Bariatric surgery is an effective treatment option for individuals with obesity and type 2 diabetes (T2D). However, whether outcomes in subtypes of individuals at risk for T2D and/or comorbidities (Tübingen Clusters) differ, is unknown. Of these, cluster 5 (C5) and cluster 6 (C6) are high-risk clusters for developing T2D and/or comorbidities, while cluster 4 (C4) is a low-risk cluster. We investigated bariatric surgery outcomes, hypothesizing that high-risk clusters benefit most due to great potential for metabolic improvement.

We allocated participants without T2D but at risk for T2D, defined by elevated BMI, to the Tübingen Clusters. Participants had normal glucose regulation or prediabetes according to American Diabetes Association criteria. Two cohorts underwent bariatric surgery: a discovery (Lille, France) and a replication cohort (Rome, Italy). A control cohort (Tübingen, Germany) received behavioral modification counseling. Main outcomes included alteration of glucose regulation parameters and prediabetes remission.

In the discovery cohort, 15.0% of participants (n = 121) were allocated to C4, 22.3% (n = 180) to C5, and 62.4% (n = 503) to C6. Relative body weight loss was similar among all clusters; however, reduction of insulin resistance and improvement of β-cell function were strongest in C5. Prediabetes remission rate was lowest in low-risk C4 and highest in high-risk C5. Individuals from high-risk clusters changed to low-risk clusters in both bariatric surgery cohorts but not in the control cohort.

Participants in C5 had the highest benefit from bariatric surgery in terms of improvement in insulin resistance, β-cell function, and prediabetes remission. This novel classification might help identify individuals who will benefit specifically from bariatric surgery.

Individuals at increased risk of type 2 diabetes have recently been classified into six prediabetes clusters, which stratify the risk of progression to diabetes and diabetes complications. Clusters 1, 2 and 4 are low-risk clusters while clusters 3, 5 and 6 are high-risk clusters; individuals in cluster 6 have an elevated risk of nephropathy and all-cause mortality despite delayed onset of diabetes. The urinary peptidome classifiers CKD273 (chronic kidney disease, CKD), HF2 (heart failure, HF) and CAD238 (coronary artery disease, CAD) are based on unique urinary peptide patterns and have shown potential for identifying individuals at risk for CKD and cardiovascular pathologies. This observational study investigates whether peptidome classifiers can differentiate complication risks across the prediabetes clusters and if a novel combination of peptides can distinguish high-risk from low-risk prediabetes clusters.

Urine peptidome analysis was performed on spot urine samples from individuals across 6 prediabetes clusters (n = 249) and 19 individuals with screen-detected diabetes (study cohorts at University Hospital Tübingen, Germany from 11/2004 to 11/2012). Predefined urinary classifiers were calculated for each participant. Lasso regression analysis was used to identify an optimal combination of peptides distinguishing low- Schlesinger et al. (2022), Wagner et al. (2021) [1,2,4] and high-risk (Rooney et al., 2021; Wagner, 2023; Latosinska et al., 2021 [3,5,6]) clusters.

The predefined urinary peptidome classifiers CKD273, HF2 and CAD238 differed significantly across prediabetes clusters, particularly with elevated values in cluster 6 compared to the healthiest cluster 2. CKD273, HF2 and CAD238 were inversely associated with insulin sensitivity indexes. Machine Learning identified a combination of 112 urinary peptides that differentiated low-risk from high-risk prediabetes clusters (AUC-ROC 0.868 (95 % CI 0.755-0.981)).

Urinary peptidome classifiers support the increased risk of CKD and suggest an elevated risk of heart failure and coronary artery disease in the high-risk prediabetes cluster 6. Urine peptidomics show promising potential as a tool for identifying high-risk prediabetes individuals and guiding early preventive interventions.

Atherogenicity indices have emerged as promising markers for cardiometabolic disorders, yet their relationship with prediabetes risk remains unclear. This study aimed to comprehensively evaluate the associations between six atherogenicity indices and prediabetes risk in a Chinese population, and explore the predictive value of these atherosclerotic parameters for prediabetes.

This retrospective cohort study included 97,151 participants from 32 healthcare centers across China, with a median follow-up of 2.99 (2.13, 3.95) years. Six atherogenicity indices were calculated: Castelli's Risk Index-I (CRI-I), Castelli's Risk Index-II (CRI-II), Atherogenic Index of Plasma (AIP), Atherogenic Index (AI), Lipoprotein Combine Index (LCI), and Cholesterol Index (CHOLINDEX). To address the natural relationships between the atherogenicity indices and risk of prediabetes, we applied Cox proportional hazards regression with cubic spline functions and smooth curve fitting, using a recursive algorithm to calculate inflection points. Machine learning approach (XGBoost and Boruta methods) to address the high collinearity among indices and assess their relative importance, combined with time-dependent ROC analysis to evaluate the predictive performance at 3-, 4-, and 5-year follow-up.

During follow-up, 11,199 participants developed prediabetes (incidence rate: 3.71 per 100 person-years). Significant nonlinear associations were observed between all atherogenicity indices and prediabetes risk. Through Z-score standardization of atherogenicity indices and comprehensive Cox proportional hazards regression and advanced machine learning techniques, we identified AIP as the most significant predictor of prediabetes [HR = 1.057 (95% CI 1.035-1.080, P < 0.0001)], with LCI emerging as a secondary important marker [HR = 1.020 (95% CI 1.002-1.038, P = 0.0267)]. Our innovative XGBoost and Boruta analysis uniquely validated these findings, providing robust evidence of AIP and LCI's critical role in prediabetes risk assessment. Time-dependent ROC analysis further validated these findings, with LCI and AIP demonstrating comparable discrimination, with overlapping AUC ranges of 0.5952-0.6082. Notably, the combined indices model achieved enhanced predictive performance (AUC: 0.6753) compared to individual indices, suggesting the potential benefit of using multiple atherogenicity indices for prediabetes risk prediction.

This study identifies statistically significant associations between atherogenicity indices and prediabetes risk, highlighting their nonlinear relationships and combined effects. While the predictive performance of these indices is modest (AUC 0.55-0.68), these findings may contribute to improved risk stratification when incorporated into comprehensive assessment strategies.

Existing evidence suggests that elevated 1-hour post-load plasma glucose (1-h PG ≥ 8.6 mmol/L) during an oral glucose tolerance test (OGTT) is associated with atherogenic lipid parameters which are linked to an increased risk of cardiovascular disease (CVD). However, it remains unclear whether normal glucose tolerance (NGT) individuals with elevated 1-h PG (NGT-1hPG-high) should still be considered low-risk. Therefore, this study aims to demonstrate comprehensive lipid characteristics in individuals with different glycemic status stratified by 1-h PG, with a particular focus on those with NGT-1hPG-high.

