不同肾小球滤过率估算方程在15~18岁慢性肾脏病儿童中应用比较

doi:10.12372/jcp.2022.21e1353

Abstract

Abstract:

Objective To compare the accuracy and applicability of eight estimation formulas for glomerular filtration rate (GFR) in children aged 15-18 years with chronic kidney disease (CKD). Methods Children with CKD hospitalized from January 2015 to March 2021 wereenrolled. Eight eGFR formulas (update Schwartz formula, CAPA formula, Counahan-Barratt formula, Filler formula, CKD-EPI-Scr2009, CKD-EPI-CysC2012, LMR18, FAS formula) were applied to estimate GFR. The Gates method of 99mTc-DTPA renal dynamic imaging was used as the gold standard GFR (sGFR) determination. The bias, precision and accuracy of each formula were compared, and the diagnostic efficacy of each formula for renal insufficiency was analyzed. Results A total of 88 children were enrolled, including 56 boys and 32 girls, and the median age was 17.0 (16.0-18.0) years. There were 56 cases of CKD stage 1, 18 cases of CKD stage 2, 11 cases of CKD stage 3, 2 cases of CKD stage 4, and 1 case of CKD stage 5. The eGFR in all formulas was positively correlated with sGFR (all P<0.001). The CKD-EPI-Scr2009 formula had the best correlation with sGFR (r=0.73), and the Filler formula had the worst correlation with sGFR (r=0.39). The CAPA, CKD-EPI-Scr2009 and FAS formulas overestimated the GFR on the overall level, while the other formulas underestimated GFR. When sGFR was used as the gold standard, the FAS formula had the smallest bias and the CAPA formula had the largest bias. In terms of precision, the LMR18 formula showed the best precision, followed by the update Schwartz formula, and the CAPA formula showed the worst precision. In terms of accuracy, the LMR18 formula showed the highest accuracy (P₃₀=73.86%). ROC curve analysis showed that the area under the curve (AUC) of the CKD-EPI-Scr2009 formula was the largest (0.907), the sensitivity of CAPA, Filler, and CKD-EPI-CysC2012 formulas were the highest (95.90%), and the specificity of LMR18 and FAS formulas were the highest (85.71%). Conclusions Among the eight eGFR formulas, the accuracy of CysC-based formulas (CAPA, Filler and CKD-EPI-CysC2012 formula) is not as good as Scr-based formulas (update Schwartz, Counahan-Barratt, CKD-EPI-Scr2009, LMR18 and FAS formula), and LMR18 formula has the highest precision and accuracy.

Key words: chronic kidney disease, glomerular filtration rate, formula, child

KUANG Qianhuining, GAO Chunlin, ZHU Hong, YANG Xiao, PENG Yingchao, XIA Zhengkun. Comparison of different estimation formulas of glomerular filtration rate in children aged 15-18 years with chronic kidney disease[J].Journal of Clinical Pediatrics, 2022, 40(12): 905-911.

