The triglyceride–glucose (TyG) index has been correlated with insulin resistance. We aim to investigate the role of the TyG index on cardiovascular (CV) events in type 2 diabetes mellitus and compare the roles of fasting glucose, hemoglobin A_1c, and the TyG index in predicting CV events. This retrospective study enrolled 3524 patients with type 2 diabetes from the Kaohsiung Medical University Research Database in 2009 in this longitudinal study and followed them until 2015. The TyG index was calculated as log (fasting triglyceride level (mg/dL) × fasting glucose level (mg/dL)/2). CV events included myocardial infarction, unstable angina, stroke, hospitalization for coronary artery disease, peripheral artery disease, and CV-related death. The association between variables and CV events was assessed using a multivariable stepwise Cox proportional hazard analysis. Two hundred and fifteen CV events (6.1%) were recorded during a follow-up period of 5.93 years. The multivariable stepwise analysis showed that high fasting glucose (HR, 1.007; p < 0.001) and a high TyG index (HR, 1.521; p = 0.004) but not hemoglobin A_1c or triglycerides were associated with a higher rate of CV events. Adding fasting glucose and the TyG index to the basic model improved the predictive ability of progression to a CV event (p < 0.001 and p = 0.018, respectively), over that of hemoglobin A_1c (p = 0.084) and triglyceride (p = 0.221). Fasting glucose and the TyG index are useful parameters and stronger predictive factors than hemoglobin A_1c and triglyceride for CV events and may offer an additional prognostic benefit in patients with type 2 diabetes.

The aim of this study was to investigate the associations between the triglyceride-glucose (TyG) index, a marker of insulin resistance, and microangiopathies and macroangiopathies in patients with type 2 diabetes mellitus (DM). Our study enrolled 1990 type 2 diabetic patients from local hospitals in Taiwan during the period of 2002–2004. Multivariate logistic regression analysis was used to identify the factors related to microangiopathies, macroangiopathiess and TyG index. The patients were stratified by TyG index quartile (Q1–Q4). Adjusted odds ratios (aORs) of albuminuria for Q3 versus Q1 and Q4 versus Q1 were 1.424 (95% confidence interval [CI], 1.062–1.910, p = 0.018) and 1.948 (95% CI, 1.437–2.642, p < 0.001), respectively. The aOR of cerebrovascular disease (CVA) was 2.264 for Q4 versus Q1 (95% CI, 1.243–4.122, p = 0.008), but there were no significant associations with diabetic retinopathy (DR), coronary artery disease (CAD) or peripheral artery occlusive disease (PAOD). Significant stepwise increases were found in CVA (p = 0.0013) and albuminuria ≥30 mg/g (p < 0.001) corresponding to TyG index quartiles, but not DR (p = 0.573), CAD (p = 0.880) or PAOD (p = 0.223). There was a significant association between a high TyG index and a high risk of microalbuminuria and CVA in the study cohort. Further studies to investigate the use of medications in patients with DM to prevent micro- and macro-angiopathies are thus warranted.

This study aimed to evaluate the performance of 11 obesity-related indices, including body mass index (BMI), waist circumference, waist-to-height ratio, waist–hip ratio, a body shape index, abdominal volume index, body adiposity index, body roundness index, conicity index, visceral adiposity index (VAI), and triglyceride glucose (TyG) index, in identifying metabolic syndrome (MetS) in adults. The information of 5000 participants was obtained from the Taiwan Biobank. Logistic regression analyses were performed to determine the associations between MetS and obesity-related indices with odds ratio (ORs). The predictive performance of the indices to identify MetS was compared using receiver operating characteristic (ROC) curves and areas under curves (AUCs). Multivariate-adjusted logistic regression showed that the ORs for MetS increased across the quartiles of each index. ROC curves analysis demonstrated that TyG index had the greatest AUC in men (AUC = 0.850) and women (AUC = 0.890). Furthermore, VAI had the greatest AUC in men (AUC = 0.867) and women (AUC = 0.925) aged 30−50 years, while TyG index had the greatest AUC in men (AUC = 0.849) and women (AUC = 0.854) aged 51−70 years. Among the studied obesity-related indices, TyG index and VAI exhibited the best performance for identifying MetS in adults. TyG index and VAI may be the relevant indices to assess MetS in clinical practice.

