We retrospectively analyzed records of patients presenting with a first type 1 MI at age ≤50 years from 2000 to 2016. Diabetes was defined as a hemoglobin A_1c ≥6.5% (48 mmol/mol) or a documented diagnosis of or treatment for diabetes. Vital status was ascertained for all patients, and cause of death was adjudicated.

Among 2,097 young patients who had a type 1 MI (mean age 44.0 ± 5.1 years, 19.3% female, 73% white), diabetes was present in 416 (20%), of whom 172 (41%) were receiving insulin. Over a median follow-up of 11.2 years (interquartile range 7.3–14.2 years), diabetes was associated with a higher all-cause mortality (hazard ratio 2.30; P < 0.001) and cardiovascular mortality (2.68; P < 0.001). These associations persisted after adjusting for baseline covariates (all-cause mortality: 1.65; P = 0.008; cardiovascular mortality: 2.10; P = 0.004).

Diabetes was present in 20% of patients who presented with their first MI at age ≤50 years and was associated with worse long-term all-cause and cardiovascular mortality. These findings highlight the need for implementing more-aggressive therapies aimed at preventing future adverse cardiovascular events in this population.

Patients with type 1 diabetes receiving regular care were recruited in this observational cross-sectional study and divided into four groups according to their Lp(a) levels in nmol/L (very low <10, low 10–30, intermediate 30–120, high >120). Prevalence of vascular complications was compared between the groups. In addition, the association between metabolic control, measured as HbA_1c, and Lp(a) was studied.

The patients (n = 1,860) had a median age of 48 years, diabetes duration of 25 years, and HbA_1c of 7.8% (61 mmol/mol). The median Lp(a) was 19 (interquartile range 10–71) nmol/L. No significant differences between men and women were observed, but Lp(a) levels increased with increasing age. Patients in the high Lp(a) group had higher prevalence of complications than patients in the very low Lp(a) group. The age- and smoking-status–adjusted relative risk ratio of having any macrovascular disease was 1.51 (95% CI 1.01–2.28, P = 0.048); coronary heart disease, 1.70 (95% CI 0.97–3.00, P = 0.063); albuminuria, 1.68 (95% CI 1.12–2.50, P = 0.01); and calcified aortic valve disease, 2.03 (95% CI 1.03–4.03; P = 0.042). Patients with good metabolic control, HbA_1c <6.9% (<52 mmol/mol), had significantly lower Lp(a) levels than patients with poorer metabolic control, HbA_1c >6.9% (>52 mmol/mol).

Lp(a) is a significant risk factor for macrovascular disease, albuminuria, and calcified aortic valve disease in patients with type 1 diabetes. Poor metabolic control in patients with type 1 diabetes is associated with increased Lp(a) levels.

We linked data from the National Diabetes Register and the Scandinavian Obesity Surgery Register with four national databases holding information on socioeconomic variables, medications, hospitalizations, and causes of death and matched 5,321 individuals with T2DM who had undergone GBP with 5,321 who had not (age 18–65 years, mean BMI >40 kg/m², mean follow-up >4.5 years). The risks of postoperative outcomes were assessed with Cox regression models.

During the first years postsurgery, there were small reductions in creatinine and albuminuria and stable estimated glomerular filtration rate (eGFR) in the GBP group. The incidence rates of most outcomes relating to renal function, CV disease, and mortality were lower after GBP, being particularly marked for heart failure (hazard ratio [HR] 0.33 [95% CI 0.24, 0.46]) and CV mortality (HR 0.36 [(95% CI 0.22, 0.58]). The risk of a composite of severe renal disease or halved eGFR was 0.56 (95% CI 0.44, 0.71), whereas nonfatal CV risk was lowered less (HR 0.82 [95% CI 0.70, 0.97]) after GBP. Risks for key outcomes were generally lower after GBP in all eGFR strata, including in individuals with eGFR <30 mL/min/1.73 m².

Our data suggest robust benefits for renal outcomes, heart failure, and CV mortality after GBP in individuals with obesity and T2DM. These results suggest that marked weight loss yields important benefits, particularly on the cardiorenal axis (including slowing progression to end-stage renal disease), whatever the baseline renal function status.

We used logistic regression to examine associations of comorbidities with elevations in either troponin (≥85th percentile) among 1,835 participants in the Atherosclerosis Risk in Communities (ARIC) Study with diabetes (ages 67–89 years, 43% male, 31% black) at visit 5 (2011–2013). We used Cox models to compare associations of high cardiac troponins with mortality across comorbidity levels.

