The potential of insulin resistance indices to predict non-alcoholic fatty liver disease in patients with type 2 diabetes.

The triglyceride-glucose (TyG) index and related parameters, as well as the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), have been developed as insulin resistance markers to identify individuals at risk for non-alcoholic fatty liver disease (NAFLD). However, its use for predicting NAFLD in patients with type 2 diabetes mellitus (T2DM) remains unclear. In this study, we aimed to observe the performance of insulin resistance indices in diagnosing NAFLD combined with T2DM and to compare their diagnostic values in clinical practice. Overall, 268 patients with T2DM from the Endocrinology Department of Jiangsu Provincial Hospital of Traditional Chinese Medicine were enrolled in this study and divided into two groups: an NAFLD group (T2DM with NAFLD) and a T2DM group (T2DM without NAFLD). General information and blood indicators of the participants were collected, and insulin resistance indices were calculated based on these data. Receiver operating characteristic (ROC) analysis was conducted to calculate the area under the curve (AUC) for insulin resistance-related indices, aiming to assess their ability to discriminate between T2DM patients with and without NAFLD. ROC analysis revealed that among the five insulin resistance-related indices, four parameters (TyG, TyG-body mass index [BMI], TyG-waist circumference [WC], and TyG- (waist-hip ratio [WHR]) exhibited high predictive performance for identifying NAFLD, except for HOMA-IR (AUCs:0.710,0.738,0.737 and 0.730, respectivly). TyG-BMI demonstrated superior predictive value, especially in males. For males, the AUC for TyG-BMI was 0.764 (95% confidence interval [CI] 0.691-0.827). The sensitivity and specificity for male NAFLD were 90.32% and 47.89%, respectively. Moreover, in the Generalized linear regression models, there were positive associations of TyG, TyG-BMI, TyG-WC, TyG-WHR, and HOMA-IR with controlled attenuation parameter (CAP), with β values of 21.30, 0.745, 0.247, and 2.549 (all P < 0.001), respectively. TyG-BMI is a promising predictor of NAFLD combined with T2DM, particularly in lean male patients.

Tian J ，Cao Y ，Zhang W ，Wang A ，Yang X ，Dong Y ，Zhou X ... -  《BMC Endocrine Disorders》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. Level III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》

Triglyceride Glucose Index is Associated with Ultrasonographic Fatty Liver Indicator in Children and Adolescents with Non-alcoholic Fatty Liver Disease.

Non-alcoholic fatty liver disease (NAFLD) is defined as chronic hepatic steatosis and is becoming prevalent, along with the increasing trend for obesity in children and adolescents. A non-invasive and reliable tool is needed to differentiate non-alcoholic steatohepatitis from simple steatosis. This study evaluated the association between the triglyceride glucose (TyG) index and the ultrasonographic fatty liver indicator (US-FLI), and the possibility of using the TyG index for prediction of severity of pediatric NAFLD. One hundred and twenty one patients who were diagnosed with NAFLD by ultrasonography were included. They were categorized into three groups according to body mass index (BMI). Ninety-two were obese, and 19 and 10 were overweight and normal weight, respectively. The homeostatic model assessment for insulin resistance (HOMA-IR) was highest in the group with obesity (p=0.044). The TyG index and US-FLI did not differ significantly among the three BMI groups (p=0.186). Fourteen (11.6%) of the 121 patients had US-FLI ≥6, in whom the BMI-SDS and TyG index were higher (p=0.017, p=0.004), whereas HOMA-IR did not differ significantly from the group with US-FLI <6 (p=0.366). US-FLI was associated with BMI-SDS and the TyG index. TyG index was significantly associated with US-FLI after adjustment for BMI-SDS. The cut-off value for the TyG index for predicting US-FLI ≥6 was 8.91, with an area under the curve of 0.785. TyG index was associated with the degree of hepatic steatosis, suggesting that it might be a useful tool for predicting the severity of pediatric NAFLD.

Kim B ，Jin HY ，Yoon JS ，Noh ES ，Hwang IT ... -  《-》

Association of triglyceride-glucose index and its combination with adiposity-related indices with the incidence of myocardial infarction: a cohort study from the UK Biobank.

