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Introduction: Serum uric acid levels have been reported to be associated with a variety of cardiovascular conditions. Metabolic syndrome (MetS) consists of central obesity, hypertriglyceridemia, low HDL cholesterol, hyperglycemia and hypertension. Aim: Serum uric acid and its correlation with triglyceride in metabolic syndrome. Material and methods: 100 patients with MetS were conveniently recruited. For the purpose of analysis study participants were grouped into, group-1(control) and group-2 (case) triacylglycerol was defined with cut-off ≥150mg/dl in both men and women. Uric acid in Males: 3.5-7.2 mg/dl, Females: 2.6-6.0 mg/dl. Metabolic syndrome was defined by the National Cholesterol Education Program Adult Treatment Panel III Criteria with adjusted waist circumference cutoffs (90 cm for males; 80 cm for females). The association between serum uric acid quartiles and metabolic syndrome was assessed using multivariate logistic regression. Result: Shows mean uric acid in cases 6.20±1.56 and in controls 4.6840±.6264119, highly significant (p .000). Shows triglyceride in cases 197.86±122.500 and in controls 127.22±28.524, highly significant (p.ooo). Conclusion: When compared among males and females, there was increased percentage of elevated serum uric acid in females. Metabolic syndrome is a group of risk factors that include abdominal fat, high uric acid and unhealthy cholesterol levels. [ABSTRACT FROM AUTHOR]

Introduction: Metabolic syndrome is a cluster of metabolic abnormalities characterized by abdominal obesity, hyperglycemia, decreased high density lipoprotein (HDL), increased Triglycerides and high blood pressure, which predispose the individual at higher risk for both cardiovascular disease (CVD) and type 2 diabetes. Postmenopausal state is considered as a vulnerable period for developing MS. Aims and Objectives: To study the Prevalence of metabolic syndrome and its components in postmenopausal women. Material and Method: This study was conducted in the Department of biochemistry, MMIMSR, MMDU, Mullana, Ambala. A total of 100 postmenopausal women in the age group of above 45 years were recruited for this study after assessing their eligibility according to the selection criteria. Biochemical Investigations: Estimation of Fasting Serum glucose was done on Erba chem 7 analyzer and Total cholesterol, HDL and Serum Triglycerides was done on Dimension® clinical chemistry system manufactured by Siemens Healthcare Diagnostics (US). Results: The mean triglycerides and fasting serum glucose levels were significantly high (<0.001) among postmenopausal women with metabolic syndrome. Overall prevalence of metabolic syndrome was 29%. Conclusions: Evaluating the biochemical parameters in postmenopausal women is useful for assessing the risk of developing metabolic syndrome in them. Monitoring the health status of these females can help to reduce the Prevalence of metabolic syndrome and thus the risk of developing cardiovascular disease. [ABSTRACT FROM AUTHOR]

Objectives: Metabolic syndrome (MetS) is a cluster of several metabolic disorders including hyperglycemia, reduced high density lipoprotein cholesterol, raised triglyceride level in serum, hypertension and abdominal obesity. Methods: The present study was conducted at the MM Institute of Medical Sciences and Research. The study includes 300 patients with MetS as a case and 300 healthy volunteers as a control. MetS was diagnosed according to international diabetes federation. Results: In our study 103 MetS patients of 300 have shown the complications like DM (Diabetes Mellitus), HTN (Hypertension) and obesity which are predisposing factors for atherosclerosis and other cardiovascular diseases which lead to morbidity and mortality. Conclusions: Our study found that diabetes Mellitus, hypertension, dyslipidemia and obesity are the predisposing factors for metabolic syndrome. [ABSTRACT FROM AUTHOR]

Background: Unreliable and ingenuine results issued by clinical laboratories have serious consequences for the patients. Sigma metrics is a standardized tool for Quality assessment for test performance in a laboratory., Objective: To evaluate the performance of routine biochemistry laboratory at MMIMSR, Mullana in terms of Sigma metrics and Quality Goal Index., Material and Methods: This cross sectional study evaluated performance of 14 routine chemistry parameters using retrospective Internal Quality Control data of two levels on Siemens Dimension Rxl from Feb to Jul 2019 for CV% and EQAS reports from CMC, Vellore for Bias%. Sigma metrics was calculated using total allowable error targets as per CLIA and Biological Variability database guidelines., Results: For level-2 IQC; TG, Chol, ALP showed excellent performance with σ ​> ​6 while σ ​< ​3 was observed for AST, Total Protein, Glucose, BUN and ALT using CLIA guidelines while in IQC Level-3 poor performers were only BUN and ALT with Ca, TG and Chol showing σ ​> ​6. Further by using Biological Variability data guidelines; 10 parameters of IQC Level-2 and 5 of IQC level-3 were poor performers with σ ​< ​3., Conclusion: Sigma metrics is an excellent tool for performance analysis of tests performed in a clinical laboratory. Lack of precision in terms of CV% was seen for majority of the poor performers. Total allowable error targets using Biological Variability data revealed σ ​< ​3 for 10 parameters while using CLIA guidelines σ ​< ​3 was seen for only 5 parameters of IQC level-2., (© 2020 Published by Elsevier B.V.)