Action To Control Cardiovascular Risk In Diabetes Research Articles

Representation of Real-World Adults With Chronic Kidney Disease in Clinical Trials Supporting Blood Pressure Treatment Targets.

Little is known about how well trial participants with chronic kidney disease (CKD) represent real-world adults with CKD. We assessed the population representativeness of clinical trials supporting the 2021 Kidney Disease: Improving Global Outcomes blood pressure (BP) guidelines in real-world adults with CKD. Using a cross-sectional analysis, we identified patients with CKD who met the guideline definition of hypertension based on use of antihypertensive medications or sustained systolic BP ≥120 mm Hg in 2019 in the Veterans Affairs and Kaiser Permanente of Southern California. We applied the eligibility criteria from 3 BP target trials, SPRINT (Systolic Pressure Intervention Trial), ACCORD (Action to Control Cardiovascular Risk in Diabetes), and AASK (African American Study of Kidney Disease), to estimate the proportion of adults with a systolic BP above the guideline-recommended target and the proportion who met eligibility criteria for ≥1 trial. We identified 503 480 adults in the Veterans Affairs and 73 412 adults in Kaiser Permanente of Southern California with CKD and hypertension in 2019. We estimated 79.7% in the Veterans Affairs and 87.3% in the Kaiser Permanente of Southern California populations had a systolic BP ≥120 mm Hg; only 23.8% [23.7%-24.0%] in the Veterans Affairs and 20.8% [20.5%-21.1%] in Kaiser Permanente of Southern California were trial-eligible. Among trial-ineligible patients, >50% met >1 exclusion criteria. Major BP target trials were representative of fewer than 1 in 4 real-world adults with CKD and hypertension. A large proportion of adults who are at risk for cardiovascular morbidity from hypertension and susceptible to adverse treatment effects lack relevant treatment information.

Abstract P423: Individual and Combined Effects of Diet, Exercise, and Metformin on Risk of Microvascular Complications in Older Type 2 Diabetes Patients: Post-Hoc Analysis of Action to Control Cardiovascular Risk in Diabetes (ACCORD) Trial Data

Introduction: Microvascular complications are a major burden on the health of type 2 diabetes (T2D) patients. The literature has yielded mixed results regarding synergistic effects of common diabetes treatments (i.e., metformin, exercise, and diet) on microvascular complication risk. Some trials demonstrated that the combination of metformin and exercise diminished beneficial effects. We aimed to explore this ambiguity in findings by examining the effects of metformin, exercise, and diet on microvascular complication risk over time among T2D patients in the U.S. and Canada. Hypothesis: We hypothesize that the combined effects of metformin, exercise, and diet would be better than their individual effects on microvascular complication risk. Methods: We analyzed data from 923 participants [mean age: 62.6; 39.2% female; mean years with diabetes: 10.7] of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) (2003-2009) trial. Adequate exercise was defined as > 150 mins of moderate-intensity physical activity per week. Metformin use was defined as yes vs. no. An adequate diet score was ≤ 2.4 of the summary fat intake score (range: 0 - 5). We defined composite outcomes for microvascular complications (i.e., nephropathy, retinopathy, and neuropathy) based on several measurements including serum creatinine doubling, decrease in estimated glomerular filtration ratio (≥ 20 ml/min/1.73 m2 decrease), vision loss, Michigan Neuropathy Screening Instrument. We performed longitudinal analysis with synergy factor (SF) approach using multinomial logistic regression models adjusted for sex, diabetes years, education, alcohol, treatment arm, and baseline outcome. Results: Among individuals with poor diet score, those taking metformin but not adequate exercise had an odds ratio of 1.12 (95% CI: 0.65 - 1.94, p = 0.68) for microvascular complication. Those not taking metformin but had adequate exercise had an odds ratio of 2.71 (95% CI: 1.12 - 6.59, p < 0.05). However, taking metformin and having adequate exercise produced an odds ratio of 0.90 (95% CI: 0.49 - 1.67, p = 0.75), which was 0.30 times less than the predicted odds of the joint effect (SF = 0·30, 95% CI: 0 - 0.59, p = 0·05). Individuals with an adequate diet, adequate exercise, and taking metformin had an odds ratio of 0.85 (95% CI: 0.48 - 1.49, p = 0.57). However, we did not find these associations to be statistically significant. A similar pattern holds for individual microvascular complication outcomes. Conclusion: Additional randomized controlled trials are needed to confirm the potential additive beneficial effect of metformin, adequate exercise, and adequate diet combination over their individual effects on odds of microvascular complications.