Evaluating nutritional status is crucial to detecting malnutrition in patients with chronic kidney disease (CKD). The Geriatric Nutritional Risk Index (GNRI) has been associated with overall and cardiovascular mortality in the dialysis population. The aim of this study was to evaluate whether the GNRI is associated with progression to dialysis in patients with moderate to advanced CKD. We enrolled 496 patients with stage 3–5 CKD who had received echocardiographic examinations, and categorized them according to baseline GNRI values calculated using the serum albumin level and body weight. The renal end-point was defined as the commencement of dialysis. During follow-up (mean, 25.2 ± 12.5 months; range, 3.3–50.1 months), 106 (21.4%) of the patients progressed to dialysis. The GNRI was positively correlated with the left ventricular ejection fraction (LVEF) (r = 0.111, p = 0.014), and negatively correlated with the left ventricular mass index (r = −0.116, p = 0.001), left ventricular hypertrophy (r = −0.095, p = 0.035), and LVEF < 50% (r = −0.138, p = 0.002). In multivariable Cox analysis, a low GNRI, female sex, high systolic blood pressure, high fasting glucose, and low estimated glomerular filtration rate were independently associated with progression to dialysis. A low GNRI was independently associated with progression to dialysis in our study cohort. The GNRI may be useful in predicting the risk of adverse renal outcomes in patients with CKD stages 3–5. Additional studies are needed to explore whether an improvement in GNRI delays CKD progression.

Little is known about the predictive value of glycosylated hemoglobin (HbA_1C) variability in patients with advanced chronic kidney disease (CKD). The aim of this study was to investigate whether HbA_1C variability is associated with progression to end-stage renal disease in diabetic patients with stages 3–5 CKD, and whether different stages of CKD affect these associations. Three hundred and eighty-eight patients with diabetes and stages 3–5 CKD were enrolled in this longitudinal study. Intra-individual HbA_1C variability was defined as the standard deviation (SD) of HbA_1C, and the renal endpoint was defined as commencing dialysis. The results indicated that, during a median follow-up period of 3.5 years, 108 patients started dialysis. Adjusted Cox analysis showed an association between the highest tertile of HbA_1C SD (tertile 3 vs. tertile 1) and a lower risk of the renal endpoint (hazard ratio = 0.175; 95% confidence interval = 0.059–0.518; p = 0.002) in the patients with an HbA_1C level ≥ 7% and stages 3–4 CKD, but not in stage 5 CKD. Further subgroup analysis showed that the highest two tertiles of HbA_1C SD were associated with a lower risk of the renal endpoint in the group with a decreasing trend of HbA_1C. Our results demonstrated that greater HbA_1C variability and a decreasing trend of HbA_1C, which may be related to intensive diabetes control, was associated with a lower risk of progression to dialysis in the patients with stages 3–4 CKD and poor glycemic control (HbA1c ≥ 7%).

Hyperuricemia has been linked with the development of diabetes, gout, kidney, and cardiovascular diseases. Although obesity is associated with hyperuricemia, data on sex differences in this association are scarce. Therefore, this study was conducted to explore sex differences in the correlations among various indices of obesity with hyperuricemia in Taiwan. Data were obtained from the Taiwan Biobank and included 122,067 participants. After excluding 179 participants with missing data, the remaining 121,888 participants (men: 43,790; women: 78,098) were enrolled. The prevalence rates of hyperuricemia (defined as serum uric acid >7.0/6.0 mg/dL in men/women) were 29.8% and 13.6%, respectively (p < 0.001). Multivariable analysis revealed high values of body shape index (ABSI), waist-to-height ratio (WHtR), waist–hip ratio (WHR), lipid accumulation product (LAP), conicity index (CI), visceral adiposity index (VAI), body adiposity index (BAI), abdominal volume index (AVI), body mass index (BMI), and body roundness index (BRI) were significantly associated with hyperuricemia in both the male and female participants (all p < 0.001). The interactions between sex and all 10 of these indices were significant (all p < 0.001) for hyperuricemia. In men, LAP had the highest area under the curve (0.669), followed by BMI (0.655), VAI (0.645), AVI (0.642), BRI (0.640), WHtR (0.633), BAI (0.605), WHR (0.599), CI (0.574), and ABSI (0.510). In women, LAP also had the highest area under the curve (0.754), followed by BMI (0.728), VAI (0.724), WHtR (0.721), BRI (0.720), AVI (0.713), WHR (0.676), BAI (0.673), CI (0.626), and ABSI (0.544). In conclusion, obesity-related indices were associated with hyperuricemia in this large Taiwanese study, and sex differences were found in these associations, with stronger associations in women than in men.