Elevations in either troponin (≥9.4 ng/L for hs-cTnI, ≥25 ng/L for hs-cTnT) were associated with prevalent coronary heart disease, heart failure, chronic kidney disease, pulmonary disease, hypoglycemia, hypertension, dementia, and frailty. Over a median follow-up of 6.2 years (418 deaths), both high hs-cTnI and high hs-cTnT further stratified mortality risk beyond comorbidity levels; those with a high hs-cTnI or hs-cTnT and high comorbidity were at highest mortality risk. Even among those with low comorbidity, a high hs-cTnI (hazard ratio [HR] 3.0 [95% CI 1.7, 5.4]) or hs-cTnT (HR 3.3 [95% CI 1.8, 6.2]) was associated with elevated mortality.

Many comorbidities were reflected by both hs-cTnI and hs-cTnT; elevations in either of the troponins were associated with higher mortality risk beyond comorbidity burden. High-sensitivity cardiac troponins may identify older adults at high mortality risk and be useful in guiding clinical care of older adults with diabetes.

A cross-sectional study of 193 patients with type 2 diabetes and 20 age- and sex-matched controls. Cardiovascular magnetic resonance was used in order to evaluate left ventricular structure and function, and MBF at rest and during adenosine-induced stress. MBF was derived as the mean of the flow within all segments of a midventricular slice.

Patients with type 2 diabetes had higher global MBF at rest (0.81 ± 0.19 mL/min/g) and lower global MBF during stress (2.4 ± 0.9 mL/min/g) than did controls (0.61 ± 0.11 at rest, 3.2 ± 0.8 mL/min/g under stress; both P < 0.01). Patients with macroalbuminuria had lower MBF during stress (1.6 ± 0.5 mL/min/g) than did patients with microalbuminuria (2.1 ± 0.7 mL/min/g; P = 0.04), who in turn had lower MBF during stress than did normoalbuminuric patients (2.7 ± 0.9 mL/min/g; P < 0.01). Patients with severe retinopathy had lower MBF during stress (1.8 ± 0.6 mL/min/g) than did patients with simplex retinopathy (2.3 ± 0.7 mL/min/g; P < 0.05) and those who did not have retinopathy (2.6 ± 1.0 mL/min/g; P < 0.05). Albuminuria and retinopathy were associated with reduced MBF during stress in a multiple regression analysis. Stress-related MBF inversely correlated with myocardial extracellular volume (P < 0.001; R² = 0.37), a measure of diffuse myocardial fibrosis. A trend toward lower basal MBF was observed in patients treated with sodium–glucose cotransporter 2 inhibitors (P = 0.07).

Patients with type 2 diabetes have higher global MBF at rest and lower maximal MBF during vasodilator-induced stress than do controls. Reduced MBF during stress is associated with diabetes complications (albuminuria and retinopathy) and is inversely correlated with diffuse myocardial fibrosis.

We studied the effects of more intensive glycemic control in 11,071 patients with type 2 diabetes (T2D), without missing values, in the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial, using Cox models.

During 5 years’ follow-up, intensive glycemic control reduced major vascular events (hazard ratio [HR] 0.90 [95% CI 0.83–0.98]), with the major driver being a reduction in the development of macroalbuminuria. There was no evidence of differences in the effect, regardless of baseline ASCVD risk or HbA_1c level (P for interaction = 0.29 and 0.94, respectively). Similarly, the beneficial effects of intensive glycemic control on all-cause mortality were not significantly different across baseline ASCVD risk (P = 0.15) or HbA_1c levels (P = 0.87). The risks of severe hypoglycemic events were higher in the intensive glycemic control group compared with the standard glycemic control group (HR 1.85 [1.41–2.42]), with no significant heterogeneity across subgroups defined by ASCVD risk or HbA_1c at baseline (P = 0.09 and 0.18, respectively).

The major benefits for patients with T2D in ADVANCE did not substantially differ across levels of baseline ASCVD risk and HbA_1c.

This article reports on a prospective, randomized, open-label, blinded end point trial with nested case-control study. Asymptomatic younger adults with T2D were randomized 1:1:1 to a 12-week intervention of 1) routine care, 2) supervised aerobic exercise training, or 3) a low-energy (~810 kcal/day) MRP. Participants underwent echocardiography, cardiopulmonary exercise testing, and cardiac magnetic resonance (CMR) at baseline and 12 weeks. The primary outcome was change in left ventricular (LV) peak early diastolic strain rate (PEDSR) as measured by CMR. Healthy volunteers were enrolled for baseline case-control comparison.

