We prospectively enrolled 3,681 patients with suspected AMI and stratified those by the presence of DM. The ESC 0/1-h and 0/3-h algorithms were used to calculate negative and positive predictive values (NPV, PPV). In addition, alternative cutoffs were calculated and externally validated in 2,895 patients.

In total, 563 patients (15.3%) had DM, and 137 (24.3%) of these had AMI. When the ESC 0/1-h algorithm was used, the NPV was comparable in patients with and without DM (absolute difference [AD] –1.50 [95% CI –5.95, 2.96]). In contrast, the ESC 0/3-h algorithm resulted in a significantly lower NPV in patients with DM (AD –2.27 [95% CI –4.47, –0.07]). The diagnostic performance for rule-in of AMI (PPV) was comparable in both groups: 0/1-h (AD 6.59 [95% CI –19.53, 6.35]) and 0/3-h (AD 1.03 [95% CI –7.63, 9.7]). Alternative cutoffs increased the PPV in both algorithms significantly, while improvements in NPV were only subtle.

Application of the ESC 0/1-h algorithm revealed comparable safety to rule out AMI comparing patients with and without DM, while this was not observed with the ESC 0/3-h algorithm. Although alternative cutoffs might be helpful, patients with DM remain a high-risk population in whom identification of AMI is challenging and who require careful clinical evaluation.

Least squares mean difference (LSMD) in estimated glomerular filtration rate (eGFR) from baseline between the EQW and placebo groups was calculated for 13,844 participants. Cox regression models were used to estimate effects by group on incident macroalbuminuria, retinopathy, and major adverse CV events (MACE). Interval-censored time-to-event models estimated effects on renal composite 1 (40% eGFR decline, renal replacement, or renal death) and renal composite 2 (composite 1 variables plus macroalbuminuria).

EQW did not change eGFR significantly (LSMD 0.21 mL/min/1.73 m² [95% CI –0.27 to 0.70]). Macroalbuminuria occurred in 2.2% of patients in the EQW group and in 2.5% of those in the placebo group (hazard ratio [HR] 0.87 [95% CI 0.70–1.07]). Neither renal composite was reduced with EQW in unadjusted analyses, but renal composite 2 was reduced after adjustment (HR 0.85 [95% CI 0.74–0.98]). Retinopathy rates did not differ by treatment group or in the HbA_1c-lowering or prior retinopathy subgroups. CV outcomes in those with eGFR <60 mL/min/1.73 m² did not differ by group. Those with eGFR ≥60 mL/min/1.73 m² had nominal risk reductions for MACE, all-cause mortality, and CV death, but interactions by renal function group were significant for only stroke (HR 0.74 [95% CI 0.58–0.93]; P for interaction = 0.035) and CV death (HR 1.08 [95% CI 0.85–1.38]; P for interaction = 0.031).

EQW had no impact on unadjusted retinopathy or renal outcomes. CV risk was modestly reduced only in those with eGFR ≥60 mL/min/1.73 m² in analyses unadjusted for multiplicity.

UK Biobank participants without baseline CVD or known diabetes (n = 357,833) were included. Associations of HbA1c with CVD was assessed using Cox models adjusting for classical risk factors. Predictive utility was determined by the C-index and net reclassification index (NRI). A separate analysis was conducted in 16,596 participants with known baseline diabetes.

Incident fatal or nonfatal CVD, as defined in the QRISK3 prediction model, occurred in 12,877 participants over 8.9 years. Of participants, 3.3% (n = 11,665) had prediabetes (42.0–47.9 mmol/mol [6.0–6.4%]) and 0.7% (n = 2,573) had undiagnosed diabetes (≥48.0 mmol/mol [≥6.5%]). In unadjusted models, compared with the reference group (<42.0 mmol/mol [<6.0%]), those with prediabetes and undiagnosed diabetes were at higher CVD risk: hazard ratio (HR) 1.83 (95% CI 1.69–1.97) and 2.26 (95% CI 1.96–2.60), respectively. After adjustment for classical risk factors, these attenuated to HR 1.11 (95% CI 1.03–1.20) and 1.20 (1.04–1.38), respectively. Adding HbA_1c to the QRISK3 CVD risk prediction model (C-index 0.7392) yielded a small improvement in discrimination (C-index increase of 0.0004 [95% CI 0.0001–0.0007]). The NRI showed no improvement. Results were similar for models based on the ACC/AHA and SCORE risk models.

