Cross-sectional comparison of the association between three different insulin resistance surrogates and frailty: NHANES 1999-2018.

Background: The correlation between various insulin resistance surrogates and frailty remains under investigation in the scientific community. Methods: Data from NHANES (1999-2018) were used. We utilized weighted binary logistic regression, trend tests, RCS analysis, and subgroup analysis to comprehensively assess the link between METS-IR, HOMA-IR, and TyG, and frailty risk. Results: The results revealed a significant positive association between high levels of METS-IR, HOMA-IR, and TyG with the risk of frailty in all models. Notably, in model 4, the highest quintile of METS-IR showed the strongest link (OR: 2.960, 95% CI: 2.219-3.949), with HOMA-IR (OR: 2.522, 95% CI: 1.927-3.301) following closely behind. Trend tests revealed a positive trend between METS-IR, HOMA-IR, and TyG with the risk of frailty (P for trend < 0.05). RCS analysis showed a linear relationship between METS-IR and the risk of frailty (P for nonlinearity > 0.05). In contrast, HOMA-IR and TyG exhibited a U-shaped nonlinear relationship (P for nonlinearity < 0.05). Conclusion: The research identified a linear association between METS-IR and frailty risk, whereas HOMA-IR and TyG displayed a U-shaped, nonlinear relationship pattern with the risk of frailty. Among the varying levels examined, the linkage between METS-IR and frailty was most pronounced in the top quintile.

A comparative study of the relationship between time in range assessed by self-monitoring of blood glucose and continuous glucose monitoring with microalbuminuria outcome, HOMA-IR and HOMA-ß test.

AIMS: To compare the time in range (TIR) obtained from self-monitoring of blood glucose (SMBG) with that obtained from continuous glucose monitoring (CGM), and explore the relationship of TIR with microalbuminuria outcome, HOMA-IR and HOMA-ß test. METHODS: We recruited 400 patients with type 2 diabetes to carry out blood glucose monitoring by both SMBG and CGM for 3 consecutive days. TIR, TAR, TBR and other blood glucose variation indices were calculated respectively through the glucose data achieved from SMBG and CGM. The HOMA-IR and HOMA-ß test was evaluated by an oral glucose tolerance test. Urinary microalbumin-to-creatinine ratio completed in the laboratory. RESULTS: The median (25 %, 75 % quartile) of TIRCGM and TIRSMBG were 74.94(44.90, 88.04) and 70.83(46.88, 87.50) respectively, and there was no significant difference, p = 0.489; For every 1 % increase in TIRCGM, the risk of microalbuminuria decreased by 1.6 % (95%CI:0.973, 0.995, p = 0.006) and for every 1 % increase in TIRSMBG, the risk of microalbuminuria decreased by 1.3 % (95%CI:0.975, 0.999, p = 0.033). Stepwise multiple linear regression analysis showed an independent positive correlation between TIR (including TIRCGM and TIRSBMG) and LnDI30 and LnDI120 levels (p = 0.000). CONCLUSIONS: The TIR calculated by SMBG was highly consistent with that reported by CGM and was significantly associated with the risk of microalbuminuria and the HOMA-ß. Higher TIR quartiles were associated with lower incidence of microalbuminuria as well as higher lever of HOMA-ß. For patients with limited CGM application, SMBG-derived TIR may be an alternative to CGM-derived TIR, to assess blood glucose control.

Extraction, Characterization, and Nutraceutical Potential of Prosthechea karwinskii Orchid for Insulin Resistance and Oxidative Stress in Wistar Rats.