Eighty-seven participants with T2D (age 51 ± 7 years, HbA_1c 7.3 ± 1.1%) and 36 matched control participants were included. At baseline, those with T2D had evidence of diastolic dysfunction (PEDSR 1.01 ± 0.19 vs. 1.10 ± 0.16 s^–1, P = 0.02) compared with control participants. Seventy-six participants with T2D completed the trial (30 routine care, 22 exercise, and 24 MRP). The MRP arm lost 13 kg in weight and had improved blood pressure, glycemia, LV mass/volume, and aortic stiffness. The exercise arm had negligible weight loss but increased exercise capacity. PEDSR increased in the exercise arm versus routine care (β = 0.132, P = 0.002) but did not improve with the MRP (β = 0.016, P = 0.731).

In asymptomatic working-age adults with T2D, exercise training improved diastolic function. Despite beneficial effects of weight loss on glycemic control, concentric LV remodeling, and aortic stiffness, a low-energy MRP did not improve diastolic function.

We studied the risk of all-cause mortality in relation to long-term visit-to-visit HbA_1c variability, expressed as coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV), from the 8th month to the transition. Multivariable Cox proportional hazards models were used to estimate adjusted hazard ratio (HR) and 95% CI.

Compared with the standard therapy group (n = 4,728), the intensive therapy group (n = 4,755) had significantly lower mean HbA_1c (6.6% [49 mmol/mol] vs. 7.7% [61 mmol/mol], P < 0.0001) and lower CV, VIM, and ARV (P < 0.0001). In multivariate adjusted analysis, all three HbA_1c variability indices were significantly associated with total mortality in all patients as well as in the standard- and intensive-therapy groups analyzed separately. The hazard ratios for a 1-SD increase in HbA_1c variability indices for the all-cause mortality were 1.19 and 1.23 in intensive and standard therapy, respectively. Cross-tabulation analysis showed the third tertile of HbA_1c mean and VIM had significantly higher all-cause mortality (HR 2.05; 95% CI, 1.17–3.61; P < 0.01) only in the intensive-therapy group.

Long-term visit-to-visit HbA_1c variability was a strong predictor of all-cause mortality. HbA_1c VIM combined with HbA_1c mean conferred an increased risk for all-cause mortality in the intensive-therapy group.

Cox regression models were constructed to analyze 20 years of data from the Danish National Patient Registry with respect to effect of the antihyperglycemic therapies on the three end points.

A total of 66,807 people with type 2 diabetes were treated with metformin (MET) including a combination of second- and third-line therapies. People on MET plus sulfonylurea (SU) had the highest risk of all end points, except for severe hypoglycemia, for which people on MET plus basal insulin (BASAL) had a higher risk. The lowest risk of major adverse cardiovascular events was seen for people on a regimen including a glucagon-like peptide 1 (GLP-1) receptor agonist. People treated with MET, GLP-1, and BASAL had a lower risk of all three end points than people treated with MET and BASAL, especially for severe hypoglycemia. The lowest risk of all three end points was, in general, seen for people treated with MET, sodium–glucose cotransporter 2 inhibitor, and GLP-1.

Findings from this study do not support SU as the second-line treatment choice for patients with type 2 diabetes. Moreover, the results indicate that adding a GLP-1 for people treated with MET and BASAL could be considered, especially if those people suffer from severe hypoglycemia.

Data were drawn from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial and the Veterans Affairs Diabetes Trial (VADT). Coefficient of variation (CV) and average real variability (ARV) were calculated for systolic (SBP) and diastolic blood pressure (DBP) along with maximum and cumulative mean SBP and DBP during both trials.

In ACCORD, CV and ARV of SBP and DBP were associated with increased risk of HF, even after adjusting for other risk factors and mean blood pressure (e.g., CV-SBP: hazard ratio [HR] 1.15, P = 0.01; CV-DBP: HR 1.18, P = 0.003). In the VADT, DBP variability was associated with increased risk of HF (ARV-DBP: HR 1.16, P = 0.001; CV-DBP: HR 1.09, P = 0.04). Further, in ACCORD, those with progressively lower baseline blood pressure demonstrated a stepwise increase in risk of HF with higher CV-SBP, ARV-SBP, and CV-DBP. Effects of blood pressure variability were related to dips, not elevations, in blood pressure.

Blood pressure variability is associated with HF risk in individuals with type 2 diabetes, possibly a consequence of periods of ischemia during diastole. These results may have implications for optimizing blood pressure treatment strategies in those with type 2 diabetes.

