RESUMEN
BACKGROUND: We aimed to explore how probiotics, prebiotics, or synbiotics impact glycemic indices in patients with diabetes mellitus. METHOD: A comprehensive search was conducted on PubMed, Scopus, and Web of Science from inception up to April 2023. The random-effects model was employed for the study analysis. Furthermore, sensitivity and subgroup analyses were conducted to investigate potential sources of heterogeneity. AMSTAR2 checklist was used to determine the quality of studies. Comprehensive meta-analysis version 3 was used for the study analysis. RESULT: A total of 31 studies were included in the final analysis. Based on the results of the meta-analysis, gut microbial therapy could significantly decrease serum fasting blood glucose levels in patients with type 2 diabetes mellitus (effect size: -0.211; 95 % CI: -0.257, -0.164; P < 0.001). Additionally, significant associations were also found between gut microbial therapy and improved serum levels of fasting insulin, glycated hemoglobin, and homeostatic model assessment for insulin resistance (effect size: -0.087; 95 % confidence interval: -0.120, -0.053; P < 0.001; effect size: -0.166; 95 % confidence interval: -0.200, -0.132; P < 0.001; effect size: -0.230; 95 % confidence interval: -0.288, -0.172; P < 0.001, respectively). CONCLUSION: Our results revealed promising effects of gut microbiota modulation on glycemic profile of patients with type 2 diabetes mellitus. The use of these agents as additional treatments can be considered.
RESUMEN
BACKGROUND: Contrast-induced nephropathy (CIN) is a form of acute kidney injury (AKI) occurring in patients undergoing cardiac catheterization, such as coronary angiography (CAG) or percutaneous coronary intervention (PCI). Although the conventional criterion for CIN detection involves a rise in creatinine levels within 72 h after contrast media injection, several limitations exist in this definition. Up to now, various meta-analyses have been undertaken to assess the accuracy of different biomarkers of CIN prediction. However, the existing body of research lacks a cohesive overview. To address this gap, a comprehensive umbrella review was necessary to consolidate and summarize the outcomes of prior meta-analyses. This umbrella study aimed to offer a current, evidence-based understanding of the prognostic value of biomarkers in predicting CIN. METHODS: A systematic search of international databases, including PubMed, Scopus, and Web of Science, from inception to December 12, 2023, was conducted to identify meta-analyses assessing biomarkers for CIN prediction. Our own meta-analysis was performed by extracting data from the included studies. Sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were assessed using Meta-Disc and CMA softwares. RESULTS: Twelve studies were ultimately included in the umbrella review. The results revealed that neutrophil gelatinase-associated lipocalin (NGAL) exhibited the highest area under the curve (AUC), followed by cystatin-C, urinary kidney injury molecule-1 (uKIM-1), and brain natriuretic peptide (BNP) with AUCs of 0.91, 0.89, 0.85, and 0.80, respectively. NGAL also demonstrated the highest positive likelihood ratio [effect size (ES): 6.02, 95% CI 3.86-9.40], followed by cystatin-C, uKIM-1, and BNP [ES: 4.35 (95% CI 2.85-6.65), 3.58 (95% CI 2.75-4.66), and 2.85 (95% CI 2.13-3.82), respectively]. uKIM-1 and cystatin-C had the lowest negative likelihood ratio, followed by NGAL and BNP [ES: 0.25 (95% CI 0.17-0.37), ES: 0.25 (95% CI 0.13-0.50), ES: 0.26 (95% CI 0.17-0.41), and ES: 0.39 (0.28-0.53) respectively]. NGAL emerged as the biomarker with the highest diagnostic odds ratio for CIN, followed by cystatin-C, uKIM-1, BNP, gamma-glutamyl transferase, hypoalbuminemia, contrast media volume to creatinine clearance ratio, preprocedural hyperglycemia, red cell distribution width (RDW), hyperuricemia, neutrophil-to-lymphocyte ratio, C-reactive protein (CRP), high-sensitivity CRP, and low hematocrit (P < 0.05). CONCLUSION: NGAL demonstrated superior diagnostic performance, exhibiting the highest AUC, positive likelihood ratio, and diagnostic odds ratio among biomarkers for CIN, followed by cystatin-C, and uKIM-1. These findings underscore the potential clinical utility of NGAL, cystatin-C and uKIM-1 in predicting and assessing CIN.