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Despite the clear association between remnant cholesterol (RC)and diabetes risk, no study to date has examined the relationship between RC and reversal of prediabetes to normoglycemia. This retrospective cohort study included a total of 15,023 patients with prediabetes who underwent a physical examination between 2010 and 2016. The link between initial RC levels and the reversion from prediabetes to normoglycemia was analyzed using the Cox proportional-hazards regression model. Additionally, the study explored the possible relationship between RC and the probability of returning normoglycemia by applying Cox proportional hazards regression models with cubic spline functions. To address competing risks, a multivariate Cox regression analysis was undertaken, treating the onset of diabetes as a competing risk event for reversing prediabetes to normoglycemia. Additionally, the study incorporated extensive subgroup analyses alongside multiple sensitivity analyses, enhancing the reliability and robustness of the results. After adjusting for covariates, the findings indicated that RC was inversely associated with the likelihood of reverting to normoglycemia (per 5 mg/dL increase, HR = 0.918, 95% CI 0.909–0.927). The analysis also revealed a nonlinear relationship between RC and normoglycemia reversion, with an inflection point at 51.08 mg/dL. For RC values below this inflection point (RC < 50.08 mg/dL), the HR for the probability of returning to normoglycemia was 0.907 (95% CI 0.897–0.917 per 5 mg/dL). Additionally, the competing risks model demonstrated a negative relationship between RC and the reversal of prediabetes to normoglycemia (SHR = 0.92, 95% CI 0.91–0.93). Sensitivity analyses confirmed the robustness and stability of these results. This study demonstrated a negative and non-linear association between RC and the probability of reversion to normoglycemia in Chinese adults with prediabetes. By actively intervening to reduce RC levels, at least to below 51.08 mg/dL, further reduction of RC may significantly increase the probability of returning to normoglycemia from prediabetes. [ABSTRACT FROM AUTHOR]

Objective: Current literature is deficient in robust evidence delineating the correlation between the triglyceride glucose-body mass index (TyG-BMI) and the incidence of stroke. Consequently, this investigation seeks to elucidate the potential link between TyG-BMI and stroke risk in a cohort of middle-aged and senior Chinese individuals. Methods: This study employs longitudinal data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011, 2013, 2015, and 2018, encompassing 8,698 participants. The CHARLS cohort was assembled using a multistage probability sampling technique. Participants underwent comprehensive evaluations through standardized questionnaires administered via face-to-face interviews. Our analytic strategy involved the application of Cox proportional hazards regression models to investigate the association between TyG-BMI and the risk of stroke. To discern potential non-linear relationships, we incorporated Cox proportional hazards regression with smooth curve fitting. Additionally, we executed a battery of sensitivity and subgroup analyses to validate the robustness of our findings. Results: Our study utilized a multivariate Cox proportional hazards regression model and found a significant correlation between the TyG-BMI and the risk of stroke. Specifically, a 10-unit increase in TyG-BMI corresponded to a 4.9% heightened risk of stroke (HR = 1.049, 95% CI 1.029–1.069). The analysis also uncovered a non-linear pattern in this relationship, pinpointed by an inflection point at a TyG-BMI value of 174.63. To the left of this inflection point—meaning at lower TyG-BMI values—a 10-unit hike in TyG-BMI was linked to a more substantial 14.4% rise in stroke risk (HR 1.144; 95% CI 1.044–1.253). Conversely, to the right of the inflection point—at higher TyG-BMI values—each 10-unit increment was associated with a smaller, 3.8% increase in the risk of stroke (HR 1.038; 95% CI 1.016–1.061). Conclusions: In the middle-aged and elderly Chinese population, elevated TyG-BMI was significantly and positively associated with stroke risk. In addition, there was also a specific non-linear association between TyG-BMI and stroke (inflection point 174.63). Further reduction of TyG-BMI below 174.63 through lifestyle changes and dietary control can significantly reduce the risk of stroke. [ABSTRACT FROM AUTHOR]

