Urinary non-albumin protein-creatinine ratio is an independent predictor of mortality in patients with type 2 diabetes: a retrospective cohort study.

Albuminuria is a well-known predictor of chronic kidney disease in patients with type 2 diabetes mellitus (DM). However, proteinuria is associated with chronic complications in patients without albuminuria. In this retrospective cohort study, we explored whether non-albumin proteinuria is associated with all-cause mortality and compared the effects of non-albumin proteinuria on all-cause mortality between patients with and without albuminuria. We retrospectively collected data from patients with type 2 DM for whom we had obtained measurements of both urinary albumin-to-creatinine ratio (UACR) and urinary protein-to-creatinine ratio (UPCR) from the same spot urine specimen. Urinary non-albumin protein-creatinine ratio (UNAPCR) was defined as UPCR-UACR. Of the 1809 enrolled subjects, 695 (38.4%) patients died over a median follow-up of 6.4 years. The cohort was separated into four subgroups according to UACR (30 mg/g) and UNAPCR (120 mg/g) to examine whether these indices are associated with all-cause mortality. Compared with the low UACR and low UNAPCR subgroup as the reference group, multivariable Cox regression analyses indicated no significant difference in mortality in the high UACR and low UNAPCR subgroup (hazard ratio [HR] 1.189, 95% confidence interval [CI] 0.889-1.589, P = 0.243), but mortality risks were significantly higher in the low UACR and high UNAPCR subgroup (HR 2.204, 95% CI 1.448-3.356, P < 0.001) and in the high UACR with high UNAPCR subgroup (HR 1.796, 95% CI 1.451-2.221, P < 0.001). In the multivariable Cox regression model with inclusion of both UACR and UNAPCR, UNAPCR ≥ 120 mg/g was significantly associated with an increased mortality risk (HR 1.655, 95% CI 1.324-2.070, P < 0.001), but UACR ≥ 30 mg/g was not significantly associated with mortality risk (HR 1.046, 95% CI 0.820-1.334, P = 0.717). In conclusion, UNAPCR is an independent predictor of all-cause mortality in patients with type 2 DM.

Contributions of elevated CRP, hyperglycaemia, and type 2 diabetes to cardiovascular risk in the general population: observational and Mendelian randomization studies.

OBJECTIVE: To investigate the contributions of low-grade inflammation measured by C-reactive protein (CRP), hyperglycaemia, and type 2 diabetes to risk of ischemic heart disease (IHD) and cardiovascular disease (CVD) death in the general population, and whether hyperglycaemia and high CRP are causally related. RESEARCH DESIGN AND METHODS: Observational and bidirectional, one-sample Mendelian randomization (MR) analyses in 112,815 individuals from the Copenhagen General Population Study and the Copenhagen City Heart Study, and bidirectional, two-sample MR with summary level data from two publicly available consortia, CHARGE and MAGIC. RESULTS: Observationally, higher plasma CRP was associated with stepwise higher risk of IHD and CVD death, with hazard ratios and 95% confidence intervals (95%CI) of 1.50 (1.38, 1.62) and 2.44 (1.93, 3.10) in individuals with the 20% highest CRP concentrations. The corresponding hazard ratios for elevated plasma glucose were 1.10 (1.02, 1.18) and 1.22 (1.01, 1.49), respectively. Cumulative incidences of IHD and CVD death were 365% and 592% higher, respectively, in individuals with both type 2 diabetes and plasma CRP ≥ 2 mg/L compared to individuals without either. Plasma CRP and glucose were observationally associated (ß-coefficient: 0.02 (0.02, 0.03), p = 3 × 10- 20); however, one- and two-sample MR did not support a causal effect of CRP on glucose (-0.04 (-0.12, 0.32) and - 0.03 (-0.13, 0.06)), nor of glucose on CRP (-0.01 (-0.08, 0.07) and - 0.00 (-0.14, 0.13)). CONCLUSIONS: Elevated concentrations of plasma CRP and glucose are predictors of IHD and CVD death in the general population. We found no genetic association between CRP and glucose, or vice versa, suggesting that lowering glucose pharmacologically does not have a direct effect on low-grade inflammation.

Physical performance strongly predicts all-cause mortality risk in a real-world population of older diabetic patients: machine learning approach for mortality risk stratification.

