Age-specific associations of glycated haemoglobin variability with cardiovascular disease and mortality in patients with type 2 diabetes mellitus: A 10- year cohort study

The association of glycaemic risk factors and diabetes duration with risk of heart failure in people with type 2 diabetes: A systematic review and meta-analysis

AIMS

To conduct a systematic review in order to better understand the association of glycaemic risk factors and diabetes duration with risk of heart failure (HF) in individuals with type 2 diabetes (T2D).

METHODS

We identified longitudinal studies investigating the association of glycaemic factors (glycated haemoglobin [HbA1c], HbA1c variability, and hypoglycaemia) and diabetes duration with HF in individuals with T2D. Hazard ratios and odds ratios were extracted and meta-analysed using a random-effects model where appropriate. Risk of bias assessment was carried out using a modified Newcastle-Ottawa Scale. Egger's test along with the trim-and-fill method were used to assess and account for publication bias.

RESULTS

Forty studies representing 4 102 589 people met the inclusion criteria. The risk of developing HF significantly increased by 15% for each percentage point increase in HbA1c, by 2% for each additional year of diabetes duration, and by 43% for having a history of severe hypoglycaemia. Additionally, variability in HbA1c levels was associated with a 20%-26% increased risk of HF for each unit increase in the metrics of variability (HbA1c standard deviation, coefficient of variation, and average successive variability). All included studies scored high in the risk of bias assessment. Egger's test suggested publication bias, with trim-and-fill analyses revealing a significant 14% increased risk of HF per percentage point increase in HbA1c.

CONCLUSIONS

Glycaemic risk factors and diabetes duration significantly contribute to the heightened risk of HF among individuals with T2D. A reduction in risk of HF is anticipated with better management of glycaemic risk factors.

The association of haemoglobin A1c variability with adverse outcomes in patients with atrial fibrillation prescribed anticoagulants

AIMS

The association of haemoglobin A1c (HbA1c) variability with the risk of adverse outcomes in patients with atrial fibrillation (AF) prescribed anticoagulants remains unclear. This study aimed to evaluate the association of HbA1c variability with the risk of ischaemic stroke (IS)/systemic embolism (SE) and all-cause mortality among patients with non-valvular AF prescribed anticoagulants.

METHODS AND RESULTS

Patients newly diagnosed with AF from 2013 to 2018 were included. Variability in HbA1c, indexed by the coefficient of variation (CV), was determined for those with at least three HbA1c measurements available from the time of study enrolment to the end of follow-up. To evaluate whether prevalent diabetes would modify the relationship between HbA1c variability and outcomes, participants were divided into diabetes and non-diabetes groups. The study included 8790 patients (mean age 72.7% and 48.5% female). Over a median follow-up of 5.5 years (interquartile range 5.2, 5.8), the incident rate was 3.74 per 100 person-years for IS/SE and 4.89 for all-cause mortality in the diabetes group. The corresponding incident rates in the non-diabetes group were 2.41 and 2.42 per 100 person-years. In the diabetes group, after adjusting for covariates including mean HbA1c, greater HbA1c variability was significantly associated with increased risk of IS/SE [hazard ratio (HR) = 1.65, 95% confidence interval (CI): 1.27-2.13) and all-cause mortality (HR = 1.24, 95% CI: 1.05-1.47) compared with the lowest CV tertile. A similar pattern was evident in the non-diabetes group (IS/SE: HR = 1.58, 95% CI: 1.23-2.02; all-cause mortality: HR = 1.35, 95% CI: 1.10-1.64).

CONCLUSION

Greater HbA1c variability was independently associated with increased risk of IS/SE and all-cause mortality among patients with AF, regardless of diabetic status.

Management of Type 2 Diabetes Mellitus: Synopsis of the Department of Veterans Affairs and Department of Defense Clinical Practice Guideline

The US Department of Veterans Affairs (VA) and the US Department of Defense (DoD) approved a joint clinical practice guideline for the management of type 2 diabetes. This was the product of a multidisciplinary guideline development committee composed of clinicians from both the VA and the DoD and was overseen by the VA/DoD Evidence Based Practice Work Group. The development process conformed to the standards for trustworthy guidelines as established by the National Academy of Medicine. The guideline development committee developed 12 key questions to guide an evidence synthesis. An independent third party identified relevant randomized controlled trials and systematic reviews that were published from January 2016 through April 2022. This evidence synthesis served as the basis for drafting recommendations. Twenty-six recommendations were generated and rated by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) system. Two algorithms were developed to guide clinical decision-making. This synopsis summarizes key aspects of the VA/DoD Clinical Practice Guideline for diabetes in 5 areas: prediabetes, screening for co-occurring conditions, diabetes self-management education and support, glycemic treatment goals, and pharmacotherapy. The guideline is designed to help clinicians and patients make informed treatment decisions to optimize health outcomes and quality of life and to align with patient-centered goals of care.