This cross-sectional study included individuals aged 25-55 years with high-risk of diabetes from the Daqing Diabetes Prevention Study II (Daqing DPS-II). Individuals were categorized into different glycemic status based on the World Health Organization's 1999 criteria and the International Diabetes Federation's 2024 position statement on 1-h PG. Traditional (TC, TG, HDL-C, LDL-C) and non-traditional lipid parameters [ApoA-1, ApoB, sdLDL-C, Lp(a), non-HDL-C, remnant cholesterol (RC), ApoB/ApoA-1, LDL-C/ApoB] were measured. Dyslipidemia was defined according to the 2023 Chinese Guidelines for Lipid Management. The China-PAR equation was used to estimate 10-year CVD risk. Spearman's correlation coefficients were calculated to evaluate the correlation between lipid parameters and 10-year CVD risk. Logistic and multiple linear regression models were performed to assess the association between 1-h PG and dyslipidemia as well as lipid parameters adjusting for covariates.

Among 2 469 individuals, 22.7% had NGT with normal 1-h PG (NGT-1hPG-normal), 19.9% had NGT-1hPG-high, 2.6% had prediabetes with normal 1-h PG (PDM-1hPG-normal), 34.2% had prediabetes with elevated 1-h PG (PDM-1hPG-high), and 20.6% had newly diagnosed diabetes. The prevalence of dyslipidemia did not significantly differ between NGT-1hPG-high and PDM-1hPG-high (OR = 1.13, 95%CI: 0.88-1.44, P > 0.05). Higher 1-h PG levels were consistently associated with an atherogenic lipid profile, characterized by increased TC, TG, LDL-C, ApoB, sdLDL-C, non-HDL-C, RC and ApoB/ApoA-1, along with decreased ApoA-1, HDL-C and LDL-C/ApoB (all P < 0.05). Among lipid parameters, TG, sdLDL-C, RC, ApoB/ApoA-1, LDL-C/ApoB and HDL-C showed the strongest correlation with 10-year CVD risk, with Spearman's correlation coefficients of 0.41, 0.38, 0.35, 0.31, - 0.37 and - 0.36, respectively. In the NGT-1hPG-high, TG, sdLDL-C, and ApoB/ApoA-1 levels were significantly higher, while HDL-C and LDL-C/ApoB levels were significantly lower compared to counterparts with NGT-1hPG-normal (all P < 0.05). Moreover, except for TG and RC (both P < 0.01), the majority of lipid parameter levels in NGT-1hPG-high did not significantly differ from those in PDM (all P > 0.05).

NGT-1hPG-high exhibited a similar atherogenic lipid profile to that observed in PDM. 1-h PG could serve as a potential indicator for the early identification of at-risk individuals who may otherwise go undetected among NGT population.

Auricular acupressure has potential in treating prediabetes; however, its effectiveness remains unclear. We aimed to evaluate the effect of auricular acupressure on blood glucose levels in patients with prediabetes and to identify optimal acupoints.

We searched nine public databases for randomized controlled trials published before March 1, 2025, according to pre-established inclusion and exclusion criteria. The risk of bias was assessed using the Risk of Bias 2 tool. RevMan 5.3 was employed to conduct a meta-analysis on glycosylated hemoglobin A1c (HbA1c), fasting blood glucose (FBG), and 2-h postprandial blood glucose (2h-PBG) levels, and body mass index (BMI). We used a Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach to assess the certainty of evidence. Data mining was used to determine optimal acupoints.

This meta-analysis involved eight studies (694 participants). Compared with lifestyle intervention alone, auricular acupressure combined with lifestyle intervention significantly reduced HbA1c (mean difference [MD] -0.51, 95 % CI -0.84 to -0.18), FBG (MD -0.63, 95 % CI -0.94 to -0.31), and 2h-PBG (MD -0.78, 95 % CI -0.95 to -0.62) levels in patients with prediabetes but no significant effect was observed concerning BMI (MD -0.26, 95 % CI -1.15 to 0.63). The GRADE showed low to very low certainty levels of evidence. Data mining indicated that CO4, CO10, CO11, CO13, CO14, and CO17 were core acupoints for prediabetes.

Auricular acupressure demonstrates potential as a complementary approach for prediabetes, with CO4, CO10, CO11, CO13, CO14, and CO17 identified as optimal acupoints. However, due to methodological limitations, these findings require further validation through high-quality evidence.

Prediabetes is a medical condition characterized by increased levels of glucose in the bloodstream. There are some lifestyle modifications like exercise, dietary patterns and prevention that can reverse prediabetes. Exercise plays an important role in controlling hyperglycemia and insulin sensitivity in prediabetes.

The objective of the study is to develop a consensus driven exercise base manual programme for the prediabetic population using the Delphi Method.

A three-rounded Delphi study was conducted with 40 panelists either as Patient panelists (n = 20) or expert panelists (n=20). Round 1 included initial items selected from a systemic literature review . Initial recommendations were rated by panalists through a 5-point Likert scale. Additional items were also added by suggestion of Panelists in Round 1. Rounds 2 and 3 included all items from Round 1. All selected items were included in the final set of recommendations in Round 3 and rated as "Important" or "Very important" by at least 70% of all respondents. Descriptive data was analyzed by using SPSS version 25.

36 panellists (patients n = 17, professionals n = 19) completed Round 3. After three rounds of the Delphi process, panelists reached a consensus on the final version of the recommendations. Sixty-two items reached consensus in Round 1. In round 2 and 3 a total of sixty-four and sixty-three items were added, respectively. Fifty-seven of these reached consensuses in round 3.

The exercise-based manual programme developed by Modified Delphi study provided disease prevention education, physical activity and dietary recommendations to improve glycemic control in the prediabetic population. The exercise manual programme along with lifestyle modifications contribute to public health by improving prediabetes levels and also addressing the modifiable risk factors. An exercise protocol needs time to mitigate hyperglycemia in prediabetic individuals and to help provide information at community level.

To investigate the association between prediabetes, frailty, and the risk of myocardial infarction (MI), stroke, heart failure (HF), and all-cause mortality in the oldest old.

A nationwide retrospective cohort study of individuals aged 80+ classified as prediabetic (HbA1c 5.7%-6.4% or impaired fasting glucose 100-125 mg/dL) or normoglycemic during two baseline periods (2005-2006 and 2014-2015) and follow-up (2007-2013 and 2016-2022). Frailty was assessed using the cumulative deficit method.

Among 126,323 participants (61.4% females, mean age 84.1 ± 3.7 years), 34,151 (27.0%) were classified as persons with prediabetes and 92,172 (73.0%) as normoglycemic at baseline. Over seven years, 13.5% progressed to diabetes, 47.4% regressed to normoglycemia, and 39.1% remained with prediabetes. Non-frail individuals were more likely to progress to diabetes than the severely frail (15.0% vs. 9.3%). Prediabetes was associated with lower all-cause mortality (HR 0.86, 95% CI 0.85-0.88) but not MI (HR 0.98, 95% CI 0.94-1.02), while it was associated with increased risks of HF (HR 1.06, 95% CI 1.03-1.09) and stroke (HR 1.06, 95% CI 1.02-1.10).

In the oldest old (aged 80+), prediabetes is associated with reduced all-cause mortality but slightly increased risks of HF and stroke. Frailty modulates prediabetes progression, with non-frail individuals more likely to develop diabetes.