Background: Prognostic risk stratification in older adults with type 2 diabetes (T2D) is important for guiding decisions concerning advance care planning. Materials and methods: A retrospective longitudinal study was conducted in a real-world sample of older diabetic patients afferent to the outpatient facilities of the Diabetology Unit of the IRCCS INRCA Hospital of Ancona (Italy). A total of 1,001 T2D patients aged more than 70 years were consecutively evaluated by a multidimensional geriatric assessment, including physical performance evaluated using the Short Physical Performance Battery (SPPB). The mortality was assessed during a 5-year follow-up. We used the automatic machine-learning (AutoML) JADBio platform to identify parsimonious mathematical models for risk stratification. Results: Of 977 subjects included in the T2D cohort, the mean age was 76.5 (SD: 4.5) years and 454 (46.5%) were men. The mean follow-up time was 53.3 (SD:15.8) months, and 209 (21.4%) patients died by the end of the follow-up. The JADBio AutoML final model included age, sex, SPPB, chronic kidney disease, myocardial ischemia, peripheral artery disease, neuropathy, and myocardial infarction. The bootstrap-corrected concordance index (c-index) for the final model was 0.726 (95% CI: 0.687-0.763) with SPPB ranked as the most important predictor. Based on the penalized Cox regression model, the risk of death per unit of time for a subject with an SPPB score lower than five points was 3.35 times that for a subject with a score higher than eight points (P-value <0.001). Conclusion: Assessment of physical performance needs to be implemented in clinical practice for risk stratification of T2D older patients.

Diabetes-related risk factors and survival among individuals with type 2 diabetes and breast, lung, colorectal, or prostate cancer.

Premature death in diabetes is increasingly caused by cancer. The objectives were to estimate the excess mortality when individuals with type 2 diabetes(T2D) were diagnosed with cancer, and to examine the impact of modifiable diabetes-related risk factors. This longitudinal nationwide cohort study included individuals with T2D registered in the Swedish National Diabetes Register between 1998-2019. Poisson models were used to estimate mortality as a function of time-updated risk-factors, adjusted for sex, age, diabetes duration, marital status, country of birth, BMI, blood pressure, lipids, albuminuria, smoking, and physical activity. We included 690,539 individuals with T2D and during 4,787,326 person-years of follow-up 179,627 individuals died. Overall, the all-cause mortality rate ratio was 3.75 [95%confidence interval(CI):3.69-3.81] for individuals with T2D and cancer compared to those remaining free of cancer. The most marked risk factors associated to mortality among individuals with T2D and cancer were low physical activity, 1.59 (1.57-1.61) and smoking, 2.15 (2.08-2.22), whereas HbA1c, lipids, hypertension, and BMI had no/weak associations with survival. In a future with more patients with comorbid T2D and cancer diagnoses, these results suggest that smoking and physical activity might be the two most salient modifiable risk factors for mortality in people with type 2 diabetes and cancer.

Safety and Efficacy of Early SGLT2 Inhibitors Initiation in Diabetic Patients Following Acute Myocardial Infarction, a Retrospective Study.

INTRODUCTION: Sodium-glucose cotransporter- 2 (SGLT2) inhibitors have become a cornerstone in heart failure (HF), Type 2 diabetes mellitus (T2DM), and cardiovascular disease (CVD) management. In the current retrospective study, we aimed to assess efficacy and safety of SGLT2 inhibitors early following acute myocardial infarction (AMI). METHODS: Patients with T2DM hospitalized for AMI in 2017-2020 were divided according to SGLT2 inhibitors therapy status on discharge (with vs without therapy). Primary outcome was defined as a composite of hospitalizations for HF, recurrent AMI, and cerebrovascular accident (CVA). Secondary outcomes included hospitalizations for any cause, total cumulative number of hospitalizations, and all-cause mortality. RESULTS: A total of 69 patients (mean age 59.2 ± 8.2 years) with AMI discharged with SGLT2 inhibitors were compared to 253 patients (mean age 62.5 ± 9.8) with no SGLT2 inhibitors. During the first year post-AMI, 4 (5.8%) patients in the treatment group and 16 (6.3%) in the control group were hospitalized for CV events (p = 1.0). Patients in the SGLT2 inhibitors group had lower rates of hospitalization for any cause (31.9% vs 47.8%, P = 0.02), with no change in mortality (0% vs 3.6%, P = 0.21). After multivariate regression analysis, only female gender was associated with increased risk for readmission, mainly due to urinary tract infections. No events of diabetic ketoacidosis (DKA) or limb amputation were reported. CONCLUSIONS: We found that early initiation of SGLT2 inhibitors in T2DM patients following AMI is safe and decreases the risk of hospitalization for any cause.