Haptoglobin Phenotype and Intensive Glycemic Control for Coronary Artery Disease Risk Reduction in People With Type 2 Diabetes: The ADVANCE Study.

Intensive glycemic control reduced coronary artery disease (CAD) events among the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study participants with the haptoglobin (Hp)2-2 phenotype but not in participants without the Hp2-2 phenotype. It is unknown whether and how these results translate across different demographic/clinical characteristics and treatment strategies. Haptoglobin phenotype was measured in available samples from the Action in Diabetes and Vascular Disease: Preterax and Diamicron MR Controlled Evaluation (ADVANCE) biomarker case-cohort study. Weighted multivariable-adjusted Cox regression models were used to evaluate the association between intensive glycemic control (HbA1c target of ≤6.5%) versus standard therapy (based on local guidelines) and major CAD events among participants with (n = 1,327) and without (n = 2,077) the Hp2-2 phenotype separately and within prespecified stratifications by sex, race, previous cardiovascular disease (CVD), diabetes duration, and HDL-cholesterol. While the hazard ratios (HRs) were in the hypothesized differing directions, compared with standard therapy, intensive glycemic control was not significantly associated with risk of CAD events among participants without (1.04, 95% CI 0.82-1.32) or with (0.84, 0.63-1.14, Pinteraction = 0.27) the Hp2-2 phenotype overall. Intensive therapy was associated with lower CAD risk among participants with the Hp2-2 phenotype who had no previous CVD (0.47, 0.29-0.76, Pinteraction = 0.01). Our findings suggest that intensive glycemic control contributes to the prevention of major CAD events among ADVANCE participants with the Hp2-2 phenotype and no previous CVD and are in alignment with our hypothesis that intensive glycemic control may be beneficial in a subset of people with the Hp2-2 phenotype.

Cumulative blood pressure predicts risk of stroke in individuals with type 2 diabetes

AimsTo determine whether cumulative blood pressure (BP) could predict stroke in individuals with type 2 diabetes (T2D). MethodsBP levels at baseline and the initial three visits were obtained from individuals participating in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial who had not experienced a stroke. Cumulative elevations in BP were assessed by adding the weighted mean BP values at various time intervals. The association of cumulative BP with stroke was evaluated by a multivariate-adjusted Cox proportional hazard model analysis. ResultsOverall, 8282 participants were included (62.10% males and 37.90% females; mean age, 62.73 years). With a median follow-up period of 6.36 years, 324 (3.91%) and 305 (3.68%) patients had any and nonfatal stroke events, respectively. Only baseline systolic BP (SBP) independently predicted any stroke after adjustment for potential confounders, whereas cumulative SBP and pulse pressure independently predicted elevated stroke events. A strong dose–response relationship between cumulative BP and stroke was identified, and conventional risk factors combined with cumulative SBP improved prediction efficiency. ConclusionCumulative SBP independently predicts stroke in individuals with T2D and provides an incremental predictive value for stroke compared with baseline BP assessments. Trial registrationURL: http://www.clinicaltrials.gov. Unique identifier: NCT00000620)

Glycemic variability evaluated by HbA1c rather than fasting plasma glucose is associated with adverse cardiovascular events.

Although studies have shown that glycemic variability is positively associated with an increased risk of cardiovascular disease, few studies have compared hemoglobin A1c (HbA1c) and fasting plasma glucose (FPG) variability with adverse cardiovascular events in patients with type 2 diabetes mellitus (T2DM). This was a post hoc analysis of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study. Cox proportional hazards models were used to explore the relationship between HbA1c or FPG variability and the incidence of major adverse cardiovascular events (MACEs). In total, 9,547 patients with T2DM were enrolled in this study. During the median 4.6 ± 1.5 years follow-up period, 907 patients developed MACEs. The risk of MACEs increased in the HbA1c variability group in each higher quartile of HbA1c variability (P < 0.01). Compared with those in the first quartile of HbA1c variability, patients in the fourth quartile had a hazard ratio of 1.37 (Model 2, 95% confidence interval: 1.13-1.67) for MACEs. Higher FPG variability was not associated with a higher risk of MACEs in patients with T2DM (P for trend=0.28). A U-shaped relationship was observed between HbA1c and FPG variability, and MACEs. Glucose control therapy modified the relationship between HbA1c and MACEs; participants with higher HbA1c variability receiving intensive glucose control were more likely to develop MACEs (P for interaction <0.01). In adults with T2DM, the relationship between glycemic variability evaluated using HbA1c and FPG was U-shaped, and an increase in HbA1c variability rather than FPG variability was significantly associated with MACEs. The relationship between HbA1c variability and MACEs was affected by the glucose control strategy, and a higher HbA1c variability was more strongly associated with MACEs in patients receiving an intensive glucose control strategy.