Background/Objectives: Despite advances in public health and medical treatment, the number of patients with type 2 diabetes is increasing and it remains among the top 10 causes of death and a leading cause of disability in the United States. Early interventions with innovative approaches are essential to improving dietary intake and blood glucose control, potentially preventing or delaying type 2 diabetes and related complications. This study examined the effects of integrating real-time feedback from continuous glucose monitoring (CGM) into individualized nutrition therapy (INT) on diet and sleep quality in individuals with prediabetes and overweight or obesity. Methods: Thirty participants were randomized to either the treatment (n = 15) or the control group (n = 15). Both groups received individualized nutrition recommendations tailored to energy needs for weight maintenance and blood glucose control. The treatment group had real-time access to CGM data, while the control group remained blinded. Dietary intake and sleep quality were assessed using ASA24 recall and analyzed via general linear model repeated measures. Results: Incorporating CGM feedback into nutrition therapy significantly increased whole-grain (p = 0.02) and plant-based protein intake (p = 0.02) in the treatment group, with trends toward increased fruit intake (p = 0.07) and a reduced percentage of calories from carbohydrates (p = 0.08). Sleep efficiency also improved significantly by 5% (p = 0.02) following the intervention. Conclusions: These findings support the effectiveness of CGM-enhanced nutrition therapy in improving diet and sleep quality in individuals with prediabetes and overweight or obesity. Further research is needed to assess the sustainability and long-term impact of this approach.

Type 2 diabetes and prediabetes are associated with a higher risk of several health conditions. We conducted a cross-sectional study to compare the prevalence of comorbidities among 88,724 adults with prediabetes and 12,071 adults with type 2 diabetes in El Paso, Texas, using data from the Paso del Norte Health Information Exchange (PHIX) from 1 January 2021, to 31 January 2023. We estimated prevalence ratios (aPR) adjusted for age decade, gender, and Hispanic ethnicity. Individuals with prediabetes, compared to type 2 diabetes, had lower adjusted prevalence of circulatory (59.1% vs. 80.4%; aPR = 0.82 [95% CI: 0.81-0.84]), genitourinary (44.9% vs. 50.5%; aPR = 0.97 [0.96-0.99]), respiratory (32.0% vs. 35.7%; aPR = 0.94 [0.92-0.97]), neurological (27.4% vs. 32.8%; aPR = 0.91 [0.88-0.94]), blood (21.2% vs. 30.5%; aPR = 0.77 [0.75-0.80]), mental (19.5% vs. 26.1%; aPR = 0.72 [0.69-0.75]), infectious (12.8% vs. 21.5%; aPR = 0.63 [0.60-0.66]), skin (12.2% vs. 14.8%; aPR = 0.82 [0.78-0.86]), and COVID-19 (10.2% vs. 11.9%; aPR = 0.86 [0.81-0.91]) diseases/conditions. Adjusted prevalence was higher among those with prediabetes for musculoskeletal (53.8% vs. 47.0%; aPR = 1.19 [1.17, 1.21]), ear (18.4% vs. 12.9%; aPR = 1.54 [1.47-1.60]), eye (11.1% vs. 7.8%; aPR = 1.52 [1.43, 1.61]), digestive (44.0% vs. 44.0%; aPR = 1.02 [1.00-1.05]), and neoplastic (14.4% vs. 14.5%; aPR = 1.12 [1.06-1.17]) diseases/conditions. People with prediabetes in El Paso, Texas, had a lower prevalence of most comorbidities than those with type 2 diabetes, suggesting that preventing prediabetes from progressing to type 2 diabetes could have a beneficial impact on comorbid disease burden.

Aims: This study evaluates the incidence of (pre)diabetes in an Austrian population over a broad age span and addresses whether alterations in lifestyle, blood markers, and body composition are associated with the development of (pre)diabetes. Material and Methods: Data from the first and second phases of the Austrian LEAD study, a longitudinal population-based cohort study, were used. Inclusion criteria were a valid glycaemic status (i.e., normoglycaemia, prediabetes, and diabetes) at both phases using American Diabetes Association criteria. Besides blood samples, body composition parameters and an interviewer-administered questionnaire were assessed. A binary logistic regression was performed to answer the research question. Results: In total, 7822 individuals (51% females, 46 ± 19 years with 9.6% aged < 18 years, median follow-up time 4.1 [3.9-4.5] years) were included. The overall incidence rate was estimated at 63.0 (95% CI [59.7; 66.3]) and 8.4 (95% CI [7.4; 9.5]) per 1000 person-years for prediabetes and diabetes, respectively. In the 6-<10-, 10-<20-, and 20-<30-year age bins, an incidence rate of, respectively, 30.2, 16.3, and 13.4 per 1000 person-years (prediabetes) and 2.0, 3.5, and 1.3 (diabetes) was observed. Further, 38.3% of diabetic individuals at Visit 2 were undiagnosed and thus untreated. Factors identified as being significantly associated with progression towards (pre)diabetes included changes in triglycerides, high-density lipoprotein cholesterol, total cholesterol, and visceral adipose tissue mass, besides male sex, older age, low education level, and urban residence. Conclusions: The overall incidence of (pre)diabetes in the Austrian population is high and highlights the need for screening from a young age and on a regular basis so that preventive and treatment strategies can be implemented at an early stage. Trial Registration: ClinicalTrials.gov identifier: NCT01727518.

Most existing studies have primarily focused on the effects of Traditional Chinese Exercises (TCEs) on glycemic control in individuals with prediabetes, while specific recommendations for managing dyslipidemia in this population remain insufficient. Moreover, there is a lack of systematic research and conclusive evidence regarding the optimal exercise dose required to achieve metabolic improvements in individuals with prediabetes. Therefore, this meta-analysis aims to comprehensively evaluate the efficacy of TCEs in improving glycemic and lipid profiles in individuals with prediabetes and to explore the potential impact of exercise dose on these metabolic parameters.

A comprehensive search of six databases (PubMed, Web of Science, Cochrane Library, Embase, CNKI, and WanFang Data) followed PRISMA guidelines to identify randomized controlled trials (RCTs) on TCEs (e.g., "Tai Chi," "Yijinjing," "Baduanjin") and prediabetes (e.g., "impaired glucose tolerance," "impaired glucose regulation") published up to November 10, 2024. Three reviewers independently screened studies, extracted data, and assessed bias risk. Meta-analysis and subgroup/meta-regression analyses were conducted using Stata 17 software. The review protocol is registered in PROSPERO (CRD42024615150).

A total of 15 studies involving 1,839 participants were included. The meta-analysis revealed that TCEs significantly improved HbA1c (MD = -0.28%; 95% CI: -0.38% to -0.18%; P = 0.001), FBG (MD = -0.44 mmol/L; 95% CI: -0.53 to -0.34 mmol/L; P < 0.001), 2hPG (MD = -1.16 mmol/L; 95% CI: -1.48 to -0.85 mmol/L; P < 0.001), TC (MD = -0.31 mmol/L; 95% CI: -0.50 to -0.11 mmol/L; P = 0.002), TG (MD = -0.28 mmol/L; 95% CI: -0.50 to -0.06 mmol/L; P = 0.012), and HDL (MD = -0.28 mmol/L; 95% CI: -0.50 to -0.06 mmol/L; P = 0.012) compared to control groups.

TCEs significantly improve prediabetics' blood glucose and lipid levels. The recommended exercise regimen is 30-50 min per session, 2-3 times per week, for at least three months.