Pre-hospital glycemia as a biomarker for in-hospital all-cause mortality in diabetic patients - a pilot study.

BACKGROUND: Type 2 Diabetes Mellitus (T2DM) presents a significant healthcare challenge, with considerable economic ramifications. While blood glucose management and long-term metabolic target setting for home care and outpatient treatment follow established procedures, the approach for short-term targets during hospitalization varies due to a lack of clinical consensus. Our study aims to elucidate the impact of pre-hospitalization and intra-hospitalization glycemic indexes on in-hospital survival rates in individuals with T2DM, addressing this notable gap in the current literature. METHODS: In this pilot study involving 120 hospitalized diabetic patients, we used advanced machine learning and classical statistical methods to identify variables for predicting hospitalization outcomes. We first developed a 30-day mortality risk classifier leveraging AdaBoost-FAS, a state-of-the-art ensemble machine learning method for tabular data. We then analyzed the feature relevance to identify the key predictive variables among the glycemic and routine clinical variables the model bases its predictions on. Next, we conducted detailed statistical analyses to shed light on the relationship between such variables and mortality risk. Finally, based on such analyses, we introduced a novel index, the ratio of intra-hospital glycemic variability to pre-hospitalization glycemic mean, to better characterize and stratify the diabetic population. RESULTS: Our findings underscore the importance of personalized approaches to glycemic management during hospitalization. The introduced index, alongside advanced predictive modeling, provides valuable insights for optimizing patient care. In particular, together with in-hospital glycemic variability, it is able to discriminate between patients with higher and lower mortality rates, highlighting the importance of tightly controlling not only pre-hospital but also in-hospital glycemic levels. CONCLUSIONS: Despite the pilot nature and modest sample size, this study marks the beginning of exploration into personalized glycemic control for hospitalized patients with T2DM. Pre-hospital blood glucose levels and related variables derived from it can serve as biomarkers for all-cause mortality during hospitalization.

[Association between obesity and risk for all-cause mortality in patients with type 2 diabetes].

Objective: To investigate the association between obesity and the risk for all-cause mortality in type 2 diabetes (T2DM) patients. Methods: The participants were from a rural community-based T2DM patient cohort in Zhejiang Province. The study used the data collected from baseline survey in 2016 and follow-up until December 31, 2021. A total of 10 310 participants were included, excluding those who were lost in follow-up or had incomplete data in follow-up. According to BMI and waist circumference, the study subjects were divided into 6 groups: low body weight, normal body weight, simple abdominal obesity, simple body obesity, complex overweight and complex obesity. Cox proportional hazards regression model was used to analyze hazard ratios (HRs) of all-cause mortality and their 95%CIs in T2DM patients with different obesity status. Results: The cumulative follow-up period was 57 049.47 person-years with an average follow-up of (5.53±0.89) person-years. During this period, 971 subjects died. The death density was 1 702.03/100 000 person-years. After adjusting for confounders, low-weight patients had a 104% increased risk for all-cause death compared with normal-weight patients (HR=2.04, 95%CI:1.42-2.92). The risk for all-cause death decreased by 34% (HR=0.66, 95%CI: 0.53-0.82), 22% (HR=0.78,95%CI: 0.66-0.92), 38% (HR=0.62, 95%CI: 0.49-0.78) in the patients with simple body obesity, complex overweight and complex obesity, respectively, there was no significant difference for all-cause death in the patients with simple abdominal obesity alone. In subgroup analysis, the risk of all-cause mortality increased in low-weight T2DM patients of different sexes and ages, the mortality risk in women with complex obesity was 50% lower than that in the women with normal body weight, but there was no significant difference in men in the comparison between complex obesity group and normal body weight group. The risk for all-cause mortality was significantly lower in ≥65 years old patients with simple body obesity, complex overweight and complex obesity than in patients with normal body weight (HR=0.61, 95%CI: 0.48-0.78; HR=0.76, 95%CI: 0.63-0.91; HR=0.56,95%CI: 0.42-0.73), there was no significant difference in the patients aged <65 years. There was no significant change in sensitivity analysis. Conclusions: There was an "obesity paradox" in the risk for all-cause mortality in T2DM patients. The risk of all-cause mortality in the low-weight patients was significantly higher than that in normal-weight patients, and the risk for death in the patients with simple body obesity or complex overweight and obesity were significantly lower.