This age-, sex-, BMI-, and diabetes duration–matched cohort study used data from a U.K. primary care database from 1 January 2005 to 17 January 2018. Participants aged ≥16 years with type 2 diabetes were included. Exposed participants were those who developed OSA after their diabetes diagnosis; unexposed participants were those without diagnosed OSA. Outcomes were composite CVD (ischemic heart disease [IHD], stroke/transient ischemic attack [TIA], heart failure [HF]), peripheral vascular disease (PVD), atrial fibrillation (AF), peripheral neuropathy (PN), diabetes-related foot disease (DFD), referable retinopathy, chronic kidney disease (CKD), and all-cause mortality. The same outcomes were explored in patients with preexisting OSA before a diagnosis of type 2 diabetes versus diabetes without diagnosed OSA.

A total of 3,667 exposed participants and 10,450 matched control participants were included. Adjusted hazard ratios for the outcomes were as follows: composite CVD 1.54 (95% CI 1.32, 1.79), IHD 1.55 (1.26, 1.90), HF 1.67 (1.35, 2.06), stroke/TIA 1.57 (1.27, 1.94), PVD 1.10 (0.91, 1.32), AF 1.53 (1.28, 1.83), PN 1.32 (1.14, 1.51), DFD 1.42 (1.16, 1.74), referable retinopathy 0.99 (0.82, 1.21), CKD (stage 3–5) 1.18 (1.02, 1.36), albuminuria 1.11 (1.01, 1.22), and all-cause mortality 1.24 (1.10, 1.40). In the prevalent OSA cohort, the results were similar, but some associations were not observed.

Patients with type 2 diabetes who develop OSA are at increased risk of CVD, AF, PN, DFD, CKD, and all-cause mortality compared with patients without diagnosed OSA. Patients with type 2 diabetes who develop OSA are a high-risk population, and strategies to detect OSA and prevent cardiovascular and microvascular complications should be implemented.

Baseline data from the publications of the three trials were obtained and entered into the BRAVO model to predict cardiovascular outcomes. Projected benefits of reducing risk factors of interest (A1C, systolic blood pressure [SBP], LDL, or BMI) on cardiovascular events were evaluated, and simulated outcomes were compared with those observed in each trial.

BRAVO achieved the best prediction accuracy when simulating outcomes of the CANVAS and DECLARE-TIMI 58 trials. For the EMPA-REG OUTCOME trial, a mild bias was observed (~20%) in the prediction of mortality and angina. The effect of risk reduction on outcomes in treatment versus placebo groups predicted by the BRAVO model strongly correlated with the observed effect of risk reduction on the trial outcomes as published. Finally, the BRAVO engine revealed that most of the clinical benefits associated with SGLT2i treatment are through A1C control, although reductions in SBP and BMI explain a proportion of the observed decline in cardiovascular events.

The BRAVO risk engine was effective in predicting the benefits of SGLT2is on cardiovascular health through improvements in commonly measured risk factors, including A1C, SBP, and BMI. Since these benefits are individually small, the use of the complex, dynamic BRAVO model is ideal to explain the cardiovascular outcome trial results.

Four years of data were extracted from a hospital electronic health record system. This included laboratory and point-of-care blood glucose (BG) values to identify biochemical and clinically significant hypoglycemic episodes (BG ≤3.9 and ≤2.9 mmol/L, respectively). We used patient demographics, administered medications, vital signs, laboratory results, and procedures performed during the hospital stays to inform the model. Two iterations of the data set included the doses of insulin administered and the past history of inpatient hypoglycemia. Eighteen different prediction models were compared using the area under the receiver operating characteristic curve (AUROC) through a 10-fold cross validation.

We analyzed data obtained from 17,658 inpatients with diabetes who underwent 32,758 admissions between July 2014 and August 2018. The predictive factors from the logistic regression model included people undergoing procedures, weight, type of diabetes, oxygen saturation level, use of medications (insulin, sulfonylurea, and metformin), and albumin levels. The machine learning model with the best performance was the XGBoost model (AUROC 0.96). This outperformed the logistic regression model, which had an AUROC of 0.75 for the estimation of the risk of clinically significant hypoglycemia.

Advanced machine learning models are superior to logistic regression models in predicting the risk of hypoglycemia in inpatients with diabetes. Trials of such models should be conducted in real time to evaluate their utility to reduce inpatient hypoglycemia.

The association between CD34⁺ cell migration and cardiovascular mortality was reassessed at 6 years after revascularization. In a new series of T2D-CLI and control subjects, immuno-sorted bone marrow CD34⁺ cells were profiled for miRNA expression and assessed for apoptosis and angiogenesis activity. The differentially regulated miRNA-21 and its proapoptotic target, PDCD4, were titrated to verify their contribution in transferring damaging signals from CD34⁺ cells to endothelial cells.