Figures/Tables 6

References 29

[1]	Al-Aly Z, Bowe B. Biomarkers of CKD in children[J]. J Am Soc Nephrol, 2020, 31(5): 894-896. doi: 10.1681/ASN.2020020212 pmid: 32234830
[2]	Furth SL, Pierce C, Hui WF, et al. Estimating time to ESRD in children with CKD[J]. Am J Kidney Dis, 2018, 71(6): 783-792. doi: S0272-6386(18)30101-X pmid: 29653769
[3]	王学晶. 儿童肾小球滤过率的评估方法[J]. 中华儿科杂志, 2016, 54(7): 539-542.
[4]	Mian AN, Schwartz GJ. Measurement and estimation of glomerular filtration rate in children[J]. Adv Chronic Kidney Dis, 2017, 24(6): 348-356. doi: 10.1053/j.ackd.2017.09.011
[5]	吕潇阳, 钟良宝, 王善志, 等. 肾小球滤过率评估方程在中国糖尿病合并慢性肾脏病患者中的适用性评价[J]. 临床肾脏病杂志, 2019, 19(10): 719-726.
[6]	妇幼健康研究会, 妇女儿童肥胖控制专业委员会, 中国儿童代谢健康型肥胖定义与管理专家委员会. 中国儿童代谢健康型肥胖定义与筛查专家共识[J]. 中国妇幼健康研究, 2019, 30(12): 1487-1490.
[7]	孟群, 吴冬雪, 刘小荣, 等. 儿童慢性肾脏病营养状况及其影响因素分析[J]. 中国实用儿科杂志, 2015, 30(1): 51-54.
[8]	Haycock GB, Schwartz GJ, Wisotsky DH. Geometric method for measuring body surface area: a height-weight formula validated in infants, children, and adults[J]. J Pediatr, 1978, 93(1): 62-66.
[9]	Schwartz GJ, Muñoz A, Schneider MF, et al. New equations to estimate GFR in children with CKD[J]. J Am Soc Nephrol, 2009, 20(3): 629-637. doi: 10.1681/ASN.2008030287 pmid: 19158356
[10]	Grubb A, Horio M, Hansson LO, et al. Generation of a new cystatin C-based estimating equation for glomerular filtration rate by use of 7 assays standardized to the international calibrator[J]. Clin Chem, 2014, 60(7): 974-986. doi: 10.1373/clinchem.2013.220707 pmid: 24829272
[11]	Padgett D, Ostrenga A, Lepard L. Comparison of methods of estimating creatinine clearance in pediatric patients[J]. Am J Health Syst Pharm, 2017, 74(11): 826-830. doi: 10.2146/ajhp151004
[12]	Filler G, Lepage N. Should the Schwartz formula for estimation of GFR be replaced by cystatin C formula?[J]. Pediatr Nephrol, 2003, 18(10): 981-985. pmid: 12920638
[13]	Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate[J]. Ann Intern Med, 2009, 150(9): 604-612. doi: 10.7326/0003-4819-150-9-200905050-00006 pmid: 19414839
[14]	Terpos E, Christoulas D, Kastritis E, et al. The Chronic Kidney Disease Epidemiology Collaboration cystatin C (CKD-EPI-CysC) equation has an independent prognostic value for overall survival in newly diagnosed patients with symptomatic multiple myeloma; is it time to change from MDRD to CKD-EPI-CysC equations?[J]. Eur J Haematol, 2013, 91(4): 347-355. doi: 10.1111/ejh.12164 pmid: 23829647
[15]	Björk J, Nyman U, Delanaye P, et al. A novel method for creatinine adjustment makes the revised Lund-Malmö GFR estimating equation applicable in children[J]. Scand J Clin Lab Invest, 2020, 80(6): 456-463. doi: 10.1080/00365513.2020.1774641
[16]	Pottel H, Hoste L, Dubourg L, et al. An estimated glomerular filtration rate equation for the full age spectrum[J]. Nephrol Dial Transplant, 2016, 31(5): 798-806. doi: 10.1093/ndt/gfv454
[17]	National Kidney Foundation. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease [S]. Kidney International Supplements, 2013, 3: 1-150.
[18]	石鑫淼, 刘贝妮, 钟旭辉, 等. 儿童慢性肾脏病流行病学研究进展[J]. 中华儿科杂志, 2019, 57(9): 721-724.
[19]	Weingart C, Wirnsberger GH. Clinical implications of the estimated glomerular filtration rate[J]. Z Gerontol Geriatr, 2021, 54(3): 205-210. doi: 10.1007/s00391-021-01839-1
[20]	Selistre L, De Souza V, Cochat P, et al. GFR estimation in adolescents and young adults[J]. J Am Soc Nephrol, 2012, 23(6): 989-996. doi: 10.1681/ASN.2011070705 pmid: 22499586
[21]	Selistre L, Rabilloud M, Cochat P, et al. Comparison of the Schwartz and CKD-EPI equations for estimating glomerular filtration rate in children, adolescents, and adults: a retrospective cross-sectional study[J]. PloS Med, 2016, 13(3): e1001979. doi: 10.1371/journal.pmed.1001979
[22]	Webster-Clark M, Jaeger B, Zhong Y, et al. Low agreement between modified-Schwartz and CKD-EPI eGFR in young adults: a retrospective longitudinal cohort study[J]. BMC Nephrol, 2018, 19(1): 194. doi: 10.1186/s12882-018-0995-1 pmid: 30081844
[23]	Björk J, Grubb A, Sterner G, et al. Revised equations for estimating glomerular filtration rate based on the Lund-Malmö Study cohort[J]. Scan J Clin Lab Invest, 2011, 71(3): 232-239. doi: 10.3109/00365513.2011.557086
[24]	Nyman U, Berg U, Grubb A, et al. GFR estimation in children-age-adjusted creatinine makes the adult Lund-Malmö equation applicable in children and facilitates automatic GFR reporting from the clinical laboratory[J]. Lakartidningen, 2021, 118: 20134.
[25]	Gowrishankar M, VanderPluym C, Robert C, et al. Value of serum cystatin C in estimating renal function in children with non-renal solid organ transplantation[J]. Pediatr Transplant, 2015, 19(1): 27-34. doi: 10.1111/petr.12381 pmid: 25377124
[26]	Podracka L, Feber J, Lepage N, et al. Intra-individual variation of cystatin C and creatinine in pediatric solid organ transplant recipients[J]. Pediatr Transplant, 2010, 9(1): 28-32. doi: 10.1111/j.1399-3046.2005.00235.x
[27]	Huidobro E JP, Guzmán AM, Tagle R. Use of cystatin C to estimate glomerular filtration rate[J]. Rev Med Chil, 2021, 149(1): 98-102. doi: 10.4067/S0034-98872021000100098
[28]	Zheng K, Gong M, Qin Y, et al. Validation of glomerular filtration rate-estimating equations in Chinese children[J]. PloS One, 2017, 12(7): e0180565.
[29]	Feldman HI, Briggs JP. Race and the estimation of GFR: getting it right[J]. J Am Soc Nephrol, 2021, 32(6): 1269-1270. doi: 10.1681/ASN.2021020206 pmid: 33837121