Gamma-glutamyl transferase and the risk of all-cause and disease-specific mortality in patients with diabetes: A nationwide cohort study.

BACKGROUND: There exists a paucity of data regarding whether gamma-glutamyl transferase is associated with disease-specific mortality in patients with type 2 diabetes mellitus. This study aimed to investigate the association of serum gamma-glutamyl transferase levels with all-cause and disease-specific mortality in patients with diabetes mellitus using a Korean nationwide health-screening database. METHODS: A total of 9 687 066 patients without viral hepatitis or liver cirrhosis who underwent health examination in 2009 were included. These patients were divided into four groups according to sex-specific quartiles of serum gamma-glutamyl transferase levels. RESULTS: During a median follow-up period of 8.1 years, 222 242 deaths were identified. The all-cause mortality rate increased as the serum gamma-glutamyl transferase levels became higher (highest quartile vs lowest quartile: hazard ratio [HR], 1.57; 95% confidence interval [CI], 1.55-1.59; p for trend <.001). Similar trends were observed for cardiovascular disease (HR, 1.57; 95% CI, 1.53-1.62), ischemic heart disease (HR, 1.40; 95% CI, 1.33-1.48), and stroke (HR, 1.72; 95% CI, 1.60-1.85) in the highest quartile, as compared with the lowest quartile (p for trend <.001). As the gamma-glutamyl transferase quartiles became higher, mortality rates related to cancer (HR, 1.56; 95% CI, 1.52-1.60), liver disease (HR, 9.42; 95% CI, 8.81-10.07), respiratory disease (HR, 1.55; 95% CI, 1.49-1.62), and infectious disease (HR, 1.73; 95% CI, 1.59-1.87) also increased in the highest quartile, compared with the lowest quartile (p for trend <.001). CONCLUSIONS: Serum gamma-glutamyl transferase levels may be useful for the risk assessment of all-cause and disease-specific mortality among patients with type 2 diabetes mellitus.

The impact of pre-stroke metformin use on clinical outcomes after acute ischemic stroke: A systematic review and meta-analysis.

OBJECTIVES: Stroke is a leading cause of mortality and disability globally, with limited treatment options available for acute ischemic stroke (AIS) patients. Type 2 diabetes mellitus (T2DM) is not only widespread but also a known risk factor for stroke. Our meta-analysis aims to assess the influence of pre-stroke metformin use on the clinical outcomes in AIS patients with T2DM. MATERIALS AND METHODS: We conducted this study following PRISMA guidelines, searching the following databases: Medline, Embase, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials up to February 29, 2024. All studies providing separate data on AIS patients using metformin were included, and statistical analysis was conducted using R software to pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CI). RESULTS: Out of 1051 studies, 7 met the inclusion criteria for our meta-analysis with a total of 11589 diabetic patients, including 5445 patients taking metformin and 6144 diabetic patients in the non-metformin group. Compared to the non-metformin group, the metformin group had a significantly higher rate of mRS 0-2 score at discharge (OR 1.56; 95% CI 1.25:1.95; p=< 0.01) and a lower rate of 90-day mortality (OR 0.51; 95% CI 0.42:0.61; p=< 0.01), with no significant difference in sICH (OR 0.88; 95% CI 0.47:1.64; p= 0.68) between the two groups. CONCLUSIONS: Our meta-analysis demonstrated that pre-stroke metformin use is associated with higher functional independence and lower mortality in AIS patients with T2DM.

The prognostic impact of insulin resistance surrogates in patients with acute myocardial infarction with and without type 2 diabetes.