Intensified glycemic control by HbA1c for patients with coronary heart disease and Type 2 diabetes: a review of findings and conclusions

The occurrence and development of coronary heart disease (CHD) are closely linked to fluctuations in blood glucose levels. While the efficacy of intensified treatment guided by HbA1c levels remains uncertain for individuals with diabetes and CHD, this review summarizes the findings and conclusions regarding HbA1c in the context of CHD. Our review showed a curvilinear correlation between regulated level of HbA1c and therapeutic effectiveness of intensified glycemic control among patients with type 2 diabetes and coronary heart disease. It is necessary to optimize the dynamic monitoring indicators of HbA1c, combine genetic profiles, haptoglobin phenotypes for example and select more suitable hypoglycemic drugs to establish more appropriate glucose-controlling guideline for patients with CHD at different stage of diabetes.

Random Blood Glucose, but Not HbA1c, Was Associated with Mortality in COVID-19 Patients with Type 2 Diabetes Mellitus—A Retrospective Study

Previous studies have yielded inconsistent results on whether glycated hemoglobin (HbA1c) and random blood glucose (RBG) are associated with mortality of coronavirus disease 2019 (COVID-19) patients with type 2 diabetes mellitus (T2DM). This study aimed to assess the association of HbA1c and RBG with mortality among COVID-19 patients with T2DM. A retrospective study was conducted on 237 patients with COVID-19 and T2DM (survival (n = 169) and non-survival groups (n = 68)). Data on socio-demography, comorbidities, clinical symptoms, laboratory examination, and mortality were collected. Patients in the non-survival group had an older age range as compared with those in the survival group (60 (52.3–65.0) vs. 56.0 (48.5–61.5) years, p = 0.009). There was no statistical gender difference between the two groups. After matching was done, chronic kidney disease, NLR, d-dimer, procalcitonin, and random blood glucose were higher in the non-survival group compared to the survival group (p < 0.05). HbA1c levels were similar in survivors and non-survivors (8.7% vs. 8.9%, p=0.549). The level of RBG was independently associated with mortality of COVID-19 patients with T2DM (p = 0.003, adjusted OR per 1-SD increment 2.55, 95% CI: 1.36–4.76). In conclusion, RBG was associated with the mortality of COVID-19 patients with T2DM, but HbA1c was not.

Long-term HbA1c variability and macro-/micro-vascular complications in type 2 diabetes mellitus: a meta-analysis update

AIMS

The aim of the present study was to evaluate, by means of a meta-analysis approach, whether new available data, appeared on qualified literature, can support the effectiveness of an association of HbA1c variability with the risk of macro- and/or micro-vascular complications in type 2 diabetes mellitus (T2DM).

METHODS

The meta-analysis was conducted according to PRISMA Statement guidelines and considered published studies on T2DM, presenting HbA1c variability as standard deviation (SD) or its derived coefficient of variation (CV). Literature search was performed on PubMed in the time range 2015-July 2022, with no restrictions of language.

RESULTS

Twenty-three selected studies fulfilled the aims of the present investigation. Overall, the analysis of the risk as hazard ratios (HR) indicated a significant association between the HbA1c variability, expressed either as SD or CV, and the complications, except for neuropathy. Macro-vascular complications were all significantly associated with HbA1c variability, with HR 1.40 (95%CI 1.31-1.50, p < 0.0001) for stroke, 1.30 (95%CI 1.25-1.36, p < 0.0001) for transient ischaemic attack/coronary heart disease/myocardial infarction, and 1.32 (95%CI 1.13-1.56, p = 0.0007) for peripheral arterial disease. Micro-vascular complications yielded HR 1.29 (95%CI 1.22-1.36, p < 0.0001) for nephropathy, 1.03 (95%CI 0.99-1.08, p = 0.14) for neuropathy, and 1.15 (95%CI 1.08-1.24, p < 0.0001) for retinopathy. For all-cause mortality, HR was 1.33 (95%CI 1.27-1.39, p < 0.0001), and for cardiovascular mortality 1.25 (95%CI 1.17-1.34, p < 0.0001).

CONCLUSIONS

Our meta-analysis on HbA1c variability performed on the most recent published data since 2015 indicates positive association between HbA1c variability and macro-/micro-vascular complications, as well as mortality events, in T2DM, suggesting that this long-term glycaemic parameter merits further attention as a predictive, independent risk factor for T2DM population.

Association of visit-to-visit HbA1c variability with cardiovascular diseases in type 2 diabetes within or outside the target range of HbA1c

Background

Although a growing attention has been recently paid to the role of HbA1c variability in the risk of diabetic complications, the impact of HbA1c variability on cardiovascular diseases (CVD) in type 2 diabetes is still debated. The aim of the study is to investigate the association of HbA1c variability with CVD in individuals within or outside the target range of HbA1c.

Methods

Using data from Action in Diabetes and Vascular disease: preterAx and diamicroN-MR Controlled Evaluation (ADVANCE), we enrolled 855 patients with type 2 diabetes in China. The primary outcomes included major macrovascular events and major microvascular events. Visit-to-visit HbA1c variability was expressed as the coefficient of variation (CV) of five measurements of HbA1c taken 3-24 months after treatment. Cox proportional hazard models were used to estimate adjusted hazard ratios (aHR).