The near twofold higher unadjusted risk for CVD in people with prediabetes is driven mainly by abnormal levels of conventional CVD risk factors. While HbA_1c adds minimally to cardiovascular risk prediction, those with prediabetes should have their conventional cardiovascular risk factors appropriately measured and managed.

The concentration of 239 biochemical markers was measured in stored serum from participants in the biomarker substudy of Outcome Reduction With Initial Glargine Intervention (ORIGIN) trial. Repeated-measures mixed-effects models were used to compute the annual change in eGFR (measured as mL/min/1.73 m²/year) for the 7,482 participants with a recorded baseline and follow-up eGFR. Linear regression models using forward selection were used to identify the independent biomarker determinants of the annual change in eGFR after accounting for baseline HbA_1c, baseline eGFR, and routinely measured clinical risk factors. The incidence of the composite renal outcome (i.e., renal replacement therapy, renal death, renal failure, albuminuria progression, doubling of serum creatinine) and death within each fourth of change in eGFR predicted from these models was also estimated.

During 6.2 years of median follow-up, the median annual change in eGFR was –0.18 mL/min/1.73 m²/year. Fifteen biomarkers independently predicted eGFR decline after accounting for cardiovascular risk factors, as did 12 of these plus 1 additional biomarker after accounting for renal risk factors. Every 0.1 mL/min/1.73 m² predicted annual fall in eGFR predicted a 13% (95% CI 12, 14%) higher mortality.

Adding up to 16 biomarkers to routinely measured clinical risk factors improves the prediction of annual change in eGFR in people with dysglycemia.

This retrospective cohort study analyzed patients from Tayside and Fife in the Scottish Care Information–Diabetes Collaboration (SCI-DC) who were observable from the diagnosis of diabetes and had at least five HbA_1c measurements before the outcomes were evaluated. We used the previously reported HbA_1c variability score (HVS), calculated as the percentage of the number of changes in HbA_1c >0.5% (5.5 mmol/mol) among all HbA_1c measurements within an individual. The association between HVS and 10 outcomes was assessed using Cox proportional hazards models.

We included 13,111–19,883 patients in the analyses of each outcome. The patients with HVS >60% were associated with elevated risks of all outcomes compared with the lowest quintile (for example, HVS >80 to ≤100 vs. HVS ≥0 to ≤20, hazard ratio 2.38 [95% CI 1.61–3.53] for major adverse cardiovascular events, 2.4 [1.72–3.33] for all-cause mortality, 2.4 [1.13–5.11] for atherosclerotic cardiovascular death, 2.63 [1.81–3.84] for coronary artery disease, 2.04 [1.12–3.73] for ischemic stroke, 3.23 [1.76–5.93] for heart failure, 7.4 [3.84–14.27] for diabetic retinopathy, 3.07 [2.23–4.22] for diabetic peripheral neuropathy, 5.24 [2.61–10.49] for diabetic foot ulcer, and 3.49 [2.47–4.95] for new-onset chronic kidney disease). Four sensitivity analyses, including adjustment for time-weighted average HbA_1c, confirmed the robustness of the results.

Our study shows that higher HbA_1c variability is associated with increased risks of all-cause mortality, cardiovascular events, and microvascular complications of diabetes independently of high HbA_1c.

We performed a cross-sectional study in severely obese individuals before bariatric surgery. Lean control subjects were recruited from a research website. Cognitive deficits were defined by the National Institutes of Health (NIH) Toolbox (<5th percentile for lean control subjects). Cardiovascular autonomic neuropathy (CAN) was defined by an expiration-to-inspiration (E-to-I) ratio of <5th percentile for lean control subjects. Retinopathy was based on retinal photographs and nephropathy on the estimated glomerular filtration rate (<60 mg/dL) and/or the albumin-to-creatinine ratio (ACR) (≥30 mg/g). NIH Toolbox, E-to-I ratio, mean deviation on frequency doubling technology testing, and ACR were used as sensitive measures of these outcomes. We used multivariable linear regression to explore associations between metabolic factors and these outcomes.