BACKGROUND: Cardiovascular disease is the major cause of morbidity and mortality, particularly in type 2 diabetes mellitus (T2DM). Novel markers of insulin resistance and progression of atherosclerosis include the triglycerides and glucose index (TyG index), the triglycerides and body mass index (Tyg-BMI) and the metabolic score for insulin resistance (METS-IR). Establishing independent risk factors for in-hospital death and major adverse cardiac and cerebrovascular events (MACCE) in patients with myocardial infarction (MI) remains critical. The aim of the study was to assess the risk of in-hospital death and MACCE within 12 months after ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) in patients with and without T2DM based on TyG index, Tyg-BMI and METS-IR. METHODS: Retrospective analysis included 1706 patients with STEMI and NSTEMI hospitalized between 2013 and 2021. We analyzed prognostic value of TyG index, Tyg-BMI and METS-IR for in-hospital death and MACCE as its components (death from any cause, MI, stroke, revascularization) within 12 months after STEMI or NSTEMI in patients with and without T2DM. RESULTS: Of 1706 patients, 58 in-hospital deaths were reported (29 patients [4.3%] in the group with T2DM and 29 patients [2.8%] in the group without T2DM; p = 0.1). MACCE occurred in 18.9% of the total study population (25.8% in the group with T2DM and 14.4% in the group without T2DM; p < 0.001). TyG index, Tyg-BMI and METS-IR were significantly higher in the group of patients with T2DM compared to those without T2DM (p < 0.001). Long-term MACCE were more prevalent in patients with T2DM (p < 0.001). The area under the ROC curve (AUC-ROC) for the prediction of in-hospital death and the TyG index was 0.69 (p < 0.001). The ROC curve for predicting in-hospital death based on METS-IR was 0.682 (p < 0.001). The AUC-ROC values for MACCE prediction based on the TyG index and METS-IR were 0.582 (p < 0.001) and 0.57 (p < 0.001), respectively. CONCLUSIONS: TyG index was an independent risk factor for in-hospital death in patients with STEMI or NSTEMI. TyG index, TyG-BMI and METS-IR were not independent risk factors for MACCE at 12 month follow-up. TyG index and METS-IR have low predictive value in predicting MACCE within 12 months after STEMI and NSTEMI.

SGLT2 inhibitors: from glucose-lowering to cardiovascular benefits.

An increasing number of individuals are at high risk of type 2 diabetes (T2D) and its cardiovascular complications, including heart failure (HF), chronic kidney disease (CKD), and eventually premature death. The sodium-glucose co-transporter-2 (SGLT2) protein sits in the proximal tubule of human nephrons to regulate glucose reabsorption and its inhibition by gliflozins represents the cornerstone of contemporary T2D and HF management. Herein, we aim to provide an updated overview of the pleiotropy of gliflozins, provide mechanistic insights and delineate related cardiovascular (CV) benefits. By discussing contemporary evidence obtained in preclinical models and landmark randomized controlled trials, we move from bench to bedside across the broad spectrum of cardio- and cerebrovascular diseases. With landmark randomized controlled trials confirming a reduction in major adverse CV events (MACE; composite endpoint of CV death, non-fatal myocardial infarction, and non-fatal stroke), SGLT2 inhibitors strongly mitigate the risk for heart failure hospitalization in diabetics and non-diabetics alike while conferring renoprotection in specific patient populations. Along four major pathophysiological axes (i.e. at systemic, vascular, cardiac, and renal levels), we provide insights into the key mechanisms that may underlie their beneficial effects, including gliflozins' role in the modulation of inflammation, oxidative stress, cellular energy metabolism, and housekeeping mechanisms. We also discuss how this drug class controls hyperglycaemia, ketogenesis, natriuresis, and hyperuricaemia, collectively contributing to their pleiotropic effects. Finally, evolving data in the setting of cerebrovascular diseases and arrhythmias are presented and potential implications for future research and clinical practice are comprehensively reviewed.

Serum T50 predicts cardiovascular mortality in individuals with type 2 diabetes: A prospective cohort study.