Some patients with type 2 diabetes may benefit from intensive glycaemic and blood pressure control: A post-hoc machine learning analysis of ACCORD trial data.

The action to control cardiovascular risk in diabetes (ACCORD) trial showed a neutral average treatment effect of intensive blood glucose and blood pressure (BP) controls in preventing major adverse cardiovascular events (MACE) in individuals with type 2 diabetes. Yet, treatment effects across patient subgroups have not been well understood. We aimed to identify patient subgroups that might benefit from intensive glucose or BP controls for preventing MACE. As a post-hoc analysis of the ACCORD trial, we included 10 251 individuals with type 2 diabetes. We applied causal forest and causal tree models to identify participant characteristics that modify the efficacy of intensive glucose or BP controls from 68 candidate variables (demographics, comorbidities, medications and biomarkers) at the baseline. The exposure was (a) intensive versus standard glucose control [glycated haemoglobin (HbA1c) <6.0% vs. 7.0%-7.9%], and (b) intensive versus standard BP control (systolic BP <120 vs. <140 mmHg). The primary outcome was MACE. Compared with standard glucose control, intensive one reduced MACE in those with baseline HbA1c <8.5% [relative risk (RR): 0.79, 95% confidence interval (CI): 0.67-0.93] and those with estimated glomerular filtration rate ≥106 ml/min/1.73 m2 (RR: 0.74, 95% CI: 0.55-0.99). Intensive BP control reduced MACE in those with normal high-density lipoprotein levels (women >55 mg/dl, men >45 mg/dl; RR: 0.51, 95% CI: 0.34-0.74). Risk reductions were not significant in other patient subgroups. Our findings suggest heterogeneous treatment effects of intensive glucose and BP control and could provide biomarkers for future clinical trials to identify more precise HbA1c and BP treatment goals for individualized medicine.

Poor glycemic control is associated with more rapid kidney function decline after the onset of diabetic kidney disease.

The role of glycemic control and its variability on the rate of kidney function decline after the onset of diabetic kidney disease (DKD) remains unclear. The association between baseline HbA1c and rates of estimated GFR (eGFR) loss during follow-up was examined by mixed-effects linear regression in 530 individuals with type 1 diabetes and early-to-moderate DKD from the Preventing Early Renal Loss (PERL) trial, and 2,378 individuals with type 2 diabetes and established DKD from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. The benefit of intensive vs. standard glycemic control in slowing eGFR decline was examined in ACCORD. The associations between continuous glucose monitoring-derived short-term glycemic variability indices and rate of GFR decline were also evaluated in PERL. A higher baseline HbA1c was associated with a more negative eGFR slope in both PERL and ACCORD (-0.87 and -0.27 ml/min/1.73m2/year per Hba1c unit increment, p<0.0001 and p=0.0002, respectively). In both studies, the strength of this association progressively increased with increasing levels of albuminuria (p for interaction <0.05). Consistent with this, the benefit of intensive glycemic control on eGFR decline was greater in ACCORD participants with severe than in those with moderate albuminuria (+1.13 vs. +0.26 ml/min/1.73 m2/year, p=0.01). No independent associations were found in PERL between short-term glycemic variability indices and rate of eGFR decline. In both type 1 and type 2 diabetes, poor glycemic control is associated with a more rapid rate of GFR decline after DKD onset, especially in persons with severe albuminuria.

Effects of intensive glycemic control on microvascular outcomes in type 2 diabetes mellitus are modified by long-term HbA1c variability: A post hoc analysis of the ACCORD trial

