Diagnosis of proteinuria using a random urine protein-creatinine ratio and its correlation with adverse outcomes in pregnancy with preeclampsia characterized by renal damage.

Based on a limited number of studies, a random urine protein-creatinine ratio (uPCR) value of ≥ 0.3 indicates abnormal proteinuria in preeclampsia with renal damage. However, current guidelines do not recommend a reasonable diagnostic threshold of uPCR for severe preeclampsia with renal damage. Furthermore, the correlation between the uPCR value and clinical adverse outcomes remains poorly understood. The aim of the present study was to evaluate the value of uPCR in the diagnosis of significant proteinuria and to assess its correlation with adverse pregnancy outcomes in preeclampsia characterized by renal damage. In all, 1837 women were enrolled in this retrospective cohort study. Eventually, 961 women were enrolled under the exclusion criteria. First, the authors found that uPCR and 24-hour proteinuria showed a significant association (r = 0.901). The optimal threshold of uPCR for diagnosing preeclampsia was 0.295, and for diagnosing severe preeclampsia the cut-off was 0.625. Meanwhile, the adjusted odds ratio per 1 unit increase in ln (uPCR) was 1.679 (95% confidence interval [CI]:1.142-2.469) for severe adverse perinatal outcomes; 1.456 (95% CI: 1.242-1.705) for small for gestational age; 1.380 (95% CI: 1.051-1.811) for severe small for gestational age; 1.672 (95% CI: 1.210-2.310) for very early preterm birth; 1.989 (95% CI 1.726-2.293) for severe hypertension; and 2.279 (95% CI 1.906-2.724) for preterm birth. This study indicated that there was a significant and positive correlation between uPCR and 24-hour urine protein. For neonatal and maternal adverse outcomes, uPCR is an independent predictor of prognosis.

The Association Between Cadmium Exposure and Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis.

OBJECTIVE: Several studies have evaluated the association of cadmium exposure with the risk of gestational diabetes mellitus (GDM). However, the findings among these studies have been inconsistent. To further investigate the relationship, we carried out a meta-analysis to clarify the relationship between cadmium exposure and GDM risk. METHODS: Five databases (Scopus, PubMed, Web of Science, Cochrane, and CNKI) were searched for eligible studies until September 09, 2021. The quality of eligible studies was evaluated using the Newcastle-Ottawa quality assessment scale (NOS). The summary odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by random-effects models due to high heterogeneity. Sensitivity analysis was performed to explore the robustness of the results. Publication bias was evaluated by Egger's test and Begg's test. We also conducted meta-regression analysis and subgroup analysis to assess the potential sources of heterogeneity. RESULTS: A total of 10 studies with 32,000 participants related to our issue were included. Comparing the highest vs. lowest categories of cadmium exposure, no significant association was observed between cadmium exposure and the risk of GDM (OR = 1.16, 95% CI = 0.92-1.46, and P = 0.206). No publication bias was found in Begg's and Egger's tests (all P > 0.05). Meta-regression suggested that publication year was the potentially heterogeneous source (P = 0.034). Subgroup analysis of publication year showed that the OR of studies before the year of 2016 was 4.05 (95% CI = 1.87-8.76, P < 0.001), and prospective cohort studies showed a borderline increased GDM risk (OR = 1.15, 95% CI = 0.99-1.33, and P = 0.061). CONCLUSION: Our results indicated no significant association between cadmium exposure and GDM risk. Further high-quality prospective studies, especially those using standard analytic methods for cadmium exposure, are warranted to confirm the results.