Multivariable regression analysis confirmed that CD34⁺ cell migration forecasts long-term cardiovascular mortality. CD34⁺ cells from T2D-CLI patients were more apoptotic and less proangiogenic than control subjects and featured miRNA-21 downregulation, modulation of several long noncoding RNAs acting as miRNA-21 sponges, and upregulation of the miRNA-21 proapoptotic target PDCD4. Silencing miR-21 in control subject CD34⁺ cells phenocopied the T2D-CLI cell behavior. In coculture, T2D-CLI CD34⁺ cells imprinted naïve endothelial cells, increasing apoptosis, reducing network formation, and modulating the TUG1 sponge/miRNA-21/PDCD4 axis. Silencing PDCD4 or scavenging reactive oxygen species protected endothelial cells from the negative influence of T2D-CLI CD34⁺ cells.

Migration of CD34⁺ cells predicts long-term cardiovascular mortality in T2D-CLI patients. An altered paracrine signaling conveys antiangiogenic and proapoptotic features from CD34⁺ cells to the endothelium. This damaging interaction may increase the risk for life-threatening complications.

The Action to Control Cardiovascular Risk in Diabetes Blood Pressure trial (ACCORD BP), a two-by-two factorial randomized controlled trial, examined effects of SBP (<120 vs. <140 mmHg) and glycemic (HbA_1c <6% vs. 7.0–7.9% [<42 vs. 53–63 mmol/mol]) control on cardiovascular events in T2DM (N = 4,731). We examined whether effects of SBP control on cardiovascular composite were modified by baseline DBP and glycemic control.

Intensive SBP lowering decreased the risk of the cardiovascular composite (hazard ratio [HR] 0.76 [95% CI 0.59–0.98]) in the standard glycemic arm but not in the intensive glycemic arm (HR 1.06 [95% CI 0.81–1.40]). Spline regression models relating the effects of the intervention on the cardiovascular composite across the range of baseline DBP did not show evidence of effect modification by low baseline DBP for the cardiovascular composite in the standard or intensive glycemic arms. The relation between the effect of the intensive SBP intervention and baseline DBP was similar between glycemic arms for the cardiovascular composite three-way interaction (P = 0.83).

In persons with T2DM, intensive SBP lowering decreased the risk of cardiovascular composite end point irrespective of baseline DBP in the setting of standard glycemic control. Hence, low baseline DBP should not be an impediment to intensive SBP lowering in patients with T2DM treated with guidelines recommending standard glycemic control.

We performed exploratory analyses to identify potential mediators of the effect of liraglutide on major adverse CV events (MACE; composite of CV death, nonfatal myocardial infarction, or nonfatal stroke) from the following candidates: glycated hemoglobin (HbA_1c), body weight, urinary albumin-to-creatinine ratio (UACR), confirmed hypoglycemia, sulfonylurea use, insulin use, systolic blood pressure, and LDL cholesterol. These candidates were selected as CV risk factors on which liraglutide had an effect in LEADER such that a reduction in CV risk might result. We used two methods based on a Cox proportional hazards model and the new Vansteelandt method designed to use all available information from the mediator and to control for confounding factors.

Analyses using the Cox methods and Vansteelandt method indicated potential mediation by HbA_1c (up to 41% and 83% mediation, respectively) and UACR (up to 29% and 33% mediation, respectively) on the effect of liraglutide on MACE. Mediation effects were small for other candidates.

These analyses identify HbA_1c and, to a lesser extent, UACR as potential mediators of the CV effects of liraglutide. Whether either is a marker of an unmeasured factor or a true mediator remains a key question that invites further investigation.

Blood, medical history, and personal data were collected in a substudy of 888 participants in the Sleep Apnea Cardiovascular End Points (SAVE) trial in which patients with OSA and stable CVD were randomized to receive CPAP plus usual care, or usual care alone. Serum glucose and glycated hemoglobin A_1c (HbA_1c) were measured at baseline, 6 months, and 2 and 4 years and incident diabetes diagnoses recorded.

Median follow-up was 4.3 years. In those with preexisting diabetes (n = 274), there was no significant difference between the CPAP and usual care groups in serum glucose, HbA_1c, or antidiabetic medications during follow-up. There were also no significant between-group differences in participants with prediabetes (n = 452) or in new diagnoses of diabetes. Interaction testing suggested that women with diabetes did poorly in the usual care group, while their counterparts on CPAP therapy remained stable.

Among patients with established CVD and OSA, we found no evidence that CPAP therapy over several years affects glycemic control in those with diabetes or prediabetes or diabetes risk over standard-of-care treatment. The potential differential effect according to sex deserves further investigation.