Diabetes poses a significant global health challenge, with prediabetes serving as a critical phase for intervention to prevent or delay its progression. While evidence-based strategies have shown promise, their implementation within healthcare systems - particularly in low- and middle-income countries - remains a formidable challenge. This study shares preliminary findings from a regional quality improvement (QI) initiative aimed at identifying and managing prediabetes within Mexico's public healthcare framework.

The Diabetes Prevention Squad programme introduced a regional clinical service focusing on individuals at risk for diabetes or diagnosed with prediabetes in primary care settings. This QI initiative adopted a comprehensive approach, guiding participants from initial screening to engagement in a diabetes prevention programme emphasising lifestyle modifications. A cascade analysis was conducted, with results drawn from a pretest-posttest design comprising 14 visits over 1 year.

Of the 1,256 participants screened, 90 were diagnosed with prediabetes. Among those who completed the intensive phase, 57% achieved prediabetes remission, and 37% experienced significant weight loss.

This QI initiative demonstrated a promising prediabetes remission rate among participants, underscoring the importance of a complete care pathway from screening to remission. Prediabetes remission and significant weight loss are vital outcomes in diabetes prevention. Integrating interventions focused on prediabetes remission into healthcare pathways is essential to reducing the diabetes burden.

Fasting plasma glucose (FPG), glycated hemoglobin A1C (HbA1C), and 2-hour postload plasma glucose (2h PG) are all currently used to define prediabetes. We aimed to determine whether a higher number of prediabetes defects correspond to an increased all-cause and cardiovascular disease (CVD) mortality.

Individuals with prediabetes and available information on FPG, HbA1C, 2h PG, and mortality data were derived from the 2005-2016 National Health and Nutrition Examination Survey. Kaplan-Meier survival curves, Cox proportional hazards regression analysis, and stratified analysis were used to compare all-cause and CVD mortality among participants with one, two, and all three defects.

Among the 4511 individuals included, 76.31%, 30.89%, and 41.65% met the FPG-, 2h PG-, and HbA1C-defined criteria for prediabetes, respectively. There were 2609 (60.78%), 1420 (29.60%), and 482 (9.62%) adults meeting one, two, and all three criteria for prediabetes, respectively. During a median follow-up of 100 months, a total of 534 (180 CVD-related) deaths occurred. The multivariable-adjusted hazard ratios and 95% confidence intervals in those meeting two and three criteria were 1.341 (1.042-1.727) and 1.369 (1.027-1.824), respectively, for all-cause mortality (P for trend = 0.006), and 1.836 (1.228-2.744) and 2.037 (1.092-3.801), respectively, for CVD mortality (P for trend = 0.002), with those meeting only one criterion as the reference. In subgroup analysis, the association between the number of diagnostic criteria for prediabetes and CVD mortality was observed only in men.

A higher number of diagnostic criteria for prediabetes was associated with increased all-cause and CVD mortality.

Prediabetes is a chronic condition characterized by elevated blood glucose levels that are not yet high enough to be classified as diabetes. It is particularly prevalent among middle-aged and elderly populations. This study aims to investigate the association between a novel marker of insulin resistance-the estimated glucose disposal rate (eGDR)-and the reversion of prediabetes to normoglycaemia or progression to diabetes in a Chinese population.

This prospective cohort study utilized baseline data from the 2011 China Health and Retirement Longitudinal Study involving 2,600 prediabetic participants aged 45 years and older, along with follow-up data from 2015. The study's endpoints were defined according to the American Diabetes Association criteria, including maintenance of the prediabetic state, reversion to normoglycaemia, or progression to diabetes. Multivariable Cox regression models and restricted cubic spline regression were used to assess the association between eGDR and the reversion or progression of prediabetes in middle-aged and elderly populations, followed by stratified analyses to explore potential population-specific dependencies.

Over a median follow-up period of 4 years, 1,615 (62.1%) participants remained in the prediabetic state, 586 (22.5%) reverted to normoglycaemia, and 399 (15.3%) progressed to diabetes. In multivariable Cox regression analyses, our results indicated that eGDR was positively associated with the reversion of prediabetes to normoglycaemia [Hazard Ratio = 1.14, 95% Confidence Interval: 1.05, 1.23], and negatively associated with the progression of prediabetes to diabetes (HR = 0.81, 95% CI: 0.70, 0.93). Restricted cubic spline analysis revealed a nonlinear, L-shaped association between eGDR and the reversion of prediabetes to normoglycaemia, with segmented Cox regression identifying an eGDR threshold of 6.81 as the point of significant change in the likelihood of prediabetes reversion.

This prospective cohort study among middle-aged and elderly Chinese populations suggested that higher eGDR promoted the reversion of prediabetes and provided a protective effect against its progression to diabetes.

Aims: We developed a prediction model for elevated hemoglobin A1c (HbA1c) among patients presenting to the emergency department (ED) at risk for diabetes to identify important factors that may influence follow-up patient care. Methods: Retrospective electronic health records data among patients screened for diabetes at the ED in May 2021 was used. The primary outcome was elevated HbA1c (≥ 5.7%). The data was divided into a derivation set (80%) and a test set (20%) stratified by elevated HbA1c. In the derivation set, we estimated the optimal significance level for backward elimination using a 10-fold cross-validation method. A final model was derived using the entire derivation set and validated on the test set. Performance statistics included C-statistic, sensitivity, specificity, predictive values, Hosmer-Lemeshow test, and Brier score. Results: There were 590 ED patients screened for diabetes in May 2021. The final model included nine variables: age, race/ethnicity, insurance, chief complaints of back pain and fever/chills, and a past medical history of obesity, hyperlipidemia, chronic obstructive pulmonary disease, and substance misuse. Adequate model discrimination (C-statistic = 0.75; sensitivity, specificity, and predictive values > 0.70), no evidence of model ill fit (Hosmer-Lemeshow test = 0.29), and moderate Brier score (0.21) suggest acceptable model performance. Conclusion: In addition to age, obesity, and hyperlipidemia, a history of substance misuse was identified as an important predictor of elevated HbA1c levels among patients screened for diabetes in the ED. Our findings suggest that substance misuse may be an important factor to consider when facilitating follow-up care for patients identified with prediabetes or diabetes in the ED and warrants further investigation. Future research efforts should also include external validation in larger samples of ED patients.

The aim of this study is to assess the individual and joint associations of variability in multiple cardiometabolic parameters with mortality risk across older populations.

A total of 51,551 Chinese elderly participants (aged ≥60 years) with ≥3 measurements of systolic blood pressure, visceral adiposity index, fasting blood glucose, and low-density lipoprotein cholesterol during 2018-2022 were included. Variability metrics included SD, coefficient of variation, average real variability, and variability independent of the mean (used in primary analysis). Participants were classified on the basis of the number of high-variability (highest quartile of variability) parameters into 4 categories: with 0, 1, 2, and 3-4 high-variability cardiometabolic parameters. Cox regression analyses were performed in 2024. Findings were then externally validated using the Health and Retirement Study (Waves 8-15).

