Correlation between new insulin resistance and physiological indicators in prediabetic patients
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Keywords

Prediabetes
new insulin resistance index
correlation physiological indicators with blood glucose Tiền đái tháo đường
chỉ số kháng insulin mới
tương quan sinh lý chỉ số đường huyết

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How to Cite

Nguyễn, V. V. H., Nguyễn, T. H. N., Nguyễn, T. H., Nguyễn, V. B., Nguyễn, T. T. L., & Nguyễn, H. T. (2024). Correlation between new insulin resistance and physiological indicators in prediabetic patients. Vietnam Journal of Diabetes and Endocrinology, (63), 143-154. https://doi.org/10.47122/VJDE.2023.63.17

Abstract

Background: Prediabetes has been on the rise in recent years. During this time, cardiovascular complications were recorded, and more than half of the patients who were diagnosed with diabetes had cardiovascular complications. Therefore, it is very important to screen for risk factors early. Contributes to preventing progression to diabetes as well as complications. Aim: the correlation between these physiological indicators and new insulin resistance in prediabetic patients. Methodology: Applying crosssectional description study, 86 pre-diabetic patients detected by fasting blood glucose and/or HbA1c were within the pre-diabetes threshold according to the ADA 2020 criteria. Data were collected from January 2020 to February 2021 in Center for EndocrinologyDiabetes- Da Nang Family General Hospital. Subjects will be clinically examined and performed laboratory tests according to the research protocol. From there, assess the correlation between demographicphysiological indicators and blood glucose in prediabetic patients. Result: Average blood insulin concentration: 17.07±19.44. The insulin resistance via the HOMA-IR index was 62.79% and insulin sensitivity via the ISI index (McAuley) was 53.49%. The decline in pancreatic islet β-cell function accounted for 66.28%, of which males accounted for 31.40% and females 34.88% (p>0.05). The decline in pancreatic islet β-cell function accounted for 66.28%, of which males accounted for 31.40% and females 34.88% (p>0.05). - There is an inverse correlation between fasting glucose with BMI (r=-0,304, p< 0,05) and Fasting glucose with waist circumference (r=-0,222, p<0,05). There is an inverse correlation between fasting glucose with HOMA-%β (r=-0,359, p><0,001). There is a positive correlation between insulin resistance state: HOMA-IR with HOMA-%β (r=0,809, p><0,0001), TyG- BMI (r=0,222, p><0,05). - Similar to this, there is a positive correlation between new insulin resistance indicators such as TyG-BMI, and TyG-WC with HOMA1-%β (r=0,329, p><0,05), (r=0,234, p><0,05), respectively. - TyG-BMI and TyG-WC were better than TyG in predicting insulin resistance risk with ROC AUC and cutoff point respectively, ROC AUC TyG-BMI: 76.62%, Cut off: 220.06, p>< 0.0001; ROC AUCTyG-WC: 74.42%, Cut off: 766.64, p< 0.05 and ROC AUCTyG: 63.80%, Cut off: 8.84, p< 0.05. Conclusion: Physiological indicators such as waist circumference, BMI, hypertension, smoking, sedentary lifestyle, and hypertriglyceridemia, we also noted a decline in β cell function of the pancreas and decreased insulin sensitivity in prediabetic patients.

https://doi.org/10.47122/VJDE.2023.63.17
pdf (Tiếng Việt)