估算公式	表达式/mL·(min·1.73 m²)^-1
改良Schwartz	0.413×身高/cm·Scr(mg·dL ^-1)^-1
CAPA	130×CysC^-1.069×年龄^0.117-7
Counahan-Barratt	0.43×身高cm·Scr(mg·dL^-1)^-1
Filler	91.62×CysC^-1.123/mg·L ^-1
CKD-EPI-Scr 2009 男性 Scr≤0.9/mg·dL^-1 Scr >0.9/mg·dL ^-1 女性 Scr≤0.7/mg·dL^-1 Scr >0.7/mg·dL^-1	141×(Scr/0.9)^-0.411×0.993^年龄 141×(Scr/0.9)^-1.209×0.993^年龄 141×(Scr/0.7)^-0.329×0.993^年龄 141×(Scr/0.7)^-1.209×0.993^年龄
CKD-EPI-CysC 2012 CysC≤0.8/mg·dL^-1 CysC >0.8/mg·dL^-1	133×(CysC/0.8)^-0.499×0.996^年龄×0.932^女性 133×(CysC/0.8)^-1.328×0.996^年龄×0.932^女性
LMR18	LMR18=e^{X-0.0158×max（年龄；18）+0.438×ln[max（年龄；18）]}
男性 ln（$(\widehat{C r})$）=ln（Cr）+0.259×(18-年龄)-0.543× ln(18/年龄)-0.00763×(18²-年龄²)+0.0000790×(18³-年龄³)
$(\widehat{C r})$<180 /μmol·L^-1 $(\widehat{C r})$≥180 /μmol·L^-1	X=2.56+0.00968×(180-$(\widehat{C r})$) X=2.56-0.926×ln($(\widehat{C r})$/180)
女性 ln（$(\widehat{C r})$）=ln（Cr）+0.177×(18-年龄)-0.223× ln(18/年龄)-0.00596×(18²-年龄²)+0.0000686×(18³-年龄³)
$(\widehat{C r})$<150μmol·L^-1 $(\widehat{C r})$≥150 /μmol·L^-1	X=2.50+0.0121×(150-$(\widehat{C r})$) X=2.50-0.926×ln（$(\widehat{C r})$/150）
FAS	FAS-eGFR=107.3·(Scr/Q^#)^-1

性别	例数	年龄/岁	Scr/μmol·L^-1	CysC/mg·L^-1	身高/cm	体重/kg
男性	56	17.0(16.0~17.0)	78.2(65.0~91.9)	1.1(0.9~1.3)	172.9±5.7	68.6±15.7
女性	32	16.0(16.0~18.0)	62.0(51.8~88.5)	1.1(0.8~1.9)	165.2±5.6	56.5±8.5
统计量		Z=0.35	Z=0.55	Z=1.32	t=6.15	t=4.01
P		0.730	0.582	0.191	<0.001	<0.001

估算公式	eGFR	Pearson相关
估算公式	eGFR	r值	P
改良Schwartz	83.4±31.0	0.664	<0.001
CAPA	160.2±72.2	0.396	<0.001
Counahan-Barratt	84.9±37.6	0.664	<0.001
Filler	86.8±32.3	0.394	<0.001
CKD-EPI-Scr2009	110.7±37.1	0.732	<0.001
CKD-EPI-CysC2012	80.6±36.4	0.443	<0.001
LMR18	82.8±28.2	0.708	<0.001
FAS	95.1±34.0	0.678	<0.001

估算公式	偏倚	精确性/%	准确性/%
改良Schwartz	-10.05	25.61	63.64
CAPA	66.75	65.83	30.68
Counahan-Barratt	-6.62	26.16	62.50
Filler	-8.54	38.43	45.45
CKD-EPI-Scr2009	17.29	25.73	53.41
CKD-EPI-CysC2012	-12.87	36.14	45.45
LMR18	-10.63	22.94	73.86
FAS	1.69	26.41	61.36