Higher systolic blood pressure, visceral adiposity index, fasting plasma glucose, and low-density lipoprotein cholesterol variability were associated with greater all-, cardiovascular-, and other-cause mortality risk. Compared with those of subjects with no high-variability parameters measured as the variability independent of the mean, the hazard ratios (95% CI) of all-cause mortality were 1.30 (1.16, 1.44) for 1 parameter, 1.86 (1.66, 2.09) for 2 parameters, and 2.02 (1.75, 2.32) for 3-4 parameters. Consistent results were noted for cardiovascular-, cancer-, and other-cause mortality using other variability indices and in various sensitivity and subgroup analyses. These associations were validated in the Health and Retirement Study (n=1,991).

Increased variability in cardiometabolic parameters is associated with elevated risks of all-cause and cause-specific mortality among older adults in China. Reducing variability of these parameters could serve as a target to increase life expectancy in older populations.

Lipoprotein(a) [Lp(a)] levels and diabetic status have been recognized as risk factors for atherosclerosis. However, no studies on atherosclerosis have integrated these two indicators. This study aimed to evaluate the relationship between Lp(a) levels, diabetic status, and their combined effects on subclinical atherosclerosis.

This cross-sectional study included patients presenting with a first episode of chest pain at the First Affiliated Hospital of Chongqing Medical University from June 2018 to February 2022. All participants underwent coronary computed tomography angiography (CCTA) and carotid ultrasound to evaluate subclinical atherosclerosis. Logistic regression analysis was used to examine the associations of Lp(a) levels and diabetic status-both individually and in combination-with coronary artery calcium (CAC) and carotid arteriopathy.

Among 912 patients, 473 (51.9%) had CAC and 637 (69.8%) had carotid arteriopathy. After adjusting the confounding variables, elevated Lp(a) levels associated with CAC [odds ratio (OR) 1.51, 95% confidence interval (CI): 1.02-2.24, P=0.040] and carotid arteriopathy (OR 1.77, 95% CI: 1.10-2.86, P=0.02) were statistically significant. After combining diabetic status, almost all Lp(a) levels were significantly associated with CAC and CAC score categories (CAC scores: 0.1-99.9, 100-399.9, ≥400) in the diabetes mellitus (DM) group. In this group, the highest risk for CAC and the most severe CAC score categories were observed in patients with Lp(a) levels of >300 mg/L. Among patients with DM, in the lower Lp(a) level group, the prevalence and severity of CAC were more pronounced than those in the medium Lp(a) level group. Additionally, in patients with DM only, elevated Lp(a) levels were associated with carotid arteriopathy (OR 3.38, 95% CI: 1.24-9.20; P=0.02), increased carotid intima-media thickness (cIMT; OR 3.67, 95% CI: 1.10-12.30; P=0.04), and stable/vulnerable carotid plaque (OR 3.39, 95% CI: 1.09-10.55; P=0.04; OR 3.21, 95% CI: 1.07-9.65; P=0.04). However, there were no significant differences between prediabetes and CAC or carotid arteriopathy.

In patients with chest pain and DM without cardiovascular disease (CVD), Lp(a) level was significantly associated with subclinical atherosclerosis and had a synergistic effect with DM. Notably, lower Lp(a) levels in patients with DM may lead to an additional subclinical atherosclerosis risk, whereas prediabetes does not show the same association. Therefore, these findings highlight the importance of formulating early preventive strategies for subclinical atherosclerosis based on Lp(a) levels and diabetic status.

Using a data-driven approach, six clusters with different risk profiles and burden of complications were recently identified in middle-aged people before the diagnosis of type 2 diabetes (T2D). We aimed to investigate whether these clusters could be generalised to older people and if subclinical inflammation was related to their cardiometabolic risk profiles.

We assigned 843 participants of the KORA F4 study aged 61-82 years without T2D to the six previously defined phenotype-based clusters. Based on 73 biomarkers of subclinical inflammation, we derived an inflammation-related score ("inflammatory load") using principal component analysis to assess subclinical inflammation. Risk factors, inflammatory load as well as prevalence and incidence of (pre)diabetes-related complications were compared between the clusters using pairwise comparisons and regression analyses.

Clusters 1 and 2 had the lowest cardiometabolic risk, whereas clusters 5 and 6 the highest. T2D risk was highest in clusters 3, 4, 5, and 6 compared with the low-risk cluster 2 (age- and sex-adjusted ORs between 3.6 and 34.0). In cross-sectional analyses, there were significant between-cluster differences in chronic kidney disease (CKD), distal sensorimotor polyneuropathy (DSPN) and cardiovascular disease (all p < 0.045). In prospective analyses (mean follow-up time 6.5-8.3 years), clusters differed significantly in CKD and DSPN incidence, but not in incident CVD or all-cause mortality. The inflammatory load was highest in the high-risk cluster 5 and lowest in cluster 2. Adjustment for the inflammatory load had only a minor impact on the aforementioned differences in outcomes between clusters.

Our findings extend the knowledge about the previously identified six phenotype-based clusters in older people without T2D. Differences between clusters were more pronounced for T2D risk than for prevalent or incident (pre)diabetes-related complications and absent for mortality. The high cardiometabolic risk corresponded to the high inflammatory load in cluster 5 but not to the lower inflammatory load of high-risk clusters 3 and 6.

Prediabetes is a highly prevalent and increasingly common condition affecting a significant proportion of the global population. The heterogeneous nature of prediabetes presents a challenge in identifying individuals who particularly benefit from lifestyle or other therapeutic interventions aiming at preventing type 2 diabetes (T2D) and associated comorbidities. The phenotypic characteristics of individuals at risk for diabetes are associated with both specific risk profiles for progression and a differential potential to facilitate prediabetes remission and reduce the risk of future T2D. This review examines the current definition and global prevalence of prediabetes and evaluates the potential of prediabetes remission to reduce the alarming increase in the global burden of T2D.

We aimed to investigate the value of the neutrophil-lymphocyte ratio (NLR) in predicting the all-cause and cardiovascular mortality risk of individuals with prediabetes.

A total of 11,504 prediabetic patients from the National Health and Nutrition Examination Survey (NHANES) 2003-2016 were included in the present study. Mortality and the underlying cause of death were ascertained by linkage to National Death Index records through December 31, 2019. Restricted cubic spline (RCS) analysis was conducted to visualize the association between the NLR and mortality risk. The optimal NLR cutoff value corresponding to the most significant correlation with survival outcomes was calculated by the maximally selected rank statistics method (MSRSM). Weighted multivariable Cox regression models and subgroup analyses were used to calculate HRs and 95% CIs for all-cause and cardiovascular mortality.

During a median follow-up of 101 months (interquartile range, 64.0-138.0 months), 1654 (14.38%) deaths were documented, including 422 (3.67%) and 1232 (10.71%) due to cardiovascular and non-cardiovascular events, respectively. RCS regression analysis indicated that the NLR was positively associated with all-cause and cardiovascular mortality. Individuals were divided into lower (≤2.94) and higher (>2.94) NLR groups using the MSRSM. In the multivariable-adjusted model, compared with the lower NLR group, the higher NLR group had a HR of 1.63 (95% CI, 1.38-1.93) and 2.19 (95% CI, 1.55-3.01) for all-cause and cardiovascular mortality, respectively.

The NLR was a valuable marker for predicting all-cause and cardiovascular mortality risk in prediabetic patients.

Prediabetes (HbA1c 39-47 mmol/mol [5.7-6.4%] or fasting glucose 5.6-6.9 mmol/l) is associated with elevated risks of microvascular and macrovascular complications. It is unknown to what extent these risks in prediabetes remain after accounting for progression to diabetes.