Prosthechea karwinskii is an endemic orchid of Mexico with cultural significance for its ornamental, food, religious, and medicinal uses. In traditional medicine, diabetic patients use the leaves of this plant to lower glucose levels. The present study evaluated the effect of P. karwinskii leaves extract on the antioxidant enzymes superoxide dismutase (SOD) and catalase (CAT) in a model of obese rats with insulin resistance for its nutraceutical potential to reduce insulin resistance and oxidative stress. Obesity and insulin resistance were induced with 40% sucrose in water for 20 weeks. Four groups (control rats, obese rats, obese rats administered the extract, and obese rats administered metformin) were evaluated. Extract compounds were identified by UHPLC-ESI-qTOF-MS/MS. Glucose, insulin, triglyceride, and insulin resistance indices (HOMA-IR and TyG), as well as the activity of the antioxidant enzymes, increased in rats in the obese group. Administration of P. karwinskii extract and metformin reduced glucose, insulin, triglyceride, and insulin resistance indices and antioxidant enzyme activity to values similar to those of the control group. Therefore, this study shows the nutraceutical potential of P. karwinskii extract as an ingredient in the formulation of dietary supplements or functional foods to help treat diseases whose pathophysiology is related to oxidative stress and insulin resistance.

Effect of dietary myo-inositol supplementation on the insulin resistance and the prevention of gestational diabetes mellitus: an open-label, randomized controlled trial.

PURPOSE: Myo-inositol (MI) is an insulin-sensitizing dietary supplement, enhancing the transfer of glucose into the cell. Gestational diabetes mellitus (GDM) is characterized by abnormal glucose tolerance, which is associated with elevated insulin resistance. The present study aimed to assess the effect of MI supplementation during pregnancy on the incidence of GDM. METHODS: We performed a single-center, open-label, randomized controlled trial. A cohort of 200 pregnant women at 11-13+6 weeks of gestation were randomly assigned in two groups: MI group (n = 100) and control group (n = 100). The MI group received MI and folic acid (4000 mg MI and 400 mcg folic acid daily), while the control group received folic acid alone (400 mcg folic acid daily) until 26-28 weeks of gestation, when the 75 g Oral Glucose Tolerance Test (OGTT) was performed for the diagnosis of GDM. Clinical and metabolic outcomes were assessed. RESULTS: The incidence of GDM was significantly higher in the MI group (14.9%) compared to the control group (28.5%) (P = 0.024). Women treated with MI had significantly lower OGTT glucose values, than those not treated with MI (P < 0.001). The insulin resistance as assessed by HOMA-IR was significantly lower in the MI group versus control (P = 0.045). Furthermore, MI group had significantly higher insulin sensitivity as measured by the Matsuda Index, compared to the control group (P = 0.037). CONCLUSION: MI supplementation seems to be an effective option to improve the glycemic control of pregnant women and prevent the onset of GDM. TRIAL REGISTRATION: ISRCTN registry: ISRCTN16142533. Registered 09 March 2017.

Value of the triglyceride-glucose index and related parameters in heart failure patients.

The triglyceride-glucose (TyG) index, proven to be a crucial insulin resistance biomarker (better than the Homeostasis Model Assessment for Insulin Resistance), is simple and non-invasive. Recently, indisputable evidence has shown that the TyG index is strongly associated with cardiovascular disease [CVD, including atherosclerosis, heart failure (HF), and hypertension] prognosis and mortality. Nevertheless, the value of the TyG index in HF patients treated with sodium-glucose cotransporter 2 inhibitors (SGLT2is) has not been systematically evaluated. Therefore, in this review, we summarized the value of the TyG index and its related parameters as markers of CVD, especially HF. Furthermore, we addressed the use of SGLT2is and GLP-1 receptor antagonists in HF patients. Finally, we summarized the mechanism of the "obesity paradox."

New Onset Diabetes After COVID 19 (NODAC) is predominantly due to exacerbated Insulin Resistance (IR) rather than beta cell dysfunction: Lessons from tertiary care hospital data during confluence of two epidemics.

