Prediabetes and structural brain abnormalities: Evidence from observational studies.

Type 2 diabetes mellitus has been linked to structural brain abnormalities, but evidence of the association among prediabetes and structural brain abnormalities has not been systematically evaluated. Comprehensive searching strategies and relevant studies were systematically retrieved from PubMed, Embase, Medline and web of science. Twelve articles were included overall. Stratified analyses and regression analyses were performed. A total of 104 468 individuals were included. The risk of infarct was associated with continuous glycosylated haemoglobin (HbA1c ) [adjusted odds ratio (OR) 1.19 (95% confidence interval [CI]: 1.05-1.34)], or prediabetes [adjusted OR 1.13 (95% CI: 1.00-1.27)]. The corresponding ORs associated with white matter hyperintensities were 1.08 (95%CI: 1.04-1.13) for prediabetes, and 1.10 (95%CI: 1.08-1.12) for HbA1c . The association was significant between the decreased risk of brain volume with continuous HbA1c (the combined OR 0.92, 95% CI: 0.87-0.98). Grey matter volume and white matter volume were inversely associated with prediabetes [weighted mean deviation (WMD), -9.65 (95%CI: -15.25 to -4.04) vs WMD, -9.25 (95%CI: -15.03 to -3.47)]. There were no significant association among cerebral microbleeds, hippocampal volume, continuous total brain volume, and prediabetes. Our findings demonstrated that (a) both prediabetes and continuous HbA1c were significantly associated with increasing risk of infarct or white matter hyperintensities; (b) continuous HbA1c was associated with a decreased risk of brain volume; (c) prediabetes was inversely associated with grey matter volume and white matter volume. To confirm these findings, further studies on early diabetes onset and structural brain abnormalities are needed.

Urine NGAL as an early biomarker for diabetic kidney disease: accumulated evidence from observational studies.

Objectives: Urine neutrophil gelatinase-associated lipocalin (NGAL) was found to increase in diabetic kidney disease (DKD). However, the clinical value of urine NGAL as diagnostic indicators in DKD remains to be clarified. Methods: Relevant studies were systematically retrieved from PubMed, Embase, Web of Science, and the Cochrane Library. Stratified analyses and regression analyses were performed. Results: Fourteen studies with 1561 individuals were included in our analysis, including 1204 cross-sectional participants and 357 cohort participants. For the cross-sectional studies, the pooled sensitivity and specificity of NGAL in the diagnosis of DKD were 0.82 (95% confidence interval (CI): 0.75-0.87) and 0.81 (95% CI: 0.68-0.90), respectively. The pooled diagnostic odds ratio was 19 (95% CI: 11-33), and the overall area under the curve was 0.88 (95% CI: 0.84-0.90). For the cohort studies, the pooled sensitivity and specificity of NGAL in the diagnosis of DKD were 0.96 (95% CI: 0.91-0.98) and 0.89 (95% CI: 0.84-0.92), respectively. The overall area under the curve was 0.98, indicating good discriminative ability of NGAL as biomarkers for DKD. Conclusions: Urine NGAL, as the early diagnostic marker of DKD, might have the high diagnostic value, especially in cohort studies.