AimsTo assess the impact of long-term visit-to-visit variability in HbA1c on microvascular outcomes in type 2 diabetes mellitus (T2DM), and its influence on the effects of intensive glycemic control. MethodsIncluded were participants with T2DM enrolled in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) who had at least three measurements of HbA1c prior to new-onset microvascular outcomes, namely nephropathy, retinopathy and neuropathy. Variability in HbA1c was defined as the coefficient of variation (CV) across HbA1c measurements obtained from enrollment to the transition from intensive to standard glycemic therapy. ResultsDuring a median of 22,005, 23,121, and 13,080 person-years of follow-up, 2,905 nephropathy, 2,655 retinopathy, and 1,974 neuropathy cases were recorded, respectively. Median CV (IQR) was 7.91 % (5.66 %-10.76 %) in the standard treatment group and 9.79 % (7.32 %-13.35 %) in the intensive treatment group. In the standard treatment group, lower HbA1c-CV (the first versus the second quartile) was associated with a higher risk of all microvascular outcomes, while higher HbA1c-CV (the fourth quartile) was associated with a higher risk of nephropathy only. In the intensive treatment group, only higher HbA1c-CV was associated with a higher risk of developing the microvascular outcomes. Intensive therapy reduced all microvascular outcomes among individuals with lower HbA1c-CV, but increased the risk among those with the highest HbA1c-CV (all P values for interaction < 0.0001). For example, hazard ratios (95 % CI) of retinopathy comparing intensive with standard treatments were 0.65 (0.56–0.75), 0.84 (0.71–0.98), 0.97 (0.82–1.14) and 1.28 (1.08–1.53) across the lowest to the highest quartiles of HbA1c variability. ConclusionsThe effects of intensive glycemic control on microvascular outcomes in T2DM appear to be modified by the variability of HbA1c during the treatment process, suggesting the significance of dynamic monitoring of HbA1c levels and timely adjustments to the therapeutic strategy among individuals with a high HbA1c variability.

Interplay of heart rate variability and resting heart rate on mortality in type 2 diabetes

AimsHeart rate variability (HRV) and resting heart rate (RHR) are usually analyzed and interpreted separately. We aimed to assess the interplay of HRV and RHR on mortality in type 2 diabetes. MethodsThe study included 7,529 participants from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. HRV metrics included standard deviation of all normal-to-normal intervals (SDNN) and root mean square of successive differences between normal-to-normal intervals (rMSSD). Abnormal values were defined based on <25th percentile for HRV and >75th percentile for RHR. Interactions of HRV status and RHR status were tested on multiplicative and additive scales. Results were validated in a subset of patients with type 2 diabetes (n = 745) from the Multi-Ethnic Study of Atherosclerosis. ResultsLow SDNN was associated with increased all-cause mortality in the high RHR group (HR 1.60; 95% CI 1.29–1.97), but not in the normal RHR group. Compared with those who had neither low SDNN nor high RHR, the presence of either low SDNN or high RHR was not significantly associated with an increased risk of all-cause mortality. In contrast, the combination of low SDNN and high RHR was associated with a significantly increased risk of all-cause mortality (HR 1.68; 95% CI 1.43–1.97). Significant multiplicative and additive interactions were found between HRV status and RHR status on risk of all-cause mortality (all Pinteraction < 0.05). Similar findings were observed for cardiovascular mortality, in analyses using rMSSD, and in the Multi-Ethnic Study of Atherosclerosis. ConclusionsThe association between HRV and mortality risk is modified by RHR levels. Furthermore, low HRV and high RHR have interdependent and synergistic associations with mortality risk.

Cumulative HbA1c exposure as a CVD risk in patients with type 2 diabetes: A post hoc analysis of ACCORD trial

AimsThe study aimed to investigate the relationship between cumulative HbA1c exposure and cardiovascular events in patients with type 2 diabetes (T2D). MethodsThis study included 9307 participants from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Cumulative HbA1c exposure was calculated as the area under the curve during exposure time. ResultsAfter adjusting for covariates, a 1-SD increase in cumulative HbA1c exposure was significantly associated with a higher risk of the primary outcome (HR 1.32, 95 % CI: 1.22–1.43, P < 0.001), all-cause mortality (HR 1.33, 95 % CI: 1.21–1.46, P < 0.001), and cardiovascular death (HR 1.45, 95 % CI: 1.27–1.67, P < 0.001). These associations were independent of baseline HbA1c and the first HbA1c level after enrollment. Cross-tabulation analysis showed that participants in the intensive-therapy group with high baseline HbA1c and cumulative HbA1c exposure had a significantly higher risk of primary outcome, all-cause mortality and cardiovascular death. ConclusionsHigher cumulative HbA1c exposure was significantly associated with an increased risk of the primary outcome, all-cause mortality and cardiovascular death among T2D patients. Patients with T2D should strive for stable glycemic control to reduce their risk of cardiovascular events, and that those with high baseline HbA1c may require more intensive therapy to achieve this goal.