In 10,310 participants from the Atherosclerosis Risk in Communities (ARIC) Study (aged 46-70 years, ~55% women, ~20% Black adults) without diabetes at baseline (1990-1992), we used Cox regression to characterise age- and sex-adjusted associations of prediabetes with ~30 year incidence of complications (composite and separately), including atherosclerotic CVD (ASCVD), heart failure, chronic kidney disease (CKD) and all-cause mortality before and after accounting for intervening incidence of diabetes, modelled as a time-varying variable. We calculated the excess risk of complications in prediabetes remaining after accounting for progression to diabetes.

Of the 60% of adults with prediabetes at baseline, ~30% progressed to diabetes (median time to diabetes, 7 years). Over the maximum follow-up of ~30 years, there were 7069 events (1937 ASCVD, 2109 heart failure, 3288 CKD and 4785 deaths). Prediabetes was modestly associated with risk of any complication (HR 1.21 [95% CI 1.15, 1.27]) vs normoglycaemia. This association remained significant after accounting for progression to diabetes (HR 1.18 [95% CI 1.12, 1.24]) with 85% (95% CI 75, 94%) of the excess risk of any complication in prediabetes remaining. Results were similar for the individual complications.

Progression to diabetes explained less than one-quarter of the risks of clinical outcomes associated with prediabetes. Prediabetes contributes to the risk of clinical outcomes even without progression to diabetes.

Background and Objectives: Prediabetes is a medical disease characterized by elevated blood sugar levels that exceed normal levels but do not meet the criteria for a diagnosis of diabetes mellitus. This study aimed to assess the impact of structured exercise manual interventions on the biochemical markers of sedentary prediabetic patients over sixteen weeks. Materials and Methods: A sixteen-weeks randomized controlled trial was conducted to assess the impact of an exercise-based manual program on biochemical markers, such as HbA1c, insulin sensitivity measures, and lipid profiles, in sedentary individuals with prediabetes. The Riphah Rehabilitation Center in Lahore, Pakistan, was the site of the trial. In this investigation, 126 individuals with prediabetes were randomly assigned to three groups: control, unsupervised, and supervised. The RCT was completed by 36 participants in each group after a 16-weeks intervention in the supervised and unsupervised groups, as well as a follow-up in the control group. An activity-based exercise manual that included dietary guidelines, educational materials, and an exercise routine was followed by both the supervised and unsupervised groups. The exercise interventions included both aerobic and resistance components. Results: The results indicated that the supervised group exhibited a substantial increase in insulin sensitivity, lipid profiles, and glycemic control when contrasted with the unsupervised and control groups. Significant improvements were observed in key biochemical parameters, including fasting blood levels (supervised as compared to unsupervised and control, respectively, the mean difference was 12.82 mg/dL vs. 11.36 mg/dL vs. 0.09 mg/dL p > 0.001), HbA1c (supervised as compared to unsupervised and control groups, respectively, the mean difference was 0.67% vs. 0.69% vs. 0.13% p < 0.001), and lipid profile (triglycerides (mean difference 0.25 mmol/L, 0.08 mmol/L, 0.11 mmol/L p < 0.001); LDL (mean difference 19.31 mg/dL, 10.51 mg/dL, 2.49 mg/dL p < 0.001); HDL (mean difference -12.68 mg/dL, -8.03 mg/dL, -1.48 mg/dL p < 0.001)). In comparison to the unsupervised and control groups, the insulin sensitivity parameters also demonstrated a modest improvement in the supervised group. The supervised group exhibited the greatest benefits from exercise among the groups that received exercise interventions. Conclusions: The present investigation demonstrated the significance of including structured physical activity into the regular routine of individuals with prediabetes, to decelerate the advancement of prediabetes to type 2 diabetes mellitus (T2DM). The current study emphasizes the essential role of structured exercise routines in the control of prediabetes and suggests that monitoring enhances the adherence and effectiveness of lifestyle interventions.

Prediabetes, impacting a third of the adult Chinese population, is linked to a variety of detrimental health outcomes. However, scant research has delved into the factors that affect a regression from prediabetes to normal glucose regulation (NGR) in middle-aged and elderly Chinese adults.

We conducted a longitudinal analysis of 2,655 adults, aged 45 years and above, drawing data from wave 1 and wave 3 of the China Health and Retirement Longitudinal Study (CHARLS). We employed a stepwise logistic regression model to identify factors associated with the regression to NGR. Restricted Cubic Spline (RCS) analysis was used to evaluate the dose-response relationships between baseline fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c) levels and the likelihood of regression to NGR. Attribution fraction (AF) analysis was conducted to measure the impact of modifiable factors on the regression of prediabetes. We further examined how changes in these factors were associated with regression to NGR.

During the 4-year follow-up, 570 of 2,655 prediabetes participants regressed to NGR. The stepwise logistic regression model identified older age, female sex, abdominal obesity (OR 0.70, 95% CI 0.57-0.86), elevated LDL-C (OR 0.69, 95% CI 0.48-0.97), higher FPG (OR 0.68, 95% CI 0.52-0.90), and higher HbA1c (OR 0.23, 95% CI 0.18-0.30) as factors associated with regression to NGR. AF analysis showed that a lower initial HbA1c was the most influential factor for regression to NGR. Additionally, evaluated blood lipid profiles reduced the odds of regression to NGR.

This study underscores the influence of age, gender, abdominal obesity, LDL-C levels, FPG, HbA1c, and blood lipid profiles on the likelihood of regressing from prediabetes to NGR. It suggests that adopting a healthy lifestyle and preemptively mitigating these risks may be more beneficial than addressing them after they have been identified in clinical settings.

To investigate the modifying role of obesity in the association between abnormal glucose metabolism and atrial fibrillation (AF) risk in older individuals.

From April 2007 to November 2011, 11,663 participants aged ≥60 years were enrolled in the Shandong area. Glucose metabolic status was determined using fasting plasma glucose and hemoglobin A1c levels, and obesity was determined using body mass index (BMI), waist-to-hip ratio (WHR), and visceral fat area (VFA). Obesity-associated metabolic activities were assessed using the adiponectin-to-leptin ratio (ALR), galectin-3, and triglyceride-glucose index (TyG). New-onset AF was diagnosed by ICD-10.

During an average of 11.1 years of follow-up, 1343 participants developed AF. AF risks were higher in those with prediabetes, uncontrolled diabetes, and well-controlled diabetes than with normoglycemia. The hazard ratios were decreased by 14.79%, 40.29%, and 25.23% in those with prediabetes; 31.44%, 53.56%, and 41.90% in those with uncontrolled diabetes; and 21.16%, 42.38%, and 27.59% in those with well-controlled diabetes after adjusting for BMI, WHR, and VFA, respectively. The population-attributable risk percentages of general obesity, central obesity, and high VFA for new-onset AF were 10.43%, 34.78%, and 31.30%, respectively. ALR, galectin-3, and TyG significantly mediated the association of BMI, WHR, and VFA with AF risk (all Padj. < 0.001).