PURPOSE: To investigate determinants of new onset diabetes after COVID-19 (NODAC) and its recovery at 6 months. METHODS: This was an observational follow up study conducted from August, 2020 to July, 2023, recruiting patients with preexisting DM and COVID 19 patients with no history of DM. Multivariate regression analysis was used to determine the factors responsible for severity of COVID 19 infection in preexisting DM group. Clinical, laboratory and glycometabolic parameters were estimated at baseline and 6 months in NODAC and euglycemic group to determine the factors responsible for NODAC and its persistence at 6 months. RESULTS: Of 1310 patients, 855 (65.3%) COVID 19 patients were further divided based on their glycemic status: preexisting DM (19%), NODAC (8.5%) and euglycemia (72.5%). Older age and male gender were independent risk factors for severe COVID 19 disease in patients with preexisting diabetes. Prevalence of NODAC in present study was 8.5%. Patients with NODAC had higher mean fasting blood glucose (FBG), random blood glucose (RBG) and HbA1c at baseline as compared to COVID with euglycemic group with no difference in serum C-peptide levels. Female gender, family history of DM, signs of insulin resistance, higher BMI, WHR, HbA1c, serum insulin levels, FBG and RBG predicted persistence of NODAC at 6 months. CONCLUSION: Preexisting DM is a risk factor for severe COVID 19 disease. Patients with NODAC have evidence of persistence insulin resistance on follow up, underscoring the need for long term glycemic monitoring.

Postmenopausal women treated for breast cancer with insulin resistance: clinical, analytical, cross-sectional.

This study aims to investigate the potential association between serum levels of cytokines, HSP60, HSP70 and IR (HOMA-IR) in postmenopausal women. We conducted a cross-sectional study involving 381 postmenopausal women, including 94 with a breast cancer diagnosis and 278 without. We analyzed anthropometric and laboratory measurements. Immunoassays were used to measure cytokines (TNF-α, IL-10, and IL-6) as well as heat shock proteins (HSP) 60 and 70 in the serum using the ELISA technique. Women diagnosed with breast cancer showed higher levels of HOMA-IR, IL-6, TNF, and HSP60, and lower levels of IL-10 and HSP70 compared to women without cancer. An association was found between HSP70 and HOMA-IR only in women with breast cancer (ß = 0.22, p = .030; without cancer: ß = 0.04, p = .404), regardless of age, waist circumference, smoking, and physical activity. No associations were observed between cytokines, HSP60, and HOMA-IR in both groups of women. HSP70 is positively associated with IR in women diagnosed with breast cancer.

Exploring effects of melatonin supplementation on insulin resistance: An updated systematic review of animal and human studies.

BACKGROUND: Insulin resistance (IR), defined as an impaired response to insulin stimulation of target tissues, is a substantial determinant of many metabolic disorders. This study aimed to update the findings of the previous systematic review evidence regarding the effect of melatonin on factors related to IR, including hyperinsulinemia, hyperglycemia, homeostasis model assessment of insulin resistance (HOMA-IR), and quantitative insulin sensitivity check index (QUICKI). METHODS: We systematically reviewed the evidence on the impact of melatonin supplementation on IR indices, fasting insulin, and fasting plasma glucose. PubMed, ScienceDirect, SCOPUS, and Google Scholar databases were searched until March 2024. RESULTS: We identified 6114 potentially relevant articles during the search. Eighteen animal studies and 15 randomized clinical trials met the inclusion criteria. The results indicated that melatonin supplementation reduced fasting plasma glucose (FPG, 14 out of 29 studies), fasting insulin (22 out of 28 studies), HOMA-IR (28 out of 33 studies), and increased QUICKI (7 out of 7 studies). According to RCT studies, melatonin treatment at a dosage of 10 mg reduced HOMA-IR levels in individuals with various health conditions. CONCLUSION: According to most evidence, melatonin supplementation may decrease fasting insulin and HOMA-IR and increase QUICKI but may not affect FPG.

Predictive role of triglyceride-glucose index and HOMA index on development of arterial stiffening in non-diabetic men.