Abstract 16426: A Risk Model to Predict Atrial Fibrillation in Diabetes Using Machine Learning: The ACCORD Study

Introduction: Atrial fibrillation (AF) is the most common cardiac arrhythmia seen in clinical practice, which necessitates identifying factors that can precipitate this dysrhythmia. We utilized the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial to build an AF risk prediction model specifically in the type 2 diabetes (T2DM) population, using machine learning (ML) approaches, and comparing to the established CHARGE-AF risk model. Methods: We utilized a patient cohort from the ACCORD clinical trial without prior AF. Baseline characteristics were collected as potential risk factors and incident AF was defined from ECG at follow-up. A random forest (RF) binary classifier was trained with 27 variables, including age, race, sex, smoking, waist circumference, BMI, blood pressure (BP), history of heart disease, medications, cholesterol, renal function, and left ventricular hypertrophy by ECG. All ACCORD subjects had T2DM, therefore this variable was not included. The CHARGE-AF model consisted of a Cox proportional hazard model trained on the following variables: age, race, height, weight, systolic/diastolic BP, current smoking, heart failure, prior MI, and BP medication. Area under ROC curve (AUC) was measured with randomized, stratified, 5-fold cross validation with 80/20 splits. Imputation and resampling methods were used for missing data and class imbalance. Results: Out of 9307 patients in the ACCORD cohort, 175 developed AF during the study period of 6.26 years, with a mean time to AF event of 3.68 years. The RF model, with an AUC of 0.912, showed improved prediction of AF over the Cox model, which had an AUC of 0.784. Permutation feature importance revealed age, race, waist circumference, weekly alcohol consumption, sex, and GFR as the most predictive features of the RF model (Fig 1). Conclusions: The CHARGE-AF risk model performed modestly on the ACCORD cohort, while a RF model showed superior performance.

Association of Urine Albumin to Creatinine Ratio With Cardiovascular Outcomes in Patients With Type 2 Diabetes Mellitus.

The urinary albumin to creatinine ratio (UACR) is a widely used indicator of albuminuria and has predictive value for adverse cardiovascular events. To evaluate the correlation between the UACR and the risk of developing major adverse cardiovascular events (MACEs) and total mortality in patients with type 2 diabetes mellitus (T2DM). This post hoc analysis included 10 171 participants from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study and the ACCORD follow-up study (ACCORDION) with baseline UACR data. The natural logarithm (ln) of each UACR measurement was calculated. Univariate and multivariate Cox proportional hazard regression analyses were conducted to examine the association between the UACR and the risk of MACEs and total mortality. The additional predictive value of UACR was further evaluated. Similar methods were used to analyze the correlation between the UACR and MACEs and total mortality within the normal range. During a median follow-up period of 8.83 years, 1808 (17.78%) participants experienced MACEs, and there were 1934 (19.01%) total deaths. After adjusting for traditional cardiovascular risk factors, the multivariate analysis revealed a significant association between the UACR and the risk of MACEs and total mortality. The inclusion of UACR in the conventional risk model enhanced the predictive efficacy for MACEs and total mortality. An elevated UACR is associated with a higher risk of MACEs and total mortality in patients with T2DM, even when it falls within the normal range. The UACR improves prediction of MACE and total mortality risk in patients with T2DM.

Cardiac Autonomic Dysfunction and Risk of Silent Myocardial Infarction Among Adults With Type 2 Diabetes.

Background There is a paucity of large-scale epidemiological studies on the link between cardiac autonomic neuropathy (CAN) and the risk of silent myocardial infarction (SMI) in type 2 diabetes. We evaluated the association between CAN and the risk of SMI in a large sample of adults with type 2 diabetes. Methods and Results Participants with type 2 diabetes from the ACCORD (Action to Control Cardiovascular Risk in Diabetes) study without atherosclerotic cardiovascular disease at baseline were included. CAN was ascertained using heart rate variability indices calculated from 10-s resting electrocardiograms. The heart rate variability indices included standard deviation of all normal-to-normal R-R intervals and root mean square of successive differences between normal-to-normal R-R intervals. CAN was defined as both the standard deviation of all normal-to-normal R-R intervals and root mean square of successive differences between normal-to-normal R-R intervals less than the fifth percentile of the general population. We used Cox proportional hazards regression to generate hazard ratios (HRs) for incident SMI in relation to CAN measures. Among 4842 participants (mean age, 62.5 years; 46.6% women; 60.2% White), there were 73 incident SMI cases over a median follow-up of 4.9 years (incidence rate 3.1 out of 1000 person-years [95% CI, 2.5-3.9]). After adjusting for confounders, low heart rate variability was associated with a higher risk of SMI (HR, 1.67 [95% CI, 1.02-2.72] and HR, 1.56 [95% CI, 0.94-2.58] for low standard deviation of all normal-to-normal R-R intervals and root mean square of successive differences between normal-to-normal R-R intervals, respectively). Participants with CAN had a 1.9-fold greater risk of SMI (HR, 1.91 [95% CI, 1.14-3.20]). Conclusions In a large cohort of adults with type 2 diabetes, CAN was significantly associated with an increased risk of incident SMI.