We recruited 138 severely obese individuals and 46 lean control subjects. The prevalence of cognitive deficits, CAN, retinopathy, and nephropathy were 6.5%, 4.4%, 0%, and 6.5% in lean control subjects; 22.2%, 18.2%, 0%, and 6.1% in obese participants with normoglycemia; 17.7%, 21.4%, 1.9%, and 17.9% in obese participants with prediabetes; and 25.6%, 31.9%, 6.1%, and 16.3% in obese participants with diabetes. Waist circumference was significantly associated with cognitive function (–1.48; 95% CI –2.38, –0.57) and E-to-I ratio (–0.007; 95% CI –0.012, –0.002). Prediabetes was significantly associated with retinal function (–1.78; 95% CI –3.56, –0.002).

Obesity alone is likely sufficient to cause cognitive deficits but not retinopathy or nephropathy. Central obesity is the key metabolic risk factor.

We identified 8,528 patients with diabetes (self-report, medication use, or electronic medical record diagnosis) from the Henry Ford Exercise Testing Project (FIT Project). Patients with a BMI <18.5 kg/m² or cancer were excluded. Fitness was measured as the METs achieved during a physician-referred treadmill stress test and categorized as low (<6), moderate (6–9.9), or high (≥10). Adjusted hazard ratios for mortality were calculated using standard BMI (kilograms per meter squared) cutoffs of normal (18.5–24.9), overweight (25–29.9), and obese (≥30). Adjusted splines centered at 22.5 kg/m² were used to examine BMI as a continuous variable.

Patients had a mean age of 58 ± 11 years (49% women) with 1,319 deaths over a mean follow-up of 10.0 ± 4.1 years. Overall, obese patients had a 30% lower mortality hazard (P < 0.001) compared with normal-weight patients. In adjusted spline modeling, higher BMI as a continuous variable was predominantly associated with a lower mortality risk in the lowest fitness group and among patients with moderate fitness and BMI ≥30 kg/m². Compared with the lowest fitness group, patients with higher fitness had an ~50% (6–9.9 METs) and 70% (≥10 METs) lower mortality hazard regardless of BMI (P < 0.001).

Among patients with diabetes, the obesity paradox was less pronounced for patients with the highest fitness level, and these patients also had the lowest risk of mortality.

Based on the prospective European Prospective Investigation of Cancer (EPIC)-Potsdam cohort (n = 27,548), we constructed case-cohorts including a random subsample of 2,500 participants and all physician-verified incident cases of type 2 diabetes (n = 820; median follow-up time 6.5 years) and CVD (n = 508; median follow-up time 8.2 years). Information on the relative abundance of 39 N-glycan groups in baseline plasma samples was generated by chromatographic profiling. We selected predictive N-glycans for type 2 diabetes and CVD separately, based on cross-validated machine learning, nonlinear model building, and construction of weighted prediction scores. This workflow for CVD was applied separately in men and women.

The N-glycan–based type 2 diabetes score was strongly predictive for diabetes risk in an internal validation cohort (weighted C-index 0.83, 95% CI 0.78–0.88), and this finding was externally validated in the Finland Cardiovascular Risk Study (FINRISK) cohort. N-glycans were moderately predictive for CVD incidence (weighted C-indices 0.66, 95% CI 0.60–0.72, for men; 0.64, 95% CI 0.55–0.73, for women). Information on the selected N-glycans improved the accuracy of established and clinically applied risk prediction scores for type 2 diabetes and CVD.

Selected N-glycans improve type 2 diabetes and CVD prediction beyond established risk markers. Plasma protein N-glycan profiling may thus be useful for risk stratification in the context of precisely targeted primary prevention of cardiometabolic diseases.