BACKGROUND AND AIMS: Insulin resistance (IR) is a major risk factor for cardiovascular disease. Recently, a novel index (triglyceride-glucose index-TyG) has been proposed as a surrogate marker of IR and a better expression of IR than the Homeostatic Model Assessment of IR (HOMA-IR) index. Few and heterogeneous data are so far available on the relationship between vascular damage and this novel index. Therefore, we aimed to estimate the predictive role of TyG, in comparison with the HOMA-IR, on the development of arterial stiffening (AS), defined as a pulse pressure>60 mmHg, in an 8-year follow-up observation of a sample of non-diabetic adult men (the Olivetti Heart Study). METHODS AND RESULTS: The analysis included 527 non-diabetic men, with normal arterial elasticity at baseline and not on antihypertensive or hypolipidemic treatment. TyG was significantly greater in those who developed AS than those who did not (p = 0.006). On the contrary, the HOMA-IR index was not different between the two groups (p = 0.24). Similar trends were shown by logistic regression analysis adjusting for main confounders. After the stratification by the optimal cut-off point, values of TyG >4.70 were significantly associated with the development of AS, also after adjustment for main confounders. On the contrary, the HOMA-IR index >1.90 was not associated with the risk of AS development in multivariate models. CONCLUSION: The results of this study indicate a predictive role of TyG on AS, independently of the main potential confounders. Moreover, the predictive power of TyG seems to be greater than that of the HOMA-IR index.

Glycated hemoglobin, type 2 diabetes, and poor diabetes control are positively associated with impulsivity changes in aged individuals with overweight or obesity and metabolic syndrome.

Impulsivity has been proposed to have an impact on glycemic dysregulation. However, it remains uncertain whether an unfavorable glycemic status could also contribute to an increase in impulsivity levels. This study aims to analyze associations of baseline and time-varying glycemic status with 3-year time-varying impulsivity in older adults at high risk of cardiovascular disease. A 3-year prospective cohort design was conducted within the PREDIMED-Plus-Cognition substudy. The total population includes 487 participants (mean age = 65.2 years; female = 50.5%) with overweight or obesity and metabolic syndrome. Insulin resistance (HOMA-IR), glycated hemoglobin (HbA1c), presence of type 2 diabetes mellitus, and type 2 diabetes control were evaluated. Impulsivity was measured using the Impulsive Behavior Scale questionnaire and various cognitive measurements. Impulsivity z-scores were generated to obtain Global, Trait, and Behavioral Impulsivity domains. Linear mixed models were used to study the longitudinal associations across baseline, 1-year, and 3-year follow-up visits. HOMA-IR was not significantly related to impulsivity. Participants with higher HbA1c levels, type 2 diabetes, and poor control of diabetes showed positive associations with the Global Impulsivity domain over time, and those with higher HbA1c levels were further related to increases in the Trait and Behavioral Impulsivity domains over the follow-up visits. These results suggest a potential positive feedback loop between impulsivity and glycemic-related dysregulation.

Age-related differences in fluctuations in insulin resistance evaluated with HOMA-IR and triglyceride and glucose-based indices during the menstrual cycle, as determined using the NHANES cross-sectional dataset.

OBJECTIVES: To determine how age affects insulin resistance during the menstrual cycle and insulin resistance-associated indices: the Triglyceride-glucose and Triglyceride-glucose-BMI indexes. METHODS: This prospective observational study used fasting plasma glucose, fasting insulin, triglycerides, body mass index (BMI), and days since the start of the menstrual period collected from the NHANES dataset (1999-2006). Insulin resistance was determined using the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR). The participants were categorized as young (16-34 years) or older (>35 years). Rhythmicity during the menstrual cycle was analyzed using the Cosinor and Cosinor2 packages for R. MAIN OUTCOME MEASURES: Cosine fit curves for insulin resistance during the menstrual cycle and age-associated effects on rhythmicity. RESULTS: Using 1256 participants, rhythmicity was observed for fasting insulin and HOMA-IR (p < 0.05) but not for fasting plasma glucose, the Triglyceride-glucose index, or the Triglyceride-glucose-BMI index. Significant amplitudes for fasting insulin and HOMA-IR were observed when age was considered. Acrophases for fasting insulin and HOMA-IR were significant only for the younger group, and the differences between these groups were significant, suggesting that the changes in scores for insulin resistance for the younger and older groups occur at different times of their menstrual cycle. CONCLUSIONS: Insulin resistance does fluctuate during the menstrual cycle, and it is at a maximum at different times for younger and older women. Since these results are unadjusted, this study is preliminary and further investigation is required.