Objective: The current body of evidence on the association between the ratio of triglycerides to high-density lipoprotein cholesterol (TG/HDL-c) and the reversal of prediabetes to normoglycemia remains limited. The aim of this study is to investigate the association between TG/HDL-c and the reversion to normoglycemia in patients with prediabetes. Methods: This retrospective cohort study included 15,107 individuals with prediabetes from 32 Chinese districts and 11 cities who completed health checks from 2010 to 2016. The Cox proportional-hazards regression model examined baseline TG/HDL-c and reversion to normoglycemia from prediabetes. Cox proportional hazards regression with cubic spline functions and smooth curve fitting determined the non-linear connection between TG/HDL-c and reversion to normoglycemia. We also ran sensitivity and subgroup analysis. By characterizing progression to diabetes as a competing risk for the reversal of prediabetes to normoglycemic event, a multivariate Cox proportional hazards regression model with competing risks was created. Results: Upon adjusting for covariates, the findings indicate a negative association between TG/HDL-c and the likelihood of returning to normoglycemia (HR = 0.869, 95%CI:0.842–0.897). Additionally, a non-linear relationship between TG/HDL-c and the probability of reversion to normoglycemia was observed, with an inflection point of 1.675. The HR on the left side of the inflection point was 0.748 (95%CI:0.699, 0.801). The robustness of our results was confirmed through competing risks multivariate Cox's regression and a series of sensitivity analyses. Conclusion: The present study reveals a negative and non-linear correlation between TG/HDL-c and the reversion to normoglycemia among Chinese individuals with prediabetes. The findings of this study are anticipated to serve as a valuable resource for clinicians in managing dyslipidemia in prediabetic patients. Interventions aimed at reducing the TG/HDL-c ratio through the reduction of TG or elevation of HDL-c levels may substantially enhance the likelihood of achieving normoglycemia in individuals with prediabetes. [ABSTRACT FROM AUTHOR]

Aim: To develop a personalized nomogram and risk score to predict the 5‐year risk of diabetes among Chinese adults with prediabetes. Methods: There were 26 018 participants with prediabetes at baseline in this retrospective cohort study. We randomly stratified participants into two cohorts for training (n = 12 947) and validation (n = 13 071). The least absolute shrinkage and selection operator (LASSO) model was applied to select the most significant variables among candidate variables. And we further established a stepwise Cox proportional hazards model to screen out the risk factors based on the predictors chosen by the LASSO model. We presented the model with a nomogram. The model's discrimination, clinical use and calibration were assessed using the area under the receiver operating characteristic (ROC) curve, decision curve and calibration analysis. The associated risk factors were also categorized according to clinical cut‐points or tertials to create the diabetes risk score model. Based on the total score, we divided it into four risk categories: low, middle, high and extremely high. We also evaluated our diabetes risk score model's performance. Results: We developed a simple nomogram and risk score that predicts the risk of prediabetes by using the variables age, triglyceride, fasting blood glucose, body mass index, alanine aminotransferase, high‐density lipoprotein cholesterol and family history of diabetes. The area under the ROC curve of the nomogram was 0.8146 (95% CI 0.8035‐0.8258) and 0.8147 (95% CI 0.8035‐0.8259) for the training and validation cohort, respectively. The calibration curve showed a perfect fit between predicted and observed diabetes risks at 5 years. Decision curve analysis presented the clinical use of the nomogram, and there was a wide range of alternative threshold probability spectrums. A total risk score of 0 to 2.5, 3 to 4.5, 5 to 7.5 and 8 to 13.5 is associated with low, middle, high and extremely high diabetes risk status, respectively. Conclusions: We developed and validated a personalized prediction nomogram and risk score for 5‐year diabetes risk among Chinese adults with prediabetes, identifying individuals at a high risk of developing diabetes. Doctors and other healthcare professionals can easily and quickly use our diabetes score model to assess the diabetes risk status in patients with prediabetes. In addition, the nomogram model and risk score we developed need to be validated in a prospective cohort study. [ABSTRACT FROM AUTHOR]