In a post hoc analysis of 14,752 Exenatide Study of Cardiovascular Event Lowering (EXSCEL) participants, we examined time-dependent associations between SHEs and subsequent major adverse cardiac events (CV death, nonfatal myocardial infarction [MI] or stroke), fatal/nonfatal MI, fatal/nonfatal stroke, hospitalization for acute coronary syndrome (hACS), hospitalization for heart failure (hHF), and all-cause mortality (ACM), as well as time-dependent associations between nonfatal CV events and subsequent SHEs.

SHEs were uncommon and not associated with once-weekly exenatide therapy (hazard ratio 1.13 [95% CI 0.94–1.36], P = 0.179). In fully adjusted models, SHEs were associated with an increased risk of subsequent ACM (1.83 [1.38–2.42], P < 0.001), CV death (1.60 [1.11–2.30], P = 0.012), and hHF (2.09 [1.37–3.17], P = 0.001), while nonfatal MI (2.02 [1.35–3.01], P = 0.001), nonfatal stroke (2.30 [1.25–4.23], P = 0.007), hACS (2.00 [1.39–2.90], P < 0.001), and hHF (3.24 [1.98–5.30], P < 0.001) were all associated with a subsequent increased risk of SHEs. The elevated bidirectional time-dependent hazards linking SHEs and a composite of all CV events were approximately constant over time, with those individuals at dual risk showing higher comorbidity scores compared with those without.

These findings, showing greater risk of SHEs after CV events as well as greater risk of CV events after SHEs, validate a bidirectional relationship between CV events and SHEs in patients with high comorbidity scores.

This study applied observational and one-sample Mendelian randomization (MR) analyses to individual-level data from 117,193 Danish individuals, and validation by two-sample MR analyses on summary-level data from 133,010 individuals from the Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC), 117,165 from the CKDGen Consortium, and 452,264 from the UK Biobank.

Observationally, glucose levels in the normoglycemic range and higher were associated with high risks of retinopathy, neuropathy, diabetic nephropathy, PAD, and MI (all P for trend <0.001). In genetic causal analyses, the risk ratio for a 1 mmol/L higher glucose level was 2.01 (95% CI 1.18–3.41) for retinopathy, 2.15 (1.38–3.35) for neuropathy, 1.58 (1.04–2.40) for diabetic nephropathy, 0.97 (0.84–1.12) for estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m², 1.19 (0.90–1.58) for PAD, and 1.49 (1.02–2.17) for MI. Summary-level data from the MAGIC, the CKDGen Consortium, and the UK Biobank gave a genetic risk ratio of 4.55 (95% CI 2.26–9.15) for retinopathy, 1.48 (0.83–2.66) for peripheral neuropathy, 0.98 (0.94–1.01) for eGFR <60 mL/min/1.73 m², and 1.23 (0.57–2.67) for PAD per 1 mmol/L higher glucose level.

Glucose levels in the normoglycemic range and higher were prospectively associated with a high risk of retinopathy, neuropathy, diabetic nephropathy, eGFR <60 mL/min/1.73 m², PAD, and MI. These associations were confirmed in genetic causal analyses for retinopathy, neuropathy, diabetic nephropathy, and MI, but they could not be confirmed for PAD and seemed to be refuted for eGFR <60 mL/min/1.73 m².

CVD events in the 1,441 DCCT/EDIC participants were analyzed separately by type (CVD death, acute myocardial infarction [MI], stroke, silent MI, angina, percutaneous transluminal coronary angioplasty/coronary artery bypass graft [PTCA/CABG], and congestive heart failure [CHF]) or as composite outcomes (CVD or major adverse cardiovascular events [MACE]). Proportional rate models and conditional models assessed associations between risk factors and CVD outcomes.

Over a median follow-up of 29 years, 239 participants had 421 CVD events, and 120 individuals had 149 MACE. Age was the strongest risk factor for acute MI, silent MI, stroke, and PTCA/CABG, while glycemia was the strongest risk factor for CVD death, CHF, and angina, second strongest for acute MI and PTCA/CABG, third strongest for stroke, and not associated with silent MI. HbA_1c was the strongest modifiable risk factor for a first CVD event (CVD: HR 1.38 [95% CI 1.21, 1.56] per 1% higher HbA_1c; MACE: HR 1.54 [1.30, 1.82]) and also for subsequent CVD events (CVD: incidence ratio [IR] 1.28 [95% CI 1.09, 1.51]; MACE: IR 1.89 [1.36, 2.61]).