BACKGROUND AND AIMS: Individuals with type 2 diabetes (T2D) have a higher risk of cardiovascular disease, compared with those without T2D. The serum T50 test captures the transformation time of calciprotein particles in serum. We aimed to assess whether serum T50 predicts cardiovascular mortality in T2D patients, independent of traditional risk factors. METHODS: We analyzed 621 individuals with T2D in this prospective cohort study. Cox regression models were performed to test the association between serum T50 and cardiovascular and all-cause mortality. Causes of death were categorized according to ICD-10 codes. Risk prediction improvement was assessed by comparing Harrell's C for models without and with T50. RESULTS: The mean age was 64.2 ± 9.8 years, and 61% were male. The average serum T50 time was 323 ± 63 min. Higher age, alcohol use, high-sensitive C-reactive protein, and plasma phosphate were associated with lower serum T50 levels. Higher plasma triglycerides, venous bicarbonate, sodium, magnesium, and alanine aminotransferase were associated with higher serum T50 levels. After a follow-up of 7.5[5.4-10.7] years, each 60 min decrease in serum T50 was associated with an increased risk of cardiovascular (fully adjusted HR 1.32, 95% CI 1.08-1.50, and p = 0.01) and all-cause mortality (HR 1.15, 95%CI 1.00-1.38, and p = 0.04). Results were consistent in sensitivity analyses after exclusion of individuals with estimated glomerular filtration rate <45 or <60 mL/min/1.73 m2 and higher plasma phosphate levels. CONCLUSIONS: Serum T50 improves prediction of cardiovascular and all-cause mortality risk in individuals with T2D. Serum T50 may be useful for risk stratification and to guide therapeutic strategies aiming to reduce cardiovascular mortality in T2D.

Comparison of all-cause mortality associated with non-alcoholic fatty liver disease and metabolic dysfunction-associated fatty liver disease in Taiwan MJ cohort.

OBJECTIVES: The global burden of non-alcoholic fatty liver disease (NAFLD) is rising. An alternative term, metabolic dysfunction-associated fatty liver disease (MAFLD), instead highlights the associated metabolic risks. This cohort study examined patient classifications under NAFLD and MAFLD criteria and their associations with all-cause mortality. METHODS: Participants who attended a paid health check-up (2012-2015) were included. Hepatic steatosis (HS) was diagnosed ultrasonographically. NAFLD was defined as HS without secondary causes, while MAFLD involved HS with overweight/obesity, type 2 diabetes mellitus, or ≥2 metabolic dysfunctions. Mortality was tracked via the Taiwan Death Registry until November 30, 2022. RESULTS: Of 118,915 participants, 36.9% had NAFLD, 40.2% had MAFLD, and 32.9% met both definitions. Participants with NAFLD alone had lower mortality, and those with MAFLD alone had higher mortality, than individuals with both conditions. After adjustment for potential confounders, the hazard ratios (HRs) for all-cause mortality were 1.08 (95% confidence interval [CI], 0.78 to 1.48) for NAFLD alone and 1.26 (95% CI, 1.09 to 1.47) for MAFLD alone, relative to both conditions. Advanced fibrosis conferred greater mortality risk, with HRs of 1.93 (95% CI, 1.44 to 2.58) and 2.08 (95% CI, 1.61 to 2.70) for advanced fibrotic NAFLD and MAFLD, respectively. Key mortality risk factors for NAFLD and MAFLD included older age, unmarried status, higher body mass index, smoking, diabetes mellitus, chronic kidney disease, and advanced fibrosis. CONCLUSIONS: All-cause mortality in NAFLD and/or MAFLD was linked to cardiometabolic covariates, with risk attenuated after multivariable adjustment. A high fibrosis-4 index score, indicating fibrosis, could identify fatty liver disease cases involving elevated mortality risk.

Regional variation in cause of death in patients with type 2 diabetes: Insights from EXSCEL.

