Gabi Gazi

Osteoprotegerin (OPG) is a glycoprotein involved in bone metabolism and cardiovascular health, with emerging evidence suggesting its role in heart failure (HF). Despite its potential as a biomarker, the association between circulating OPG levels and HF severity remains unclear. This systematic review and meta-analysis aimed to evaluate OPG levels in HF patients and their relationship with disease severity according to the New York Heart Association (NYHA) classification. A comprehensive search of PubMed, EMBASE, and Scopus was conducted to identify observational studies assessing OPG levels in HF patients. Studies were included if they reported OPG levels in HF patients and controls, with subgroup analyses according to NYHA classification when available. Risk of bias assessment was performed using the Newcastle–Ottawa Scale (NOS). The principal outcome was the mean difference (MD) in circulating OPG levels between HF patients and controls. Random-effects meta-analysis models were used to pool the data. Thirteen studies with a total of 1387 participants were included in the quantitative and qualitative synthesis. Overall, OPG levels were significantly elevated in HF patients compared to healthy controls (2.490 [95% CI 0.531, 4.449]). Subgroup analysis showed a significant decrease in OPG levels in controls versus NYHA II patients (−1.503 [95% CI −2.402, −0.604]). However, no statistically significant difference was found when comparing OPG levels between the combined NYHA II/III group and controls (−1.019 [95% CI −2.451, 0.412]). OPG levels are significantly elevated in HF patients compared to controls, with a progressive increase in NYHA II patients. However, the lack of significance in the NYHA II/III group highlights the need for further studies with a more comprehensive NYHA classification breakdown.

Background: Numerous studies have explored the potential of the biomarker copeptin (CPP) in diagnosing and assessing the severity of chronic kidney disease (CKD). Despite these efforts, findings have been inconsistent. Consequently, this study aimed to examine the association between CPP and CKD, specifically evaluating its diagnostic value and correlation with CKD severity as classified by the Kidney Disease Improving Global Outcomes (KDIGO) guidelines. Methods: A systematic search of PubMed, EMBASE, and Scopus was conducted using a predefined search string to identify relevant studies. Eligible studies included those involving CKD patients classified by glomerular filtration rate (GFR) according to the Kidney Disease Outcomes Quality Initiative (KDOQI) guidelines or by the estimated GFR (eGFR) calculated using the MDRD formula, provided they met predefined inclusion criteria. Study quality was assessed using the Newcastle–Ottawa Scale (NOS). The primary outcome measured was the mean difference (MD) in serum CPP levels across the various stages of CKD. Results: A total of seven studies, comprising 2769 participants, met the inclusion criteria and were incorporated into our systematic review and meta-analysis. Notable differences in CPP levels were identified across various comparisons. Specifically, CPP levels were significantly elevated in CKD patients compared to healthy controls, with a mean difference (MD) of 12.975 (95% CI 6.572, 19.379). Additional significant MDs were observed in comparisons including controls versus CKD stages 1–2/2 (−1.600 [95% CI −3.179, −0.020]), controls versus CKD stage 3 (−9.598 [95% CI −12.959,−6.237]), controls versus CKD stages 4–5 (−28.776 [95% CI −42.925, −14.628]), and CKD stages 1–2 versus stages 4–5 (−30.475 [95% CI −46.790, −14.160]). Conclusions: Comparison between the CKD patients and healthy controls revealed significantly elevated CPP levels, suggesting a possible role in renal pathology. Furthermore, the distinct differences in CPP concentrations across various CKD stages highlight its potential as a biomarker for assessing disease severity and progression.

Background and Objectives: Numerous studies have explored the biomarker atherogenic index of plasma (AIP) in relation to metabolic syndrome (MetS), showing its potential utility in assessing this condition. However, the existing evidence remains inconsistent and inconclusive. Therefore, this study aimed to evaluate the association between AIP and MetS and assess its predictive accuracy. Materials and Methods: A comprehensive search of PubMed, EMBASE, and Scopus was conducted using a predefined search strategy to identify relevant studies. Eligible studies diagnosed MetS based on the International Diabetes Federation criteria. The primary outcomes were the mean difference (MD) in AIP between MetS patients and healthy controls, as well as the area under the curve (AUC) for AIP in predicting MetS. Results: Thirteen studies involving 17,689 participants met the inclusion criteria and were included in the systematic review and meta-analysis. AIP levels were significantly higher in MetS patients compared to healthy controls, with an MD of 0.309 (95% CI 0.214, 0.405). In contrast, the difference in AIP levels between type 2 diabetes mellitus (T2DM) patients with MetS and normoglycemic MetS patients was not statistically significant (MD 0.142, 95% CI −0.091, 0.376). The predictive accuracy of AIP for MetS yielded an AUC of 0.864 (95% CI 0.856, 0.871). Conclusions: AIP levels are significantly elevated in MetS patients compared to healthy individuals, supporting AIP’s potential role as a biomarker for MetS. However, AIP levels did not differ significantly between T2DM patients with MetS and normoglycemic MetS patients. The predictive accuracy of AIP for MetS is acceptable, indicating that AIP may serve as a useful tool in MetS diagnosis. Further research is warranted to clarify its diagnostic and prognostic significance in clinical settings.