Intensive glycemic management is recommended to lower the risk of initial CVD events in T1D. After a first event, optimal glycemic control may reduce the risk of recurrent CVD events and should be maintained.

The Swedish Obese Subjects study is a prospective matched study performed at 25 surgical departments and 480 primary health care centers. Participants aged 37–60 years with BMI ≥34 kg/m² (men) or ≥38 kg/m² (women) were recruited between 1987 and 2001; 2,007 participants received bariatric surgery and 2,040 usual care. Self-reported body weight at 20 years of age was used to stratify patients into subgroups with normal BMI (<25 kg/m²), overweight (BMI 25–29.9 kg/m²), or obesity (BMI ≥30 kg/m²). Body weight, energy intake, and type 2 diabetes status were examined over 10 years, and incidence of cardiovascular and microvascular disease was determined over up to 26 years using data from health registers.

There were small but statistically significant differences in reduction of body weight among the subgroups after bariatric surgery (interaction P = 0.032), with the largest reductions among those with obesity aged 20 years. Bariatric surgery increased type 2 diabetes remission (odds ratios 4.51, 4.90, and 5.58 in subgroups with normal BMI, overweight, or obesity at 20 years of age, respectively; interaction P = 0.951), reduced type 2 diabetes incidence (odds ratios 0.15, 0.13, and 0.15, respectively; interaction P = 0.972), and reduced microvascular complications independent of obesity status at 20 years of age (interaction P = 0.650). The association between bariatric surgery and cardiovascular disease was similar in the subgroups (interaction P = 0.674). Surgical complications were similar in the subgroups.

The treatment benefits of bariatric surgery in adults are similar regardless of obesity status at 20 years of age.

A total of 24 T1D patients (median age 5.1 years) received a single intravenous infusion of autologous UCB cells and underwent metabolic and immunologic assessments.

No infusion-related adverse events were observed. β-Cell function declined after UCB infusion. Area under the curve C-peptide was 24.3% of baseline 1 year postinfusion (P < 0.001) and 2% of baseline 2 years after infusion (P < 0.001). Flow cytometry revealed increased regulatory T cells (Tregs) (P = 0.04) and naive Tregs (P = 0.001) 6 and 9 months after infusion, respectively.

Autologous UCB infusion in children with T1D is safe and induces changes in Treg frequency but fails to preserve C-peptide.

In this double-blind study, 587 patients taking stable-dose insulin glargine (±metformin ≥1,500 mg/day) were randomized (1:1:1:1:1) to MK-0941 10, 20, 30, or 40 mg or matching placebo t.i.d. before meals (a.c.). This study included an initial 14-week, dose-ranging phase followed by a 40-week treatment phase during which patients were to be uptitrated as tolerated to 40 mg (or placebo) t.i.d. a.c. The primary efficacy end point was change from baseline in A1C at Week 14.

At Week 14, A1C and 2-h postmeal glucose (PMG) improved significantly versus placebo with all MK-0941 doses. Maximal placebo-adjusted least squares mean changes from baseline in A1C (baseline A1C 9.0%) and 2-h PMG were –0.8% and –37 mg/dL (–2 mmol/L), respectively. No significant effects on fasting plasma glucose were observed at any dose versus placebo. By 30 weeks, the initial glycemic responses noted at 14 weeks were not sustained. MK-0941 at one or more doses was associated with significant increases in the incidence of hypoglycemia, triglycerides, systolic blood pressure, and proportion of patients meeting criteria for predefined limits of change for increased diastolic blood pressure.

In patients receiving stable-dose insulin glargine, the GKA MK-0941 led to improvements in glycemic control that were not sustained. MK-0941 was associated with an increased incidence of hypoglycemia and elevations in triglycerides and blood pressure.