Evaluation of Urinary Biomarkers for Prediction of Diabetic Kidney Dis
ease: A Propensity Score Matching Analysis Yongzhang QinFirst Aff
iliated Hospital of Gannan Medical UniversityJul. 8, 2023 Ganzho
uResearch BackgroudMaterials and MethodsResultsConclusionZhang L,
et al. N Engl J Med. 2016 Sep 1;375(9):905-6. Prevalence of dia
betes-related chronic kidney disease (CKD) has exceeded that of g
lomerulonephritis-related chronic kidney disease and became the l
eading cause of CKD in China. Research BackgroudESRDGregg EW et a
l. N Engl J Med 2014;370:1514-23Rates of end-stage renal disease
have decreased less than rates of other complications of diabetes
.The diagnosis of early-stage DKD base on microalbuminuria.DKD re
fers to chronic kidney disease that is specific to diabetes, main
ly including eGFR < 60 ml/min/1.73 m2 and / or albuminuria [urine
albumin to creatinine ratio (ACR) ≥ 30 mg/g, urinary albumin exc
retion rate (UAE) ≥ 30 mg/24 h] present for > 3 months.Am J Kidne
y Dis 2007; 49(2 Suppl 2):S12-154Am J Kidney Dis 2014; 64(4):510-
533Chinese Journal of Diabetes Mellitus 2014; 6(11):792-801Early
progressive renal decline precedes the onset of microalbuminuria
and its progression to macroalbuminuria. Krolewski?AS , et al. Di
abetes Care.?2014;37(1):226-34.Early progressive renal decline Re
nal structural changes may precede proteinuria.Caramori ML, et al
. Diabetes.?2000?Sep;49(9):1399-408.P < 0.005 vs. groups I and I
II: AER <15 μg/min; II: AER 15–30 μg/min; III:31–70 μg/min; IV: 7
1–150μg/min.The shaded area represents the means ± 2 SD in a grou
p of 52 age-matched normal control subjects.Andrzej S. Krolewski
Time to Retire “Microalbuminuria”——Early, Progressive Renal Decli
ne is the New Paradigm 2014 ADA Kelly West Award for Outstanding
Achievement in Diabetes Epidemiology ——Prof. Andrzej S. Krolewsk
iNovel and effective biomarkers?Aim: To evaluate the diagnostic v
alues of six urinary biomarkers for prediction of diabetic kidney
disease. Materials & MethodsStudy populationThe cross-sectional
study recruited 1053 patients with T2DM admitted in Tianjin Medic
al University Chu Hsien-I Memorial?Hospital between Jan. 2018 and
Dec. 2018. All patients were divided into the DM with NA (DM) gr
oup and DKD group based on 24-hour ?urinary ?albumin excretion ra
te (24-h UAE) of < 30mg/24h, ≥ 30mg/24h, respectively and estima
ted glomerular filtration rate (eGFR) [DM group: 24-h UAE < 30 mg
/24 h, eGFR ≥ 60 ml/min/1.73 m2); DKD group: 24-h UAE ≥ 30 mg/24
h, eGFR ≥ 60 ml/min/1.73 m2)]. Inclusion criteria:T2DM diagnosis,
age ≥ 18 years,eGFR ≥ 60 ml/min/1.73m2 according to the KDIGO cl
inical practice guideline in 2012 and the CKD-EPI formula. Exclus
ion criteria:Patients with anemia, neoplasm, severe cardiovascula
r, cerebrovascular, and liver diseases, chronic glomerulonephriti
s, known kidney diseases other than DKD, infection, autoimmune d
iseases, and acute diabetic complications such as ketoacidosis. M
oreover, patients with poorly controlled hypertension, fever, vig
orous physical activity, urinary tract infection, pregnant women,
and those on their menstrual period were excluded to avert non-s
pecific albuminuria. Inclusion & exclusion criteriaResultsImbalan
ce in patient characteristics before and after propensity score m
atchingGrey squares represent imbalance before PSM and red square
s represent imbalance after PSM.variablesdifferentvariables: sex
, age, BMI, smoking, retinopathy, SBP, DBP, DM duration, HbA1c, e
GFR, SUA, TG, TC,HDL, LDL, ACEI/ARB use, and statin use. Patients
with DKD had higher levels of all six urinary biomarkers. All in
dicators demonstrated significantly increased risk of DKD, except
for GAL and β2MG. Note: Adjusted for sex, age, BMI, smoking, r
etinopathy, SBP, DBP, DM duration, HbA1c, eGFR, SUA, TG, TC, HDL,
LDL, ACEI/ARB use, and statin use. Odds ratios for increased ris
ks of DKD in univariate and multivariate logistic regressions.Sin
gle RBP yielded the greatest area under the curve (AUC) value.Not
e: cob1, TF + RBP; cob2, TF + IgG; cob3, IgG + RBP; cob4, TF + Ig
G + RBP; cob5, RBP + GAL + NAG + β2MG; cob6, TF + IgG + RBP + GA
L + NAG + β2MG.Graph ROC curves showing AUCs of different biomark
ers for the diagnosis of DKD.The diagnostic values of the differe
nt combinations were not superior to the single RBP. Note: cob1,
TF + RBP; cob2, TF + IgG; cob3, IgG + RBP; cob4, TF + IgG + RBP; cob5, RBP + GAL + NAG + β2MG; cob6, TF + IgG + RBP + GAL + NAG + β2MG.Conclusions1. RBP, TF, and IgG could be used as reliable or good predictors of DKD. 2. The combined use of these biomarkers did not improve DKD detection. Thanks |
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