Author links open overlay panel, , , , , , , , , , , , , , Highlights•Renal surface irregularity assessed by ultrasonography is useful.
•Urinary type IV collagen excretion is useful in predicting eGFR decline.
•Serum soluble thrombomodulin levels are useful in predicting eGFR decline.
•Deceleration of renal function decline was calculated in each case.
•Rapid renal function decliners have more possibility to slow the decline.
AbstractAimsThis study aimed to identify noninvasive biomarkers for predicting the effectiveness of multifactorial management in individual cases of diabetic kidney disease (DKD).
MethodsThis multicenter, retrospective–prospective observational study included patients with type 2 diabetes and DKD. Candidate biomarkers were evaluated within 1 year of enrollment. Deceleration in the rate of decline in the estimated glomerular filtration rate (eGFR) was defined as an indicator of prognostic improvement in DKD. The correlation between candidate biomarkers and baseline eGFR, as well as with eGFR decline, was analyzed. Furthermore, candidate biomarkers were compared between the groups with and without a deceleration in eGFR decline.
ResultsSerum soluble thrombomodulin (sTM) levels, urinary liver-type fatty acid-binding protein excretion, kidney size, and renal surface irregularities were found to be independently associated with baseline eGFR. Serum sTM levels and urinary type IV collagen excretion were independently associated with eGFR decline. Furthermore, the eGFR decline rate during the first 2 years of the observation period was independently associated with the later deceleration of eGFR decline. Additionally, the probability of deceleration in eGFR decline was higher among patients who experienced a more rapid eGFR decline early in the observation period. However, a biomarker that could predict the likelihood of deceleration in eGFR decline could not be identified.
ConclusionsWe identified four noninvasive biomarkers that independently correlated with the eGFR, among which urinary type IV collagen excretion and serum sTM levels were particularly useful in predicting eGFR decline.
KeywordsDiabetic kidney disease
Estimated glomerular filtration rate
Urinary type IV collagen excretion
Renal ultrasonography
Thrombomodulin
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