PMID- 33171707
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20201201
IS  - 2075-4418 (Print)
IS  - 2075-4418 (Electronic)
IS  - 2075-4418 (Linking)
VI  - 10
IP  - 11
DP  - 2020 Nov 7
TI  - Diagnostic Performance of Biomarkers Urinary KIM-1 and YKL-40 for Early Diabetic 
      Nephropathy, in Patients with Type 2 Diabetes: A Systematic Review and 
      Meta-Analysis.
LID - 10.3390/diagnostics10110909 [doi]
LID - 909
AB  - There is a lack of prediction markers for early diabetic nephropathy (DN) in 
      patients with type 2 diabetes mellitus (T2DM). The aim of this systematic review 
      and meta-analysis was to evaluate the performance of two promising biomarkers, 
      urinary kidney injury molecule 1 (uKIM-1) and Chitinase-3-like protein 1 (YKL-40) 
      in the diagnosis of early diabetic nephropathy in type 2 diabetic patients. A 
      comprehensive search was performed on PubMed by two reviewers until May 2020. For 
      each study, a 2 x 2 contingency table was formulated. Sensitivity, specificity, 
      and other estimates of accuracy were calculated using the bivariate random 
      effects model. The hierarchical summary receiver operating characteristic curve 
      hsROC) was used to pool data and evaluate the area under curve (AUC). The sources 
      of heterogeneity were explored by sensitivity analysis. Publication bias was 
      assessed using Deek's test. The meta-analysis enrolled 14 studies involving 598 
      healthy individuals, 765 T2DM patients with normoalbuminuria, 549 T2DM patients 
      with microalbuminuria, and 551 T2DM patients with macroalbuminuria, in total for 
      both biomarkers. The AUC of uKIM-1 and YKL-40 for T2DM patients with 
      normoalbuminuria, was 0.85 (95%CI; 0.82-0.88) and 0.91 (95%CI; 0.88-0.93), 
      respectively. The results of this meta-analysis suggest that both uKIM-1 and 
      YKL-40 can be considered as valuable biomarkers for the early detection of DN in 
      T2DM patients with the latter showing slightly better performance than the 
      former.
FAU - Kapoula, Georgia V
AU  - Kapoula GV
AD  - Department of Biochemistry, General Hospital of Lamia, End of Papasiopoulou, 
      35100 Lamia, Greece.
AD  - Department of Computer Science and Biomedical Informatics, School of Science, 
      University of Thessaly, Papasiopoulou 2-4, 35100 Lamia, Greece.
FAU - Kontou, Panagiota I
AU  - Kontou PI
AD  - Department of Computer Science and Biomedical Informatics, School of Science, 
      University of Thessaly, Papasiopoulou 2-4, 35100 Lamia, Greece.
AD  - Department of Mathematics and Engineering Sciences, Informatics LAB, Hellenic 
      Military Academy, 16673 Athens, Greece.
FAU - Bagos, Pantelis G
AU  - Bagos PG
AUID- ORCID: 0000-0003-4935-2325
AD  - Department of Computer Science and Biomedical Informatics, School of Science, 
      University of Thessaly, Papasiopoulou 2-4, 35100 Lamia, Greece.
LA  - eng
PT  - Journal Article
DEP - 20201107
PL  - Switzerland
TA  - Diagnostics (Basel)
JT  - Diagnostics (Basel, Switzerland)
JID - 101658402
PMC - PMC7695026
OTO - NOTNLM
OT  - chitinase-3-like protein 1 (YKL-40)
OT  - diabetic nephropathy
OT  - kidney injury molecule 1 (KIM-1)
OT  - meta-analysis
COIS- The authors declare no conflict of interest.
EDAT- 2020/11/12 06:00
MHDA- 2020/11/12 06:01
PMCR- 2020/11/07
CRDT- 2020/11/11 01:01
PHST- 2020/10/08 00:00 [received]
PHST- 2020/11/03 00:00 [revised]
PHST- 2020/11/05 00:00 [accepted]
PHST- 2020/11/11 01:01 [entrez]
PHST- 2020/11/12 06:00 [pubmed]
PHST- 2020/11/12 06:01 [medline]
PHST- 2020/11/07 00:00 [pmc-release]
AID - diagnostics10110909 [pii]
AID - diagnostics-10-00909 [pii]
AID - 10.3390/diagnostics10110909 [doi]
PST - epublish
SO  - Diagnostics (Basel). 2020 Nov 7;10(11):909. doi: 10.3390/diagnostics10110909.