Racial/ethnic and socioeconomic disparities in achievement of treatment goals within a clinical trial: a secondary analysis of the ACCORD trial.

Clinical trial participation should theoretically reduce barriers to care by ensuring medication and healthcare access. We aimed to evaluate disparities in achieving diabetes treatment targets by race/ethnicity and educational attainment within the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (ClinicalTrials.gov NCT00000620). The ACCORD trial included three interventions of varying participant burden: glycaemic (high burden), blood pressure (medium burden) and triglyceride-lowering (low burden). We examined adjusted odds ratios (aORs) for achievement of glycaemic targets, blood pressure targets and a ≥25% reduction in triglyceride levels (a proxy for adherence to fenofibrate therapy) in the first year, and for hypoglycaemia requiring medical assistance at any time, by treatment arm, race/ethnicity and educational attainment using multivariable models adjusted for demographics and clinical characteristics. We explored whether disparities in glycaemic goal achievement were mediated by hypoglycaemia, medication use, change in BMI or number of study visits attended. Compared with White participants, participants who identified as Black, Hispanic and Other race/ethnicity were less likely to achieve glycaemic targets (aOR [95% CI]) 0.63 [0.55,0.71], 0.73 [0.61, 0.88], 0.82 [0.71, 0.96], respectively); Black participants but not Hispanic and Other race/ethnicity participants were less likely to achieve blood pressure targets (aOR [95% CI] 0.77 [0.65, 0.90], 1.01 [0.78, 1.32], 1.01 [0.81, 1.26], respectively); and Black, Hispanic and Other race/ethnicity participants were equally or more likely to achieve triglyceride reduction (aOR [95% CI] 1.77 [1.38, 2.28], 1.34 [0.98, 1.84], 1.43 [1.10, 1.85], respectively). Differences in goal achievement by educational attainment were generally not significant after adjusting for baseline characteristics. Rates of hypoglycaemia requiring medical assistance were highest among Black individuals and those with lower educational attainment. Associations between race/ethnicity and glycaemic control were partially mediated by differences in insulin dosing and oral medication use. Racially/ethnically minoritised participants in the ACCORD trial were less likely to achieve high-burden (glycaemic) treatment goals but were generally similarly likely to achieve goals of less intensive interventions. Differences in glycaemic treatment goal achievement were partially mediated by differences in medication use but not mediated by hypoglycaemia, change in BMI or study visit attendance.

Intensive Glycemic Therapy in Type 2 Diabetes Patients With Cardiac Autonomic Dysfunction: The ACCORD Trial

ObjectiveTo assess whether the presence of cardiac autonomic dysfunction denoted by low heart rate variability (HRV) modifies the effect of intensive glycemic therapy on outcomes in patients with type 2 diabetes. Patients and MethodsThis study included 7946 participants in the ACCORD (Action to Control Cardiovascular Risk in Diabetes) trial from January 2001 through June 2009. Heart rate variability measures included standard deviation of all normal-to-normal intervals (SDNN) and root mean square of successive differences between normal-to-normal intervals (rMSSD). Abnormal values were defined based on less than the 10th percentile for SDNN and rMSSD. ResultsCompared with standard therapy, intensive therapy was associated with improved primary outcome (composite of cardiovascular events) in the low-HRV group (SDNN: HR, 0.57; 95% CI, 0.39 to 0.84; rMSSD: HR, 0.57; 95% CI, 0.38 to 0.84), but not in the normal-HRV group (SDNN: HR, 0.90; 95% CI, 0.77 to 1.05; rMSSD: HR, 0.90; 95% CI, 0.77 to 1.05). A similar pattern was found for coronary heart disease. Conversely, intensive therapy had a neutral effect on all cause death in the low-HRV group (SDNN: HR, 0.88; 95% CI, 0.54 to 1.41; rMSSD: HR, 0.71; 95% CI, 0.43 to 1.17;), but increase risk of all-cause death in the normal-HRV group (SDNN: HR, 1.21; 95% CI, 1.00 to 1.46; rMSSD: HR, 1.25; 95% CI, 1.03 to 1.51). Intensive therapy induced a greater risk of hypoglycemia in the normal-HRV group than that in the low-HRV group. ConclusionCardiac autonomic dysfunction expressed as low HRV identified subpopulations in ACCORD with more benefits and less harms from intensive therapy.