AIMS: Type 2 diabetes (T2D) is a risk factor for cardiovascular and non-cardiovascular mortality. However, global distribution of cause-specific deaths in T2D is poorly understood. We characterized cause-specific deaths by geographic region among individuals with T2D at risk for cardiovascular disease (CVD). METHODS AND RESULTS: The international EXSCEL trial included 14,752 participants with T2D (73% with established CVD). We identified the proportion of deaths over 5-year follow-up attributed to cardiovascular and non-cardiovascular causes, and associated risk factors. During median 3.2-year follow-up, 1,091 (7.4%) participants died. Adjudicated causes of death were 723 cardiovascular (66.3% of deaths), including 252 unknown, and 368 non-cardiovascular (33.7%). Most deaths occurred in North America (N = 356/9.6% across region) and Eastern Europe (N = 326/8.1%), with fewest in Asia/Pacific (N = 68/4.4%). The highest proportional cause-specific deaths by region were sudden cardiac in Asia/Pacific (23/34% of regional deaths) and North America (86/24%); unknown in Eastern Europe (90/28%) and Western Europe (39/21%); and non-malignant non-cardiovascular in Latin America (48/31%). Cox proportional hazards model for adjudicated causes of death showed prognostic risk factors (hazard ratio [95% CI]) for cardiovascular and non-cardiovascular deaths, respectively: heart failure 2.04 (1.72-2.42) and 1.86 (1.46-2.39); peripheral artery disease 1.83 (1.54-2.18) and 1.78 (1.40-2.26); and current smoking status 1.61 (1.29-2.01) and 1.77 (1.31-2.40). CONCLUSIONS: In a contemporary T2D trial population, with and without established CVD, leading causes of death varied by geographic region. Underlying mechanisms leading to variability in cause of death across geographic regions and its impact on clinical trial endpoints warrant future research.

Association of carotid atherosclerosis markers with all-cause and cardiovascular disease-specific mortality in persons with type 2 diabetes: a causal mediation analysis with glucose variation.

AIMS: Glucose variation (GV) is independently associated with mortality in patients with diabetes. However, no study has examined the effects of carotid atherosclerosis markers on mortality after considering GV. Our purpose is to investigate the independent effects of carotid atherosclerosis markers in persons with type 2 diabetes (T2DM) after considering GV and the mediation effects of carotid atherosclerosis markers on associations between GV with cardiovascular disease (CVD) mortality. MATERIALS AND METHODS: This study is a retrospective cohort study including 3628 persons with T2DM who were admitted to a medical center between January 01, 2001 and October 31, 2021. GV was defined as a coefficient of variation (CV) of repeated measurements within a year before the index date (date of first IMT assessment). Carotid atherosclerosis markers included intima-media thickness (IMT), plaque, and stenosis. The outcomes consisted of all-cause and expanded cardiovascular disease (CVD) mortality. Cox proportional hazards models were applied. RESULTS: Among the participants, 286 (7.9%) had IMT ≥ 2 mm, 2834 (78.1%) had carotid plaque, and 464 (12.8%) had carotid stenosis ≥ 50%. When GV was considered, IMT, carotid plaque, and carotid stenosis were significant factors for all-cause mortality (except IMT considering HbA1c-CV) and expanded CVD mortality. IMT was a significant mediator in the associations of fasting plasma glucose (FPG)-CV with all-cause and expanded CVD mortality (2 and 3.19%, respectively), and carotid stenosis was a significant mediator in the association between FPG-CV and expanded CVD mortality (3.83%). CONCLUSIONS: Our statistical evaluations show suggests that carotid atherosclerosis markers are important predictors of CVD mortality in persons with T2DM if GV is considered. In addition, IMT and carotid stenosis were significant mediators in the association between GV and mortality.

Impacts of heatwaves on type 2 diabetes mortality in China: a comparative analysis between coastal and inland cities.

The impacts of extreme temperatures on diabetes have been explored in previous studies. However, it is unknown whether the impacts of heatwaves appear variations between inland and coastal regions. This study aims to quantify the associations between heat exposure and type 2 diabetes mellitus (T2DM) deaths in two cities with different climate features in Shandong Province, China. We used a case-crossover design by quasi-Poisson generalized additive regression with a distributed lag model with lag 2 weeks, controlling for relative humidity, the concentration of air pollution particles with a diameter of 2.5 µm or less (PM2.5), and seasonality. The wet- bulb temperature (Tw) was used to measure the heat stress of the heatwaves. A significant association between heatwaves and T2DM deaths was only found in the coastal city (Qingdao) at the lag of 2 weeks at the lowest Tw = 14℃ (relative risk (RR) = 1.49, 95% confidence interval (CI): 1.11-2.02; women: RR = 1.51, 95% CI: 1.02-2.24; elderly: RR = 1.50, 95% CI: 1.08-2.09). The lag-specific effects were significant associated with Tw at lag of 1 week at the lowest Tw = 14℃ (RR = 1.14, 95% CI: 1.03-1.26; women: RR = 1.15, 95% CI: 1.01-1.31; elderly: RR = 1.15, 95% CI: 1.03-1.28). However, no significant association was found in Jian city. The research suggested that Tw was significantly associated with T2DM mortality in the coastal city during heatwaves on T2DM mortality. Future strategies should be implemented with considering socio-environmental contexts in regions.