Obesity mediates the association between abnormal glucose metabolism and AF risk in older individuals. WHR is a more effective modifier than BMI and VFA for moderating the association. ALR, TyG, and galectin-3 mediate the moderating effect of obesity on the association between abnormal glucose metabolism and AF risk.

Immunotherapy has transformed current cancer management, and it has achieved significant progress over last decades. However, an immunosuppressive tumor microenvironment (TME) diminishes the effectiveness of immunotherapy by suppressing the activity of immune cells and facilitating tumor immune-evasion. Adenosine monophosphate-activated protein kinase (AMPK), a key modulator of cellular energy metabolism and homeostasis, has gained growing attention in anti-tumor immunity. Metformin is usually considered as a cornerstone in diabetes management, and its role in activating the AMPK pathway has also been extensively explored in cancer therapy although the findings on its role remain inconsistent. Metformin in a nanomedicine formulation has been found to hold potential in reprogramming the immunosuppressive TME through immunometabolic modulation of both tumor and immune cells. This review elaborates the foundation and progress of immunometabolic reprogramming of the TME via metformin-based nanomedicines, offering valuable insights for the next generation of cancer therapy.

Pancreatic cancer and prediabetes pose significant public health challenges. Given the lack of strong evidence we performed a meta-analysis to assess the risk of pancreatic cancer in prediabetes.

We performed a thorough search of the major databases over the last 10 years to identify relevant articles. The pooled odds ratio (OR) and hazard ratio (HR) were combined to calculate the effect size (ES).

We analyzed 5 studies including 5,425,111 prediabetic individuals and 16,096,467 normoglycemic population across 5 countries with a median follow-up of 8.5 years. We identified a noteworthy association between prediabetes and pancreatic cancer, reporting an unadjusted ES of 1.36 (95% confidence interval [CI] 1.05-1.77, P = 0.02) and an adjusted ES of 1.40 (1.23-1.59, P < 0.01). Subgroup analyses by age revealed variations in risk, with studies involving participants aged 60 and above exhibiting a higher ES (ES 1.83, 95% CI 1.28-2.62, P < 0.01). Geographical differences were also observed, with Japanese studies reporting a higher risk (ES 1.89, 95% CI 1.15-3.10, P < 0.01) compared with those from the United States (ES 1.32, 95% CI 1.13-1.53, P < 0.01).

We identified 40% higher risk of pancreatic cancer in patients with prediabetes than those with normal blood glucose necessitating urgent attention for further research and policy change.

Obesity and prediabetes affect a substantial part of the general population, but are largely underdiagnosed, underestimated, and undertreated. Prediabetes differs from diabetes only in the degree of hyperglycaemia consequent to the progressive decline in residual beta-cell function. Both prediabetes and diabetes occur as a consequence of insulin resistance that starts several years before the clinical onset of overt diabetes. Macrovascular complications in patients with diabetes are mainly caused by insulin resistance. This is why in prediabetes, the overall cardiovascular risk is, by all means, similar to that in patients with diabetes. It is important, therefore, to identify prediabetes and treat patients not only to prevent or delay the onset of diabetes, but to reduce the cardiovascular risk associated with prediabetes. This review provides an overview of the pathophysiology of prediabetes in patients with obesity and the progression toward overt diabetes. We have reviewed nutritional and pharmacological approaches to the management of obesity and reduced glucose tolerance, and the treatment of the major comorbidities in these patients, including hypertension, dyslipidaemia, and Metabolic dysfunction-associated Steatotic Liver Disease (MASLD), has also been reviewed. In patients with obesity and prediabetes, the nutritional approach is similar to that adopted for patients with obesity and diabetes; treatments of dyslipidaemia and hypertension also have the same targets compared to patients with diabetes. MASLD is a critical issue in these patients; in the prediabetic state, MASLD rarely progresses into fibrosis. This highlights the importance of the early recognition of this pathological condition before patients become diabetic when the risk of fibrosis is much higher. It is necessary to raise awareness of the clinical relevance of this pathological condition in order to prompt early intervention before complications occur. The single most important therapeutic goal is weight loss, which must be early and persistent.

Both air pollution and diabetes are key urban challenges. The association between particulate matter with a diameter of <2.5 μm (PM2.5) exposure and prediabetes/diabetes in adults is well documented, but the health effects of life course exposure remain unclear. This study evaluated the impact of PM2.5 exposure throughout various life stages on the prevalence of prediabetes/diabetes in adulthood.

We included 4,551 individuals with 19,593 medical visits from two open cohorts in Taiwan and Hong Kong between 2000 and 2018. Ambient PM2.5 exposure was assessed using a satellite-based model, delivering a 2-year average exposure at a resolution of 1 km2. Logistic mixed-effects models were used to investigate longitudinal associations between PM2.5 exposure and the prevalence of prediabetes/diabetes. Life course models were used to examine the impact of PM2.5 exposure at different life stages on prediabetes/diabetes in adulthood.

Over an average follow-up period of 9.93 years, 1,660 individuals with prediabetes/diabetes were observed. For the longitudinal association, every 10 μg/m3 increase in PM2.5 was associated with an increased odds of having prediabetes/diabetes (odds ratio 1.32, 95% CI 1.13, 1.54). The odds of adulthood prediabetes/diabetes increased by 15%, 18%, and 29% for each 10 μg/m3 increase in PM2.5 exposure during school age, adolescence, and adulthood, respectively.

Our findings suggest a link between PM2.5 exposure during each life stage and the prevalence of prediabetes/diabetes in adulthood, with the health impacts of exposure during adulthood being slightly greater. This study underscores the need for life course air pollution control strategies to mitigate the substantial disease burden of diabetes.

To explore the effects of lifestyle interventions on the prevention of type 2 diabetes (T2D) and reversion to normoglycemia by prediabetes phenotype.

We searched MEDLINE, Embase, and the Cochrane Library for randomized controlled trials (RCTs) that evaluated the effects of lifestyle interventions in adults with prediabetes for a minimum duration of one year. Two reviewers independently screened articles, extracted data, and performed quality assessment. The relative effects were analyzed using a random-effects model, subgroup analysis was employed to explore the potential effects among subpopulations.

A total of 31 RCTs involving 23684 participants were analyzed. Compared with usual care, lifestyle interventions reduced the incident T2D by 41 % (RR 0.59 [95 % CI 0.52-0.68]) and increased the probability of reverting to normoglycemia by 44 % (RR 1.44 [95 % CI 1.15-1.81]) in adults with prediabetes. No significant difference was observed between the impaired fasting glucose (IFG5.6)/impaired glucose tolerance (IGT) and IFG6.1/IGT (P = 0.752). IGT + IFG benefited more than isolated IGT in prevention of T2D (RRIGT + IFG 0.47 [95 % CI 0.41-0.55]; RRisolatedIGT 0.77 [95 % CI 0.64-0.93]), whereas no benefit was found in isolated IFG (RR 0.77 [95 % CI 0.51-1.16]) or elevated HbA1c (RR 0.89 [95 % CI 0.74-1.07]).

Lifestyle intervention could help prevent T2D and revert to normoglycemia in adults with prediabetes, with significant benefit in people with IGT but not in those with isolated IFG or elevated HbA1c.

This study aimed to examine the risk of common diseases among people with pre-diabetes and explored the relationship between pre-diabetes and multimorbidity (in this case, two or more comorbid diseases).

