Metabolic Syndrome and Insulin Resistance: Global Crisis

Al-Mahmood, AK; Afrin, Syeda Fahmida; Hoque, Nazmul

doi:10.3329/bjmb.v4i1.13779

Cited by 5 publications

(5 citation statements)

References 18 publications

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“…The metabolic syndrome (MetS),as comprised of visceral obesity, dyslipidaemia, hyperglycaemia, and hypertension, has become one of the major challenges in clinical medicine as well as in publichealthworldwide [1][2][3] .MetS is a cluster of interrelated risk factors whichshows higher susceptibilityto cardiovascular disease (CVD) by 2-fold increase of risk and type 2 diabetes mellitusby 5-fold 4 and that tends to come to an effect within 5-10 years spanin an apparently healthy individual 5 -as itis evident that subjectively healthy individuals may have biochemical abnormalities along with presence of MetS 6,7 . The identification ofmodifiable CVD risk factors and predictors of MetS inan otherwise healthy population is necessary in order toidentify individuals who may benefit from early interventions 6 .…”

Section: Introductionmentioning

confidence: 99%

Triglycerides and Glucose Index as Potential Marker of Metabolic Syndrome

Tabassum

Mozaffor

Rahman

et al. 2020

Int. J. Hum. Health Sci.

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Background:Triglycerides and Glucose Index (TyG index), a product from fasting levels of triglycerides and glucose, presented promising results as apotential marker of metabolic syndrome in different ethnicity. However, no such reports are available in our population to date.Objective: To see the effectiveness of ‘Triglycerides and Glucose Index’ to predict metabolic syndromein a Bangladeshi population.Methods: This cross-sectional study was carried out in Department of Biochemistry and Molecular Biology, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh, from March 2016 to February 2017. A total of 200 apparently healthy subjects (127 men and 73 women) were selected for the study, who attended the out-patient-departments of the same institution. Anthropometric measurements were recorded – height, weight, waist circumference (WC) and body mass index (BMI). Overnight fasting blood samples were collected to estimate fasting serum glucose andlipid profile. Then TyG index was calculated and evaluated as a tool in diagnosis of metabolic syndrome in the study subjects.Receiver operating characteristic (ROC) curves were plotted to assess the performance of TyG index in MetS prediction by gender. The power of MetS prediction was quantified by the area under the curve (AUC) with 95% confidence intervals.Results: Sensitivity, specificity, positive predictive value and negative predictive value of TyG index to predict metabolic syndrome were 70.45%, 82.14%, 75.61% and 77.97%in males and 25.00%, 97.32%, 88.00% and 62.29%in females respectively. ROC curve showed optimal cut off value 8.72 and area under the curve 0.72 in male study subjects; in female study subjects, the values were 8.72 and 0.96 respectively (P<0.001).Conclusion:Triglycerides and Glucose Index (TyG index) represents a simple,accessible and effective tool for assessment of metabolic syndrome in Bangladeshi population.International Journal of Human and Health Sciences Vol. 05 No. 01 January’21 Page: 85-89

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Section: Introductionmentioning

confidence: 99%

Triglycerides and Glucose Index as Potential Marker of Metabolic Syndrome

Tabassum

Mozaffor

Rahman

et al. 2020

Int. J. Hum. Health Sci.

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“…The R-square score in this report demonstrates that the LM model is a good fit (84.97%), and the MSE.net value of 0.00529 indicates that the model is both accurate and predictive. cross-sectional and prospective studies of patients older than 65 years have shown that total and LDL cholesterol levels decrease with age 3,4,5,6 . According to Borel et al 7 , there is an association between the waist circumference ratio, total cholesterol, LDL, and triglyceride levels.…”

Section: Methodsmentioning

confidence: 99%

Computational statistical modelling for parameters optimization of LDL-cholesterol levels in patients with type 2 diabetes

Amir W Ahmad,

Mohamad Ghazali,

Shahzad

et al. 2024

Bangladesh J Med Sci

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Introduction LDL is the acronym used to denote low-density lipoproteins. When the level of LDL is high, it leads to the accumulation of cholesterol in the arteries, and as a result, it is commonly known as “bad” cholesterol. Recognizing the significance, a study is conducted on computational and statistical modelling for parameter optimization of LDL-cholesterol levels. In recent years, there has been an increase in the application of precise statistical analysis methodologies. Consequently, scientists are more focused on producing reliable results and are more determined to provide credible findings. Objective This study aims to develop and validate a proposed hybrid method that combines Multilayer Feedforward Neural Network (MLFFNN), and Multiple Linear Model (MLR) and to present the R-syntax applications of the proposed hybrid method with clinical study data. Material and Methods The proposed hybrid model will be built using the generalized mixture model, which is formulated using an MLFFNN framework and Linear Model (LM). The performance of the hybrid model will be assessed utilizing the predicted mean square error neural network (MSE.net) and the predicted mean square error (P.MSE), which will serve as a benchmark for precision and efficacy. Results: The result indicates that hybrid method modelling is superior, with the highest R-squared value and the lowest MSE.net value. The hybrid model technique was found to produce a more precise forecast of the outcome when the data is separated into training and testing datasets. The R-square score in this report demonstrates that the LM model is a good fit (84.97%), and the MSE.net value of 0.00529 indicates that the model is both accurate and predictive. Conclusion: The research concludes that the hybrid model method proposed is preferable. This critical conclusion helps us comprehend the hybrid method’s proportional contribution to this illustration’s result. Bangladesh Journal of Medical Science Vol. 23 No. 02 April’24 Page : 498-506

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“…In addition, we employed 2 wt% Tween 20/H 2 O (comparable to 16 mM) as our solvent because this concentration is higher than the critical micelle concentration (CMC) of Tween 20 (∼0.05 mM). 27,28 It is also the concentration at which the copper complex (1b) can be dispersed in and resulted in a relatively higher substrate conversion (Table S1 †). We also further optimise the conditions with several variations as shown in Table 2.…”

Section: Copper-catalysed Atra In An Aqueous-dispersed Systemmentioning

confidence: 99%