Sotagliflozin and Kidney Outcomes, Kidney Function, and Albuminuria in Type 2 Diabetes and CKD: A Secondary Analysis of the SCORED Trial.

BACKGROUND: In the initial analysis of the Effect of Sotagliflozin on Cardiovascular and Renal Events in Patients with Type 2 Diabetes and Moderate Renal Impairment Who Are at Cardiovascular Risk (SCORED) trial, because of early trial termination and suspension of adjudication, reconciliation of eGFR laboratory data and case report forms had not been completed. This resulted in a small number of kidney composite events and a nominal effect of sotagliflozin versus placebo on this outcome. This exploratory analysis uses laboratory eGFR data, regardless of case report form completion, to assess the effects of sotagliflozin on the predefined kidney composite end point in the SCORED trial and additional cardiorenal composite end points. METHODS: SCORED was a multicenter, randomized trial evaluating cardiorenal outcomes with sotagliflozin versus placebo in 10,584 patients with type 2 diabetes and CKD. This exploratory analysis used laboratory data to derive the eGFR components and case report form data for the non-laboratory-defined components that together made up the kidney and cardiorenal composites. AKI was also assessed in this dataset. RESULTS: Using laboratory data, 223 events were identified, and sotagliflozin reduced the risk of the composite of first event of sustained ≥50% decline in eGFR, eGFR <15 ml/min per 1.73 m 2 , dialysis, or kidney transplant with 87 events (1.6%) in the sotagliflozin group and 136 events (2.6%) in the placebo group (hazard ratio [95% confidence interval], 0.62 [0.48 to 0.82]), P < 0.001). Sotagliflozin reduced the risk of a cardiorenal composite end point defined as the abovementioned composite plus cardiovascular or kidney death with 239 events (4.5%) in the sotagliflozin group and 306 events (5.7%) in the placebo group (hazard ratio [95% confidence interval], 0.77 [0.65 to 0.91], P = 0.0023). The results were consistent when using different eGFR decline thresholds and when only including kidney death in composites (all P < 0.01). The incidence of AKI was similar between treatment groups. CONCLUSIONS: In this exploratory analysis using the complete laboratory dataset, sotagliflozin reduced the risk of kidney and cardiorenal composite end points in patients with type 2 diabetes and CKD. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: ClinicalTrials.gov Identifier: NCT03315143 .

Type 1 and type 2 diabetes mortality burden: Predictions for 2030 based on Bayesian age-period-cohort analysis of China and global mortality burden from 1990 to 2019.

AIMS: This study assessed diabetes (type 1 and type 2) mortality in China and globally from 1990 to 2019, predicting the next decade's trends. MATERIALS AND METHODS: Data came from the Global Burden of Disease (GBD) database. The annual percentage change (AAPC) in age-standardized mortality rates (ASMR) for diabetes (type 1 and type 2) during 1990-2019 was calculated. A Bayesian age-period-cohort (BAPC) model predicted diabetes (type 1 and type 2) mortality from 2020 to 2030. RESULTS: In China, type 1 diabetes deaths declined from 6,005 to 4,504 cases (AAPC -2.827), while type 2 diabetes deaths rose from 64,084 to 168,388 cases (AAPC -0.763) from 1990 to 2019. Globally, type 1 diabetes deaths increased from 55,417 to 78,236 cases (AAPC 0.223), and type 2 diabetes deaths increased from 606,407 to 1,472,934 cases (AAPC 0.365). Both China and global trends showed declining type 1 diabetes ASMR. However, female type 2 diabetes ASMR in China initially increased and then decreased, while males had a rebound trend. Peak type 1 diabetes deaths were in the 40-44 age group, and type 2 diabetes peaked in those over 70. BAPC predicted declining diabetes (type 1 and type 2) mortality burden in China and globally over the next 10 years. CONCLUSIONS: Type 2 diabetes mortality remained high in China and globally despite decreasing type 1 diabetes mortality over 30 years. Predictions suggest a gradual decrease in diabetes mortality over the next decade, highlighting the need for continued focus on type 2 diabetes prevention and treatment.