZSCAN分数 (0~100) 是基于计时电流分析的专有算法计算得出的。本研究入组了2020年1月至10月浙江大学医学院附属第二医院体检中心健康体检的6 661名受试者,包括肾功能下降[估算肾小球滤过率(eGFR) <90 mL·min
-1
·1.73 m
-2
]的2 075(31.15%)名受试者作为病例组和肾功能正常(90 mL·min
-1
·1.73 m
-2
≤ eGFR ≤ 120 mL·min
-1
·1.73 m
-2
)的4 586(68.85%)名受试者作为对照组。采用lasso回归筛选协变量,通过loess曲线和logistic回归分析风险评分与eGFR的关系。
结果
2
经过多变量调整后,风险评分与eGFR下降的风险相关,与risk值最低组(Q1<24)相比,Q2(25-27),Q3(28-47),Q4(48-75)的OR(95%CI)分别为1.84(1.54,2.20),2.47(2.08,2.94),2.41(2.05,2.83)。其中模型Ⅲ的ROC曲线下面积最大0.75(0.74,0.76),得出敏感度为73.98%,特异度为63%,阳性预测值为47.49%,阴性预测值为84.25%,约登指数为0.369 72,最佳截断值为25。
结论
2
EZSCAN是一种有效的筛选工具,可用于识别肾功能下降风险增加的健康体检人群,分数大于25应行相关实验室检测明确诊断。
Objective
2
Autonomic dysfunction is a common and serious complication in patients with early chronic kidney disease (CKD). Sweat gland dysfunction is an initial sign of autonomic dysfunction. Electrochemical skin conductance (ESC) measurement by reverse iontophoresis and chronoamperometry to assess sweat gland function may detect patients with mild renal insufficiency in healthy population for early intervention and treatment to delay further deterioration of renal function.
Methods
2
An EZSCAN score (0~100) was calculated using a proprietary algorithm based on the chronoamperometry analysis. A total of 6 661 subjects who received physical examination from the physical examination center of the Second Affiliated Hospital of Zhejiang University School of Medicine from January to October 2020 were enrolled, including 2 075 (31.15%) subjects with reduced renal function (eGFR
<
90 mL·min
-1
·1.73 m
-2
) as the case group and 4 586 (68.85%) subjects with normal renal function (90 mL·min
-1
·1.73 m
-2
≤ eGFR ≤120 mL·min
-1
·1.73 m
-2
) as the control group. Lasso regression was used to screen covariates, and the relationship between the risk score and eGFR was analyzed by loess curve and logistic regression.
Results
2
After multivariate adjustment, the risk score was correlated with the risk of eGFR decline. Compared with the group with the lowest risk value (Q1<24), the OR(95%CI )of Q2 (25-27), Q3 (28-47), and Q4 (48-75) were 1.85 (1.55, 2.21), 2.53 (2.13, 3.00), 2.49 (2.13, 2.93), respectively. The maximum area under the ROC curve is 0.75(0.74,0.76), the sensitivity is 73.98%, the specificity is 63%, the positive predictive value is 47.49%, the negative predictive value is 84.25%, and the Youden index is 0.369 72, the optimal cutoff value is 25.
Conclusions
2
EZSCAN could be a useful screening tool to identify healthy individuals at increased risk of renal function decline, and the one with an EZSCAN score of more than 25% should undergo diagnostic laboratory testing.
无创筛查技术肾功能损伤肾小球滤过率下降
non-invasive screening technologyrenal function damageeGFR decline
Bello AK, Levin A, Tonelli M, et al. Assessment of global kidney health care status[J]. JAMA, 2017, 317(18):1864-1881
Zhang L, Wang F, Wang L, et al. Prevalence of chronic kidney disease in China: a cross-sectional survey [J]. Lancet, 2012, 379(9818):815-822.
Coresh J, Selvin E, Stevens LA, et al. Prevalence of chronic kidney disease in the United States[J]. JAMA, 2007, 298(17):2038-2047.
Cheshire WP, Freeman R. Disorders of sweating [J]. Semin Neurol, 2003, 23(4): 399-406.
Low LA, Sandroni P, Fealey RD, et al. Detection of small-fiber neuropathy by sudomotor testing [J]. Muscle Nerve, 2006, 34:57–61.
Novak P. Electrochemical skin conductance: a systematic review [J]. Clin Auton Res, 2017, 29(1): 17-29.
Levey AS, De Jong PE , Coresh J , et al. The definition, classification, and prognosis of chronic kidney disease: a KDIGO controversies conference report [J]. Kidney International, 2011, 80(1):17-28.
Ozaki R, Cheung KK, Wu E, et al. A new tool to detect kidney disease in Chinese type 2 diabetes patients: comparison of EZSCAN with standard screening methods [J]. Diabetes Technol Ther, 2011, 13(9): 937-943.
Levin A, Stevens PE, Bilous RW, et al. Kidney Disease: improving global outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease [J]. Kidney int suppl, 2013, 3 (1):1-150.
Shlipak MG, Mattes MD, Peralta CA. Update on cystatin C: Incorporation into clinical practice[J]. Am J Kidney Dis, 2013, 62: 595-603.
Jafar TH, Chaturvedi N, Hatcher J, et al. Use of albumin creatinine ratio and urine albumin concentration as a screening test for albuminuria in an Indo-Asian population [J]. Nephrol Dial Transplant, 2007, 22: 2194-2200.
Xu R, Zhang L, Zhang P, et al. Gender-specific reference value of urine albumin-creatinine ratio in healthy Chinese adults: results of the Beijing CKD survey [J]. Clin Chim Acta, 2008, 398: 125–129.
Ewald B, Attia J. Which test to detect microalbuminuria in diabetic patients? a systematic review[J]. Aust Fam Physician, 2004, 571(33): 565-567.
Tonelli M, Dickinson JA. Early Detection of CKD: Implications for low-income, middle-income, and high-income countries [J]. J Am Soc Nephrol, 2020, 31(9): 1931-1940.
Norton JM, Ali K, Jurkovitz CT, et al. Development and validation of a pragmatic electronic phenotype for CKD[J]. Clin J Am Soc Nephrol, 2019, 14: 1306–1314.
Hubert D, Brunswick P, Calvet JH, et al. Abnormal electrochemical skin conductance in cystic fibrosis[J]. J Cyst Fibros, 2011, 10(1): 15-20.
Sheng CS, Zeng WF , Huang QF , et al. Accuracy of a Novel Non-I nvasive technology based EZSCAN system for the diagnosis of diabetes mellitus in Chinese[J]. Diabetol Metab Syndr, 2011, 3(1):36.
Freedman BI, Bowden DW, Smith SC, et al. Relationships between electrochemical skin conductance and kidney disease in Type 2 diabetes[J]. J Diabetes Complications, 2014, 28(1):56-60.
Freedman BI, Smith SC, Bagwell BM, et al. Electrochemical skin conductance in diabetic kidney disease[J]. Am J Nephrol, 2015; 41(6):438-447.
0
浏览量
0
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构