A case control study of clinical and biochemical parameters of metabolic syndrome with special attention among young and middle aged population

2019 ◽  
Vol 13 (4) ◽  
pp. 2653-2659 ◽  
Author(s):  
Vivek V. Bhosale ◽  
Shail Singh ◽  
Mukesh Srivastava ◽  
Priyanka Pathak ◽  
Shakti Prakash ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Biochemical Parameters ◽  
Case Control Study ◽  
Case Control ◽  
Middle Aged ◽  
Aged Population ◽  
Control Study

scholarly journals CD4/CD8 ratio as a predictor for the occurrence of metabolic syndrome in HIV / AIDS patients during 6 months of cART therapy

2019 ◽  
Vol 38 (4) ◽  
pp. 489-495 ◽  
Author(s):  
Refet Gojak ◽  
Vesna Hadžiosmanović ◽  
Rusmir Baljić ◽  
Lamija Zečević ◽  
Jozo Ćorić ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Biochemical Parameters ◽  
Case Control Study ◽  
Case Control ◽  
Hiv Positive ◽  
Retrospective Case ◽  
Aids Patients ◽  
Immunological Parameters ◽  
Control Study ◽  
Hiv Aids

Summary Background HIV infection is characterized by progressive depletion of CD4+ T cells due to their reduced synthesis and increased destruction followed by marked activation and expansion of CD8+ T lymphocytes. CD4/CD8 ratio was traditionally described as a marker of immune system ageing in the general population, but it increasingly appears as a marker of different outcomes in the HIV-infected population. The main objective of this study is to examine the power of CD4/CD8 ratio in predicting the occurrence of metabolic syndrome (MetS) in HIV-positive patients receiving cART therapy. Methods 80 HIV/AIDS subjects were included in a retrospective case-control study. Flow cytometry was used to determine the percentage of CD4+ and CD8+ cells in peripheral blood of these patients. The values of biochemical parameters (triglycerides, HDL, blood sugar, blood counts), immunological parameters (CD4/CD8, PCR), anthropometric measurements and type of cART therapy were evaluated in this study. Results After six months of cART therapy 19 (23.8%) subjects had all the elements necessary for making the diagnosis of MetS. Using multivariate analysis CD4/CD8 ratio was statistically significant (p < 0.05) and had the largest effect on development of MetS (Wald = 9.01; OR = 0.45), followed by cART (Wald = 7.87; OR = 0.10) and triglycerides (Wald = 5.27; OR = 1.7). On the other hand, body weight and waist circumference showed no statistically significant effect on the development of MetS after six months of cART, p > 0.05. Conclusions CD4/CD8 ratio proved to be a significant marker for prediction of metabolic syndrome in HIV/AIDS patients.

scholarly journals Association of cystatin C levels with metabolic syndrome incidence: a nested case-control study with propensity score matching

2021 ◽  
Vol 49 (1) ◽  
pp. 030006052098631
Author(s):  
Tengfei Yang ◽  
Dongmei Pei
Keyword(s):  
Metabolic Syndrome ◽  
Propensity Score ◽  
Physical Examination ◽  
Propensity Score Matching ◽  
Case Control Study ◽  
Case Control ◽  
Chinese Adults ◽  
Biochemical Profiles ◽  
Nested Case Control ◽  
Control Study

Objective Metabolic syndrome (MetS) involves multiple metabolic disorders and seriously affects human health. Identification of key biological factors associated with MetS incidence is therefore important. We explored the association between MetS and the biochemical profiles of Chinese adults in Shenyang City in a nested case-control study. Methods We included adult participants who underwent physical examination at our hospital for 2 consecutive years. Participants’ biochemical profiles and other MetS components were tested and monitored continuously. Propensity score matching was used to adjust confounding factors between participants with and without MetS. We analyzed the association between incidence of MetS and the biochemical profiles of participants. Results Of 5702 participants who underwent physical examination between 1 January 2017 and 1 December 2018, 538 had confirmed newly developed MetS. After successfully matching 436 pairs of participants, mean cystatin C (Cys-C) level was significantly higher in the MetS group than in the non-MetS group. Logistic regression analysis indicated that age (years) and γ-glutamate transpeptidase, creatinine, uric acid, and Cys-C levels were significantly associated with MetS incidence; among these, the odds ratio of Cys-C was highest (3.03; 95% confidence interval, 1.02–9.00). Conclusions Cys-C levels were significantly associated with the incidence of MetS among Chinese adults.

scholarly journals Inflammatory Biomarkers Predictive of Metabolic Syndrome in a Nigerian Population: A Case-Control Study

2020 ◽  
Vol 6 (4) ◽  
pp. 382-390
Author(s):  
EN Adejumo ◽  
OA Adejumo ◽  
OA Ogundahunsi
Keyword(s):  
Metabolic Syndrome ◽  
Case Control Study ◽  
Inflammatory Marker ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Case Control ◽  
Control Group ◽  
Necrosis Factor Alpha ◽  
Hs Crp ◽  
Control Study

Background: Inflammation is linked to the aetiopathogenesis of Metabolic syndrome (MetS). Objective: To assess the ability of high sensitivity C-Reactive Protein (hs-CRP), Tumour Necrosis Factor-alpha (TNFα) and Interleukin-6 (IL-6) to predict MetS. Methods: A case-control study involving 123 subjects with MetS (cases) and age-matched 123 subjects. without MetS (controls) was conducted. The levels of TNFα, IL-6, and hs-CRP between independent groups were compared. The Receiver Operative Characteristic Curve was used to assess the ability of inflammatory markers to discriminately identify MetS. Results: The mean age of the case and control groups was 49.9±0.9 years and 48.1±1.1 years (p = 0.274) respectively. The median levels of TNFα, IL-6 and hS-CRP were significantly higher among the cases than the control group in both genders (p <0.001). There was a significant increase in the serum values of the markers with increasing components of MetS (p <0.001). The Area Under the Curve of TNFα, IL-6 and hs-CRP was > 0.9 in both males and females. Conclusion: TNFα, IL-6, and hs-CRP identified MetS. There is a need for further studies to determine the inflammatory marker most predictive of MetS.

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