Association of HOMA-IR with unexpected poor ovarian response in non-obese women in poseidon 1: a retrospective cohort study.

BACKGROUND: Insulin resistance (IR) is related with adverse outcomes of in vitro fertilization (IVF) in women with obesity, but little is known about the relationship between IR and unexpected poor ovarian response (uPOR) in non-obese subjects with sufficient ovarian parameters (classified as POSEIDON group 1). This research aims to explore the association between the homeostasis model assessment of insulin resistance (HOMA-IR) and uPOR in non-obese women with normal biomarkers of ovarian reserve. METHODS: The retrospective cohort study was conducted at a fertility center. The main inclusion criteria were age < 35 years, body mass index (BMI) < 28 kg/m2, normal ovarian reserve (anti-Mullerian hormone ≥ 1.2 ng/ml, antral follicle count ≥ 5). Women undergoing the first oocyte retrieval cycle were included consecutively between 2018 until 2023. Patients who have ≤ 9 oocytes retrieved were defined as uPOR. The multivariable logistic model and subgroup analysis were conducted after adjusting confounders. RESULTS: A total of 6977 cycles were included. The adjusted odds ratio was 1.25 (95% confidence interval [CI], 1.12-1.39) for the increment of Ln HOMA-IR which was taken as a continuous variable. Meanwhile, as a sensitivity analysis, elevated tertile of HOMA-IR exhibited an increase in risk of uPOR for the third tertile (≥ 2.75) when compared with the first tertile (< 1.75) with OR of 1.33 (95%CI, 1.15-1.54). In the subgroup analysis, the positive association remained consistent. CONCLUSION: Elevated HOMA-IR values is significantly associated with increased risk of uPOR in non-obese women classified as POSEIDON group 1. Our study provided evidence for the adverse influence of IR on the ovarian response during IVF and shed light on the importance of IR measurement at the time of pre-stimulation among non-obese women.

Association between insulin resistance and vascular damage in an adult population in China: a cross-sectional study.

There is a relative scarcity of large-scale population studies investigating the relationship between the insulin resistance index of homeostasis model assessment (HOMA-IR) and vascular damage. Therefore, we assessed the association between HOMA-IR and vascular damage in adults aged 18 years and older in China. A total of 17,985 research subjects were included. Vascular damage markers and relevant laboratory tests were measured. HOMA-IR was calculated as (fasting insulin * fasting blood glucose)/22.5. Vascular damage included arteriosclerosis (ba-PWV > 1800 cm/s), peripheral artery disease (ABI < 0.9), and microalbuminuria (UACR > 30 mg/g). The relationship between HOMA-IR and vascular damage was analyzed using the RCS. The restricted cubic spline (RCS) analysis suggested that HOMA-IR was nonlinearly associated with arteriosclerosis (P for no-liner < 0.01), peripheral artery disease (P for no-liner < 0.01), and microalbuminuria (P for no-liner < 0.01). Further segmented regression analyses revealed that in study subjects with HOMA-IR < 5, we found that HOMA-IR was associated with an increased OR for arteriosclerosis (OR: 1.36, 95% CI (1.28, 1.45), P < 0.01), peripheral artery disease (OR: 1.33, 95% CI (1.10, 1.60), P < 0.01) and microalbuminuria (OR: 1.59, 95% CI (1.49, 1.70), P < 0.01). HOMA-IR is an independent risk factor for vascular damage, both macrovascular and microvascular. The phenomenon of saturation of HOMA-IR with vascular damage needs further investigation.