The Relationship Between Time-Varying Achieved HbA1c and Risk of Coronary Events Depends on Haptoglobin Phenotype Among White and Black ACCORD Participants.

Intensive glycemic therapy reduced coronary artery disease (CAD) events among White participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study with the haptoglobin (Hp)2-2 phenotype, while participants without the Hp2-2 phenotype had no CAD benefit. The association between achieved glycated hemoglobin (HbA1c) and CAD for each Hp phenotype remains unknown. Achieved HbA1c was similar in each phenotype throughout the study. Prospectively collected HbA1c data (categorized as <6.0%, 6.0-6.5%, 6.6-6.9%, or ≥8.0% compared with 7.0-7.9%) from the ACCORD study, updated every 4 months over a median of 4.7 years, were analyzed in relation to CAD in the Hp2-2 (n = 3,322) and non-Hp2-2 (n = 5,949) phenotypes separately overall, and within White (63%, 37% Hp2-2) and Black (19%, 26% Hp2-2) participants using Cox proportional hazards regression with time-varying covariables. Compared with HbA1c of 7.0-7.9%, having HbA1c ≥8.0% was associated with CAD risk among White (adjusted HR [aHR] 1.43, 95% CI 1.03-1.98) and Black (2.86, 1.09-7.51) participants with the Hp2-2 phenotype, but not when all Hp2-2 participants were combined overall (1.30, 0.99-1.70), and not among participants without the Hp2-2 phenotype. HbA1c <7.0% was not associated with a lower risk of CAD for any Hp phenotype. Achieving HbA1c >8.0% compared with 7.0-7.9% was consistently associated with incident CAD risk among White and Black ACCORD participants with the Hp2-2 phenotype, while no association was observed among participants without the Hp2-2 phenotype. We found no evidence that HbA1c concentration <7.0% prevents CAD in either Hp phenotype group.

Cardiovascular Autonomic Neuropathy and Risk of Kidney Function Decline in Type 1 and Type 2 Diabetes: Findings From the PERL and ACCORD Cohorts.

Previous studies have suggested that cardiovascular autonomic neuropathy (CAN) may predict rapid kidney function decline among persons with diabetes. We analyzed the association between baseline CAN and subsequent glomerular filtration rate (GFR) decline among individuals with type 1 diabetes (T1D) from the Preventing Early Renal Loss in Diabetes (PERL) study (N=469) and with type 2 diabetes (T2D) from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study (N=7,973). Baseline CAN was ascertained using ECG-derived heart rate variability indices. Its association with GFR slopes, rapid kidney function decline (GFR loss ≥-5 ml/min/1.73 m2/year), and ≥40% GFR loss was evaluated by linear mixed effect, logistic, and Cox regression, respectively. Participants with CAN experienced more rapid GFR decline, by an excess 1.15 (95%CI [-1.93, -0.37], P= 4.0x10-3) ml/min/1.73m2/year in PERL and 0.34 (95%CI [-0.49, -0.19], P= 6.3x10-6) ml/min/1.73m2/year in ACCORD. This translated in 2.11 (95% CI [1.23-3.63], P=6.9x10-3) and 1.39 (95% CI [1.20-1.61], P=1.1x10-5) odds ratios of rapid kidney function decline in PERL and ACCORD, respectively. Baseline CAN was also associated with a greater risk of ≥40% GFR loss events during follow-up (HR=2.60, 95%CI [1.15-5.45], p=0.02 in PERL and HR=1.54, 95%CI [1.28-1.84], P=3.8×10-6 in ACCORD). These associations remained significant after adjustment for potential confounders, including baseline GFR and albuminuria. Our findings indicate that CAN is a strong, independent predictor of rapid kidney function decline in both T1D and T2D. Further studies of the link between these two complications may help develop new therapies to prevent kidney function decline in patients with diabetes.

Diastolic and systolic blood pressure time in target range as a cardiovascular risk marker in patients with type 2 diabetes: A post hoc analysis of ACCORD BP trial

AimsWe investigated the associations between time in target range (TTR) of blood pressure (BP) and cardiovascular outcomes in patients with diabetes. Methods4651 participants from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) BP trial were included in the present study. The diastolic BP target range was defined as 70 to 80 mm Hg, and the systolic as 120 to 140 mm Hg and 110 to 130 mm Hg for the standard and intensive therapy, respectively. ResultsAfter adjusting for covariates, 1-SD increase of diastolic TTR was significantly associated with lower risks of primary outcome (HR 0.82, 95% CI: 0.74–0.91, P < 0.001; HR 0.86, 95% CI: 0.77–0.95, P = 0.0044, as well as nonfatal myocardial infarction (HR 0.79, 95% CI: 0.69–0.91, P < 0.001). Meanwhile, systolic TTR was significantly associated with various cardiovascular outcomes (P ≤ 0.016) in fully-adjusted models. The diastolic TTR sustained significance in myocardial infarction when systolic blood pressure average was higher than 120 mm Hg. ConclusionsIn patients with diabetes, TTR of diastolic and systolic BP was independently associated with lower risks of major outcomes. The diastolic BP within the optimal target range was considerably important for reducing the risk of myocardial infarction, even when systolic BP was under stable control.