An observational multicohort study using data from the UK Biobank database and the National Inpatient Sample (NIS) database (2016-2018) was conducted. We analysed 461 535 participants and 17 548 442 patients aged 18 years or older from both databases, of whom 14.0% and 0.7% were diagnosed with pre-diabetes, respectively. A total of 76 common diseases of various body systems were selected as adverse health outcomes for analysis.

Among 64 523 individuals with pre-diabetes in the UK Biobank, the mean age was 60 years, 35 304 (54.7%) were female. There were 24 non-overlapping diseases associated with pre-diabetes with significant multiple test results in both databases, and most of them are circulatory system diseases. Compared with normoglycaemia, the confounder-adjusted HR in the UK Biobank for pre-diabetes was 1.46 (95% CI 1.43 to 1.49) for accompanying complex multimorbidity (ie, four or more pre-diabetes-related diseases), the corresponding confounder-adjusted OR in the NIS study was 10.03 (95% CI 9.66 to 10.40).

Pre-diabetes was associated with a significantly higher risk of multimorbidity. Pre-diabetes, thus, might represent an important target for multimorbidity prevention, and stronger emphasis on its management seems necessary to reduce the risk of the development of multiple comorbidities, especially before the onset of overt diabetes.

Recently, International Diabetes Federation position statement has adopted one-hour post-load glucose (1hPG) ≥ 8.6 mmol/L for diagnosing intermediate hyperglycemia. We aimed to assess the association of 1hPG ≥ 8.6 mmol/L with metabolic syndrome (MetS) and its components, as well as interaction between sex and 1hPG ≥ 8.6 mmol/L on MetS and its components in Chinese people at high risk of diabetes.

The cross-sectional study was conducted in DaQing city of HeiLongJiang Province, China between August, 2023 and January, 2024. Eligible individuals with fasting glucose of 5.6-6.9 mmol/L and age of 25-55 years in health checkup data in the year of 2023 or with at least one risk factor of diabetes were invited to receive the oral glucose tolerance test and biochemical examinations. Individuals with self-reported presence of diabetes or usage of glucose-lowering medication were excluded. MetS was defined as presence of at least three of the five components according to the Chinese Diabetes Society criteria. Logistic regression was performed to evaluate the association of 1hPG ≥ 8.6 mmol/L with MetS and its components. Additive interaction was estimated using the relative excess risk due to interaction, attributable proportion due to interaction (AP), and synergy index.

A total of 2419 subjects comprising 1465 men (60.6%) with a mean age of 45.77 ± 6.20 years were included, and the prevalence of MetS was 46.8%, with 59.7% in men and 27.1% in women. 1hPG ≥ 8.6 mmol/L was associated with MetS (aOR = 4.40, 95% CI 3.26-6.01), elevated blood pressure (aOR = 1.46, 95% CI 1.13-1.89), hyperglycemia (aOR = 15.46, 95% CI 11.56-20.98), and reduced HDL-C (aOR = 1.51, 95% CI 1.07-2.15) in the overall population, whereas no significant association between 1hPG ≥ 8.6 mmol/L and elevated blood pressure in men (aOR = 1.36, 95% CI 0.97-1.91) or dyslipidemia in women (elevated TG: aOR = 0.81, 95% CI 0.47-1.39; reduced HDL-C: aOR = 1.08, 95% CI 0.49-2.37). Additive interaction effect between sex and 1hPG ≥ 8.6 mmol/L on MetS was observed, with 31% attributed to the interaction effect between men and 1hPG ≥ 8.6 mmol/L (AP = 0.31, 95% CI 0.06-0.49).

There was an additive interaction effect between sex and 1hPG on MetS among Chinese people at high risk of diabetes. 1hPG test and sex-specific strategies should be taken into consideration in cardiometabolic disorder identification and management.

Prediabetes is the first stage of a continuum that extends through the diagnosis of clinical type 2 diabetes towards long-standing diabetes with multiple comorbidities. The diagnosis of prediabetes provides an opportunity to interrupt the diabetes continuum at an early stage to ensure long-term optimization of clinical outcomes. All people with prediabetes should receive intervention to improve their lifestyles (quality of diet and level of physical activity), as this has been proven beyond doubt to reduce substantially the risk of conversion to diabetes. Additionally, a large base of clinical evidence supports the use of metformin in preventing or delaying the transition from prediabetes to clinical type 2 diabetes, for some people with prediabetes. For many years, guidelines for the management of type 2 diabetes focused on lowering blood glucose, with metformin prescribed first for those without contraindications. More recently, guidelines have shifted towards prevention of diabetes complications as the primary goal, with increased use of GLP-1 receptor agonists (or multi-agonist incretin peptides) or SGLT-2 inhibitors for patients with existing atherosclerotic cardiovascular disease, heart failure or chronic kidney disease. Access to these medications often remains challenging. Metformin remains a suitable option for initial pharmacologic intervention to manage glycemia for many people with prediabetes or type 2 diabetes along with other therapy to maintain control of blood glucose or to address specific comorbidities as the patient progresses along the diabetes continuum.

The serum uric acid (UA) to high-density lipoprotein cholesterol (HDL-C) ratio (UHR) is a novel biomarker that indicates inflammation and metabolic disorders. Also, it has been shown that UHR correlates with the risk of cardiovascular disease. Despite this, limited research exists on its prognostic significance. This study aimed to explore the association of UHR with all-cause and cardiovascular mortality in patients with diabetes or prediabetes.

This cohort study included 18,804 participants from the National Health and Nutrition Examination Survey (NHANES) 2005-2018 with diabetes or prediabetes aged 20 years or older, followed until December 31, 2019. Patients with diabetes or prediabetes were grouped according to quartiles of UHR, which was calculated as serum UA (mg/dL)/HDL-C (mg/dL). Kaplan-Meier survival analysis, multivariable Cox proportional hazards regression models, restricted cubic spline analysis, and threshold effects were performed to assess the association between baseline UHR and all-cause and cardiovascular mortality. Subgroup analysis and sensitivity analysis were also conducted.

During a median follow-up of 80 months, a total of 2,748 (14.61%) deaths occurred, including 869 (4.63%) cardiovascular deaths. Kaplan-Meier survival analysis revealed that the highest quartile of UHR had the highest mortality rates. Multivariable Cox regression analysis indicated that individuals in the highest quartile of UHR had a significantly higher risk of all-cause mortality (HR: 1.24, 95% CI: 1.07-1.45) and cardiovascular mortality (HR: 1.56, 95% CI: 1.19-2.04) compared to those in the second quartile. A J-shaped association between UHR and both all-cause and cardiovascular mortality was observed, with threshold points of 13.73% and 9.39%, respectively. Specifically, when UHR was above the respective thresholds, the HRs of a 10% increment of UHR for all-cause mortality and cardiovascular mortality were 1.45 (95% CI: 1.31-1.61) and 1.38 (95% CI: 1.20-1.60). However, UHR below the threshold did not significantly correlate with mortality. Furthermore, subgroup analyses showed that the correlation of UHR with all-cause mortality was significantly modified by sex and age, with a persistent positive correlation observed in women and those aged < 60.

Higher UHR was correlated with increased all-cause and cardiovascular mortality in patients with diabetes or prediabetes.