The undervalued league of insulin resistance testing: uncovering their importance.

Type 2 diabetes, obesity, and several other metabolic diseases are all largely attributed to the problem known as insulin resistance. Diagnosing insulin resistance promptly and accurately is essential for adequately managing and intervening in metabolic disorders. Several diagnostic methods have been developed to assess insulin resistance. However, each method has advantages and disadvantages. The most precise test is the hyperinsulinemic-euglycemic clamp, which examines the direct impact of insulin on glucose uptake by tissues. However, it is primarily utilized in research due to its complexity and intrusiveness. Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and the Quantitative Insulin Sensitivity Check Index (QUICKI) are the second most used Insulin resistance tests in the clinical setup. These tests are based on measuring the fasting glucose and insulin levels. The Oral Glucose Tolerance Test (OGTT), Insulin tolerance test, and the Matsuda Index are further diagnostic procedures that shed light on insulin sensitivity. The improved techniques, such as the insulin suppression test and the minimal model analysis, provide substitutes for unique clinical circumstances. Additionally, including extra measurements with these tests, like waist circumference, lipid profiles, and inflammatory markers, can improve the evaluation of insulin resistance. In summary, identifying insulin resistance is essential for the early detection and treatment of various metabolic illnesses. To make educated judgments and improve patient care, healthcare workers should be aware of the different available diagnostic tests and how they are used in each situation. Insulin resistance detection and monitoring will require further study to improve current diagnostic approaches and create novel, less invasive techniques.

ß-cell dedifferentiation in HOMA-ßlow and HOMA-ßhigh subjects.

CONTEXT: ß-cell dedifferentiation ratio is increased in type 2 diabetes; but its direct link to in vivo ß-cell function in human remains unclear. OBJECTIVE: The present study was designed to investigate whether ß-cell dedifferentiation in situ was closely associated with ß-cell function in vivo and to identify targets crucial for ß-cell dedifferentiation/function in human. METHODS: We acquired HOMA-ß values, calculated the number of hormone-negative endocrine cells and evaluated important markers and novel candidates for ß-cell dedifferentiation/function on paraneoplastic pancreatic tissues from 13 patients with benign pancreatic cystic neoplasm (PCN) or intrapancreatic accessory spleen. RESULTS: Both ß-cell dedifferentiation ratio and dedifferentiation marker (Aldh1a3) were inversely related with in vivo ß-cell function (HOMA-ß) and in situ ß-cell functional markers Glut2 and Ucn3 in human. Moreover, the islets from HOMA-ßlow subjects were manifested as 1) increased ß-cell dedifferentiation ratio, 2) enriched dedifferentiation maker Aldh1a3, and 3) lower expression of Glut2 and Ucn3, compared to those from HOMA-ßhigh subjects. We found that basic leucine zipper transcription factor 2 (Bach2) expression was significantly induced in islets from HOMA-ßlow patients and was positively correlated with the ratio of ß-cell dedifferentiation in human. CONCLUSIONS: Our findings emphasize the contribution of ß-cell dedifferentiation to ß-cell dysfunction in human. The Bach2 induction in ß-cells with higher frequency of dedifferentiation observed in HOMA-ßlow subjects reinforce its distinctive role as a pharmaceutical target of ß-cell dedifferentiation for the treatment of human diabetes.

The biological variation of insulin resistance markers: data from the European Biological Variation Study (EuBIVAS).