Development and Validation of an Electronic Health Record-Based Risk Assessment Tool for Hypoglycemia in Patients With Type 2 Diabetes Mellitus.

The recent availability of high-quality data from clinical trials, together with machine learning (ML) techniques, presents exciting opportunities for developing prediction models for clinical outcomes. As a proof-of-concept, we translated a hypoglycemia risk model derived from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study into the HypoHazardScore, a risk assessment tool applicable to electronic health record (EHR) data. To assess its performance, we conducted a 16-week clinical study at the University of Minnesota where participants (N = 40) with type 2 diabetes mellitus (T2DM) had hypoglycemia assessed prospectively by continuous glucose monitoring (CGM). The HypoHazardScore combines 16 risk factors commonly found within the EHR. The HypoHazardScore successfully predicted (area under the curve [AUC] = 0.723) whether participants experienced least one CGM-assessed hypoglycemic event (glucose <54 mg/dL for ≥15 minutes from two CGMs) while significantly correlating with frequency of CGM-assessed hypoglycemic events (r = 0.38) and percent time experiencing CGM-assessed hypoglycemia (r = 0.39). Compared to participants with a low HypoHazardScore (N = 19, score <4, median score of 4), participants with a high HypoHazardScore (N = 21, score ≥4) had more frequent CGM-assessed hypoglycemic events (high: 1.6 ± 2.2 events/week; low: 0.3 ± 0.5 events/week) and experienced more CGM-assessed hypoglycemia (high: 1.4% ± 2.0%; low: 0.2% ± 0.4% time) during the 16-week follow-up. We demonstrated that a hypoglycemia risk model can be successfully adapted from the ACCORD data to the EHR, with validation by a prospective study using CGM-assessed hypoglycemia. The HypoHazardScore represents a significant advancement toward implementing an EHR-based decision support system that can help reduce hypoglycemia in patients with T2DM.

Rapid kidney function decline and increased risk of heart failure in patients with type 2 diabetes: findings from the ACCORD cohort

BackgroundImpaired kidney function and albuminuria are associated with increased risk of heart failure (HF) in patients with type 2 diabetes (T2D). We investigated whether rapid kidney function decline over time is an additional determinant of increased HF risk in patients with T2D, independent of baseline kidney function, albuminuria, and other HF predictors.MethodsIncluded in the study were 7,539 participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study with baseline urinary albumin-to-creatinine ratio (UACR) data, who had completed 4 years of follow-up and had ≥ 3 eGFR measurements during that period (median eGFR/year = 1.9, IQR 1.7–3.2). The association between rapid kidney function decline (eGFR loss ≥ 5 ml/min/1.73 m2/year) and odds of HF hospitalization or HF death during the first 4 years of follow-up was estimated by logistic regression. The improvement in risk discrimination provided by adding rapid kidney function decline to other HF risk factors was evaluated as the increment in the area under the Receiving Operating Characteristics curve (ROC AUC) and integrated discrimination improvement (IDI).ResultsOver 4 years of follow-up, 1,573 participants (20.9%) experienced rapid kidney function decline and 255 (3.4%) experienced a HF event. Rapid kidney function decline was associated with a ~ 3.2-fold increase in HF odds (3.23, 95% CI, 2.51–4.16, p < 0.0001), independent of baseline CVD history. This estimate was not attenuated by adjustment for potential confounders, including eGFR and UACR at baseline as well as at censoring (3.74; 95% CI 2.63–5.31). Adding rapid kidney function decline during follow-up to other clinical predictors (WATCH-DM score, eGFR, and UACR at study entry and end of follow-up) improved HF risk classification (ROC AUC = + 0.02, p = 0.027; relative IDI = + 38%, p < 0.0001).ConclusionsIn patients with T2D, rapid kidney function decline is associated with a marked increase in HF risk, independent of starting kidney function and/or albuminuria. These findings highlight the importance of serial eGFR measurements over time to improve HF risk estimation in T2D.