估算公式	最佳截断值	AUC	95%CI	约登指数	灵敏度/%	特异度/%
改良Schwartz	57.91	0.89	0.77~1.00	0.72	93.20	78.57
CAPA	76.90	0.82	0.67~0.97	0.60	95.90	64.29
Counahan-Barratt	60.30	0.89	0.77~1.00	0.72	93.20	78.57
Filler	41.30	0.82	0.67~0.97	0.60	95.90	64.29
CKD-EPI-Scr2009	87.06	0.91	0.82~1.00	0.71	91.90	78.57
CKD-EPI-CysC2012	36.23	0.82	0.67~0.97	0.60	95.90	64.29
LMR18	76.71	0.89	0.78~1.00	0.68	82.40	85.71
FAS	81.77	0.89	0.77~1.00	0.71	85.10	85.71

Comparison of different estimation formulas of glomerular filtration rate in children aged 15-18 years with chronic kidney disease

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 6

References 29

Related Articles 15

Metrics

Comments

Recommended 0

[1]	ZOU Liping. Childhood encephalopathy: a group of diseases associated with various diseases [J]. Journal of Clinical Pediatrics, 2023, 41(9): 641-643.
[2]	ZHANG Weihua, ZOU Liping, REN Haitao, GUAN Hongzhi. Beware of the pitfalls in diagnosis and treatment of autoimmune encephalitis in children [J]. Journal of Clinical Pediatrics, 2023, 41(9): 644-649.
[3]	HOU Chi, CHEN Wenxiong, LIAO Yinting, WU Wenxiao, TIAN Yang, ZHU Haixia, PENG Bingwei, ZENG Yiru, WU Wenlin, CHEN Zongzong, LI Xiaojing. Clinical analysis of autoimmune glial fibrillary acidic protein astrocytopathy in children [J]. Journal of Clinical Pediatrics, 2023, 41(9): 656-660.
[4]	YANG Yating, CAI Yuehao, FANG Qiong, CHEN Lang, CHEN Qiaobin, LIN Zhi, WU Feifei, LIN Meng. Clinical analysis of idiopathic and symptomatic occipital lobe epilepsy in children [J]. Journal of Clinical Pediatrics, 2023, 41(9): 668-673.
[5]	HOU Ruolin, WU Jing, LI Ling. Pediatric autoimmune encephalitis with brain MRI showing meningeal thickening and enhancement [J]. Journal of Clinical Pediatrics, 2023, 41(9): 674-679.
[6]	WU Yuefang, SUN Yanling, WU Wanshui, DU Shuxu, LI Miao, SUN Liming. Analysis of prognostic factors and survival status of group 4 medulloblastoma in children [J]. Journal of Clinical Pediatrics, 2023, 41(9): 686-691.
[7]	SUN Juan, LI Haiying, JIA Peisheng, WANG Huaili. Clinical analysis of fulminant myocarditis in 12 children [J]. Journal of Clinical Pediatrics, 2023, 41(9): 692-696.
[8]	Reviewer: WANG Chenhui, Reviser: YANG Hui. Research progress on early screening and diagnosis of Crohn's disease in children [J]. Journal of Clinical Pediatrics, 2023, 41(9): 708-714.
[9]	SHEN Nan, DU Bailu. Strategies for the diagnosis, treatment, and management of invasive fungal infections in children with hematologic neoplasms [J]. Journal of Clinical Pediatrics, 2023, 41(8): 571-577.
[10]	XU Beixue, LIU Quanbo. Clinical analysis of 195 children with invasive pulmonary fungal infection [J]. Journal of Clinical Pediatrics, 2023, 41(8): 584-588.
[11]	CHEN Hongyu, LIU Zihao, WANG Heping, LIAO Cuijuan, LI Li, WANG Wenjian, LAI Jianwei. Role of nontypeable Haemophilus influenzae biofilms in chronic pulmonary infection in children [J]. Journal of Clinical Pediatrics, 2023, 41(8): 589-593.
[12]	KANG Lei, GUO Fang, LI Lifang, BAI Xinfeng, CHENG Caiyun, XU Meixian. Value of metagenomic next-generation sequencing in children with visceral leishmaniasis associated with hemolytic histiocytosis [J]. Journal of Clinical Pediatrics, 2023, 41(8): 594-598.
[13]	SUN Zhicai, LIU Yuling, LI Xiaolin, PAN Xiaofen. Clinical analysis of 15 children with primary nephrotic syndrome complicated with adrenal crisis [J]. Journal of Clinical Pediatrics, 2023, 41(8): 610-612.
[14]	WANG Hongxia, PAN Xiang, LU Jun. Report a case of α-ketoadipic aciduria caused by compound heterozygous variant of DHTKD1 gene [J]. Journal of Clinical Pediatrics, 2023, 41(8): 624-628.
[15]	XI Bixin, HU Qun, LIU Aiguo. Research advances of the bronchiolitis obliterans syndrome following allogeneic hematopoietic stem cell transplant in children [J]. Journal of Clinical Pediatrics, 2023, 41(8): 629-633.