The triglyceride-glucose (TyG) index performs better at reflecting insulin resistance when combined with waist circumference (WC), body mass index (BMI), and waist-to-height ratio (WHtR) than when used alone. This study aimed to prospectively examine the relationships between TyG, TyG-BMI, TyG-WC, and TyG-WHtR with the incidence of myocardial infarction (MI) and its subtypes. This cohort study included 370,390 participants from the UK Biobank. The Cox proportional hazards model and restricted cubic spline regression model were used to assess the associations of TyG, TyG-BMI, TyG-WC, and TyG-WHtR with MI, ST-elevation MI (STEMI) and non-ST-elevation MI (NSTEMI). The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were employed to examine the predictive value of four indicators. The hazard ratios (HRs) and 95% confidence intervals (CIs) of MI in the highest quartiles for TyG, TyG-BMI, TyG-WC, and TyG-WHtR were 1.36 (1.28-1.44), 1.47 (1.39-1.56), 1.53 (1.43-1.64), and 1.58 (1.48-1.68) in the fully-adjusted model. Comparable findings were observed when the outcomes were reclassified as STEMI or NSTEMI. However, the associations of TyG-BMI, TyG-WC, and TyG-WHtR with the risk of STEMI were weaker than MI and NSTEMI. A linear dose-response association between TyG and the risk of MI and NSTEMI were demonstrated. TyG-BMI, TyG-WC, and TyG-WHtR all showed nonlinear patterns in their associations with the risk of MI, STEMI, and NSTEMI. TyG-WC was most effective in diagnosing MI (AUC: 0.648, 95% CI: 0.644-0.653), STEMI (AUC: 0.631, 95% CI: 0.622-0.639), and NSTEMI (AUC: 0.647, 95% CI: 0.641-0.654). The TyG index was linearly associated with increased risk of MI and NSTEMI, whereas TyG-BMI, TyG-WC, and TyG-WHtR were nonlinearly associated with increased risk of MI and NSTEMI. There were distinct patterns in the relationships between these indicators with STEMI. TyG-WC provided the best diagnostic effectiveness for MI, STEMI, and NSTEMI.

Zhou J ，Huang H ，Huang H ，Peng J ，Chen W ，Chen F ，Tang Y ，Li Q ，Xiong Y ，Zhou L ... -  《-》

Correlation between triglyceride-glucose index and atrial fibrillation in acute coronary syndrome patients: a retrospective cohort study and the establishment of a LASSO-Logistic regression model.

Insulin resistance (IR) is an independent predictor of atrial fibrillation (AF), but the specific utility of the triglyceride-glucose (TyG) index as a predictive marker for the incidence of AF in the acute coronary syndrome (ACS) population has not yet been explored. To explore the correlation between TyG index and the risk of AF in ACS patients and to establish a predictive model. A retrospective study was conducted on 613 ACS patients admitted to the Department of Cardiovascular Medicine at the First Teaching Hospital of Tianjin University of Traditional Chinese Medicine from January 2022 to September 2024. Patients were divided into four groups based on quartiles of TyG index. Patients were further divided into two groups based on the occurrence of AF: the AF group and the non-AF group. Patient information was collected through the hospital's HIS system. Variable selection was completed using LASSO regression algorithms. Multivariate logistic bidirectional stepwise regression analysis was used to explore the correlation between the TyG index and the risk of AF in ACS patients and to construct a regression model. Three different models were constructed by adjusting for confounding factors and restricted cubic spline plots were drawn to validate the significance of the TyG index combined with AF further. The predictive value of the LASSO-multivariate logistic bidirectional stepwise regression model and the TyG index alone for predicting AF in ACS patients was analyzed using the receiver operating characteristic curve. The LASSO-multivariate logistic bidirectional stepwise regression algorithm showed that coronary heart disease (CHD), valvular heart disease (VHD), TyG, age (AGE), and diastolic blood pressure (DBP) were risk factors for AF in ACS. The restricted cubic spline model demonstrated a significant linear relationship between a higher TyG index and an increased risk of AF in the ACS patient population. The area under the curve (AUC) for predicting AF in ACS patients using the TyG index and the LASSO-multivariate logistic bidirectional stepwise regression model was 0.65(95%CI = 0.58 ~ 0.73) and 0.71(95%CI = 0.65 ~ 0.77) respectively. Additionally, the correlation between the TyG index and AF was consistent across different subgroups. In ACS patients, the TyG index is a stable and independent predictor of AF, with specific clinical value in identifying the occurrence of AF in this population.

Yao C ，Qin Y ，Yan X ，Zhao Z ，Wang B ，Bai Y ，Zhang T ，Hou Y ... -  《BMC Cardiovascular Disorders》