The predictability of triglyceride glucose index (TyG index) as a biomarker for identification of insulin resistance (IR) is being extensively studied in various ethnic populations. TyG index could be a beneficial tool for identification of IR and populations at high risk for developing diabetes in future. However, more studies are required to standardize optimal cut-off values in different ethnicities and populations. The present review describes existing literature, and identifies merits and demerits of TyG index as a surrogate marker for IR. Keywords: Triglyceride Glucose Index, Insulin resistance, Type 2 Diabetes Mellitus.

ObjectivesTo compare different anthropometric indices, Body composition analysis and lipid profile markers in terms of their ability to predict prediabetes (PD).MethodsWe enrolled 83 subjects with PD and 84 normoglycemic subjects who were matched for age and gender. The diagnosis of prediabetes was done according to the American Diabetes Association (ADA) criteria. All subjects were aged between 30–55 years of age and visited the outpatient department of tertiary care hospital. Anthropometric and lipid profile measurements were obtained. Analysis of body composition was done using Bodystat 1500MDD Instrument. Backward logistic regression was performed for detecting the predictors of PD. A receiver operator characteristic curve (ROC) with area under curve (AUC) was utilized for the accuracy of the predictors of PD.ResultsComparison of anthropometric measurement and body composition analysis parameters between the two groups showed that Waist circumference (WC), Body mass index, Body Fat% were significantly higher whereas Extracellular water and Dry lean weight in percentage (ECW% and DLW%) were found to be lower in PD (p< 0.05). Higher triglyceride (TG) levels and lower high-density cholesterol (HDL-C) with high TG/HDL-C were seen in subjects with PD. Backward logistic regression analysis found the combination of Body Fat % with WC, TG, ECW% and DLW% as strong predictors of PD. In ROC analysis, ECW% (AUC = 0.703) was the most predictive measure, followed by WC (AUC = 0.702).ConclusionThis study demonstrated that estimation of Body Fat % combined with waist circumference, Extracellular water and Dry lean weight in percentage are valuable in screening and diagnosis of prediabetes. Plasma levels of TG in lipid profile measurements can also serve as an additional marker for prediction of prediabetes.

No abstract

No abstract

No abstract

No abstract

BACKGROUND: Dysmenorrhea is the most common gynecologic disorder among female adolescents, with a prevalence of 60% to 93%. Primary dysmenorrhea, painful menstruation without pelvic abnormalities, may be associated with vomiting, fatigue, back pain, headaches, dizziness, and diarrhoea. MATERIALS AND METHODS: This is a comparative and cross sectional Study. Thirty one dysmenorrheic women and non dysmenorrheic women between the age group of 18-26 years participated in this study. All participants satisfied inclusion and exclusion criteria and gave informed consent. We performed Cold Pressor Test on 1st, 14th and 21st day of menstrual cycle denoting the menstrual phase, late follicular phase and luteal phase on the participants. Radial pulse rate was recorded before and after the Cold Pressor test, expressed in beats per minute. Blood pressure was recorded in sitting position just before and after immersion using sphygmomanometer, expressed as mmHg. RESULTS: The SBP difference was highest in the dysmenorrheic women (10.52±2.68) when compared to non dymenorrheic women (8.52±1.93) on the 1st day which was statistically significant. The SBP change was lowest on the 14th day in the dysmenorrheic women (6.52±2.42) when compared to non dymenorrheic women (3.74±1.00) which is statistically significant. The DBP difference was highest in the dysmenorrheic women (4.90±1.54) when compared to non dymenorrheic women (4.06±0.63) on the 1st day which was moderately significant. The DBP change was lowest on the 14th day in the dysmenorrheic women (4.06±1.50) when compared to non dymenorrheic women (2.26±0.68) which is statistically significant. In dysmenorrheic women, there was difference in pulse rate when comparing the 3 episodes that is 1st, 14th day & 21st day. In non dysmenorrheic women, there was difference in pulse rate when comparing the 3 episodes that is 1st, 14th day & 21st day. CONCLUSIONS: We concluded that dysmenorrheic women had increased cardiovascular response to experimental pain across menstrual cycle when compared to non dysmenorrheic women which could be attributed to activation of Sympatho -adrenal medullary system.

No abstract