OBJECTIVES: An insulin resistant state is characteristic of patients with type 2 diabetes, polycystic ovary syndrome, and metabolic syndrome. Identification of insulin resistance (IR) is most readily achievable using formulae combining plasma insulin and glucose results. In this study, we have used data from the European Biological Variation Study (EuBIVAS) to examine the biological variability (BV) of IR using the Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) and the Quantitative Insulin sensitivity Check Index (QUICKI). METHODS: Ninety EuBIVAS non-diabetic subjects (52F, 38M) from five countries had fasting HOMA-IR and QUICKI calculated from plasma glucose and insulin samples collected concurrently on 10 weekly occasions. The within-subject (CVI) and between-subject (CVG) BV estimates with 95 % CIs were obtained by CV-ANOVA after analysis of trends, variance homogeneity and outlier removal. RESULTS: The CVI of HOMA-IR was 26.7 % (95 % CI 25.5-28.3), driven largely by variability in plasma insulin and the CVI for QUICKI was 4.1 % (95 % CI 3.9-4.3), reflecting this formula's logarithmic transformation of glucose and insulin values. No differences in values or BV components were observed between subgroups of men or women below and above 50 years. CONCLUSIONS: The EuBIVAS, by utilising a rigorous experimental protocol, has produced robust BV estimates for two of the most commonly used markers of insulin resistance in non-diabetic subjects. This has shown that HOMA-IR, in particular, is highly variable in the same individual which limits the value of single measurements.

Association of Serum Adipsin Level with Insulin Resistance and Inflammatory Markers in Newly Diagnosed Type two Diabetes Mellitus Patients.

Adipsin is an anti-inflammatory adipokines and its altered level was seen in obesity and type II DM. Our study investigated the clinical significance of serum adipsin levels as a risk marker for type 2 diabetes and its relationships with insulin resistance and various adipo-cytokines. The study included 110 treatment-naïve T2DM cases and 100 controls of similar age and gender from northern India. Clinical, biochemical, and anthropometric characteristics were all profiled. Serum adipo-cytokines were measured using ELISA methods. Adipsin was significantly inversely correlated with body mass index (BMI), waist circumference, fasting plasma glucose, glycated haemoglobin (HbA1C), total cholesterol (TC), triglyceride (TG), homeostasis model assessment-estimated insulin resistance (HOMA-IR), tumour necrosis factor- α (TNF-α) and interleulin-6 (IL-6) and positively correlated with high-density lipoprotein cholesterol (HDL-C) and homeostasis model assessment of ß-cell function (HOMA-B) (P < 0.05). T2DM occurrence decreased with increasing concentration of adipsin with an odds ratio (OR) of 0.68 (95% CI = 0.58-0.79), P < 0.001. The area under curve (95% CI) for adipsin was 0.70 (0.63 to 0.76) with P < 0.001. The best cutoff value for adipsin to predict T2DM was < 5.50 µg/ml with 47.27% sensitivity and 82.00% specificity. FPG and WC were both independent predictors of serum adipsin levels. Our findings showed that high adipsin levels reduced the likelihood of T2DM and emerged as a potential risk marker in the prediction of T2DM.

Triglyceride-Fasting Glucose Index and Homeostatic Model Assessment for Insulin Resistance as Predictors of Type 2 Diabetes Mellitus in South Indians With Normal Body Mass Index.

INTRODUCTION:  Early detection of type 2 diabetes mellitus (T2DM) is imperative to prevent the complications associated with the disease. Current guidelines for diagnosis rely on the assessment of serum glucose (fasting and post-prandial) and glycosylated hemoglobin (HbA1c) levels. Insulin resistance, a phenomenon associated with T2DM, has been observed before the changes in these metrics. The homeostatic model assessment for insulin resistance (HOMA-IR) has been widely used to assess the degree of insulin resistance. The triglyceride-fasting glucose (TyG) index is a newer marker of insulin resistance that merits further study.  Aim: The study aimed to assess the validity of the TyG index and HOMA-IR as markers for the development of T2DM in non-obese individuals.  Materials and methods: One hundred eight non-obese patients without T2DM were included in this prospective cohort study and followed up for eight years. Anthropometric and biochemical parameters, including fasting glucose levels, HbA1c, fasting serum insulin, low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides (TG), were measured at enrolment and eight years follow-up, and HOMA-IR and TyG index were calculated.  Results: Twenty participants out of 108 (18.5%) developed T2DM over eight years. On performing the area under the curve (AUC)-receiver operating characteristic curve analysis, TyG of >8.61 and HOMA-IR of >1.5 had the highest validity (ability) to predict new-onset T2DM in the study population (TyG: AUC: 0.612 (95% CI: 0.514-0.705); HOMA-IR: AUC: 0.529 (95% CI: 0.431-0.626)); however, this was not statistically significant.  Conclusion: At an eight-year follow-up, TyG and HOMA-IR were unreliable predictors of the development of T2DM in non-obese individuals.

Discriminating insulin resistance in middle-aged nondiabetic women using machine learning approaches.

Objective: We employed machine learning algorithms to discriminate insulin resistance (IR) in middle-aged nondiabetic women. Methods: The data was from the National Health and Nutrition Examination Survey (2007-2018). The study subjects were 2084 nondiabetic women aged 45-64. The analysis included 48 predictors. We randomly divided the data into training (n = 1667) and testing (n = 417) datasets. Four machine learning techniques were employed to discriminate IR: extreme gradient boosting (XGBoosting), random forest (RF), gradient boosting machine (GBM), and decision tree (DT). The area under the curve (AUC) of receiver operating characteristic (ROC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score were compared as performance metrics to select the optimal technique. Results: The XGBoosting algorithm achieved a relatively high AUC of 0.93 in the training dataset and 0.86 in the testing dataset to discriminate IR using 48 predictors and was followed by the RF, GBM, and DT models. After selecting the top five predictors to build models, the XGBoost algorithm with the AUC of 0.90 (training dataset) and 0.86 (testing dataset) remained the optimal prediction model. The SHapley Additive exPlanations (SHAP) values revealed the associations between the five predictors and IR, namely BMI (strongly positive impact on IR), fasting glucose (strongly positive), HDL-C (medium negative), triglycerides (medium positive), and glycohemoglobin (medium positive). The threshold values for identifying IR were 29 kg/m2, 100 mg/dL, 54.5 mg/dL, 89 mg/dL, and 5.6% for BMI, glucose, HDL-C, triglycerides, and glycohemoglobin, respectively. Conclusion: The XGBoosting algorithm demonstrated superior performance metrics for discriminating IR in middle-aged nondiabetic women, with BMI, glucose, HDL-C, glycohemoglobin, and triglycerides as the top five predictors.

Effects of Plant-Based Diets on Markers of Insulin Sensitivity: A Systematic Review and Meta-Analysis of Randomised Controlled Trials.

The aim of this systematic review and meta-analysis was to examine the effects of plant-based diets on markers of insulin sensitivity in people with overweight/obesity, prediabetes, or type 2 diabetes (T2D). A systematic literature search in MEDLINE, Embase, CINAHL, and CENTRAL was conducted, and randomised controlled trials (RCTs) investigating the effect of plant-based diets (vegan, ovo-vegetarian, lacto-vegetarian, and lacto-ovo-vegetarian) for ≥14 d on markers of insulin sensitivity in adults (≥18 years) with BMI ≥ 25 kg/m2, prediabetes, or T2D were eligible. We identified eight RCTs, including 716 participants. In comparison with control diets, plant-based diets improved Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) (-0.97, 95% confidence interval (CI) (-1.67, -0.27), p = 0.007) and fasting insulin (-4.13 µU/mL, 95% CI (-7.22, -1.04), p = 0.009) in people with overweight/obesity. In people with prediabetes, one study compared vegan and vegetarian diets and found no difference in HOMA-IR, or fasting insulin. One study of people with T2D reported no difference in immunoreactive insulin and metabolic glucose clearance compared with a conventional diabetes diet. In conclusion, adhering to plant-based diets for ≥14 d improved HOMA-IR and fasting insulin in people with overweight/obesity. Long-term RCTs are needed to determine whether plant-based diets can result in prolonged improvements in insulin sensitivity in people at risk of or with T2D.