Results

Among 855 patients in the intensive glucose treatment group, 563 and 292 patients were assigned to the group of "within the target range of HbA1c" (WTH) (updated mean HbA1c ≤ 7.0%) and "outside the target range of HbA1c" (OTH) (updated mean HbA1c > 7.0%), respectively. HbA1c variability was positively associated with the risk of major microvascular events in all patients and both the subgroups during a median follow-up period of 4.8 years. Particularly, the risk related to HbA1c variability was higher in patients in WTH group for the new or worsening nephropathy [aHR: 3.35; 95% confidence interval (CI): 1.05-10.74; P = 0.042].

Conclusions

This retrospective cohort study confirmed the positive correlation between HbA1c variability and major microvascular events, especially in subjects in WTH or OTH.

Influence of Self-Practice Oriented Teaching plus Psychological Intervention on Blood Glucose Level and Psychological State in Patients with Type 2 Diabetes Mellitus on Insulin Therapy

Background. The study aimed to examine the effect of self-practice oriented teaching plus psychological intervention on blood glucose level and psychological status of type 2 diabetic patients on first insulin therapy. Methods. A total of 80 patients with type 2 diabetes admitted from April 2020 to November 2020 were assessed for eligibility and included. They were then assigned to a control group and an observation group via the random number table method, with 40 cases in each group. In addition to insulin injection treatment in both groups prior to intervention, the control group received health education and psychological intervention, whereas the observation group adopted a self-practice oriented teaching strategy plus psychological intervention. Insulin injections, nursing satisfaction, blood glucose level, and disease awareness were compared between the two groups. The Exercise of Self-Care Agency (ESCA) scale was used to assess the patients’ self-care ability, the Generic Quality of Life Inventory-74 (GQOLI-74) scale was used to assess their quality of life, and the emotional state of patients was evaluated by the Hospital Anxiety and Depression (HAD) scale. Results. Patients in the observation group outperformed the control group in terms of insulin injection after intervention ( $P<0.05$ ). Significantly higher nursing satisfaction and ESCA scores were observed after intervention ( $P<0.05$ ). Self-practice oriented teaching plus psychological intervention resulted in remarkably lower postintervention glycemic indexes ( $P<0.001$ ). Markedly higher disease knowledge scores and GQOLI-74 scores were witnessed in the observation group in contrast to those of the control group ( $P<0.001$ ). The observation group patients showed lower HAD scores than those of the control group ( $P<0.001$ ). Conclusion. Self-practice oriented teaching plus psychological intervention could effectively alleviate the negative emotions of type 2 diabetic patients on first insulin therapy, stabilize glycemic indexes, and improve quality of life, demonstrating good potential for clinical promotion.

Association between Variability of Metabolic Risk Factors and Cardiometabolic Outcomes

Despite strenuous efforts to reduce cardiovascular disease (CVD) risk by improving cardiometabolic risk factors, such as glucose and cholesterol levels, and blood pressure, there is still residual risk even in patients reaching treatment targets. Recently, researchers have begun to focus on the variability of metabolic variables to remove residual risks. Several clinical trials and cohort studies have reported a relationship between the variability of metabolic parameters and CVDs. Herein, we review the literature regarding the effect of metabolic factor variability and CVD risk, and describe possible mechanisms and potential treatment perspectives for reducing cardiometabolic risk factor variability.

Machine learning based study of longitudinal HbA1c trends and their association with all-cause mortality: Analyses from a National Diabetes Registry

OBJECTIVE

The association of long-term HbA1c variability with mortality has been previously suggested. However, the significance of HbA1c variability and trends in different age and HbA1c categories is unclear.

RESEARCH DESIGN AND METHODS

Data on patients with diabetes listed in the Israeli National Diabetes Registry during years 2012-2016 (observation period) were collected. Patients with >4 HbA1c measurements, type 1 diabetes, eGFR < 30mg/ml/min, persistent HbA1c < 6% or malignancy were excluded. Utilizing machine learning methods, patients were classified into clusters according to their HbA1c trend (increasing, stable, decreasing). Mortality risk during 2017-2019 was calculated in subgroups defined by age (35-54, 55-69, 70-89 years) and last HbA1c (≤7% and >7%) at end of observation period. Models were adjusted for demographic, clinical and laboratory measurements including HbA1c, standard deviation (SD) of HbA1c and HbA1c trend.

RESULTS

This historical cohort study included 293,314 patients. Increased HbA1c variability (high SD) during the observation period was an independent predictor of mortality in patients aged more than 55 years (p < 0.01). The HbA1c trend was another independent predictor of mortality. Patients with a decreasing versus stable HbA1c trend had a greater mortality risk; this association persisted in all age groups in patients with HbA1c > 7% at the end of the observation period (p = 0.02 in age 35-54; p < 0.01 in aged >55). Patients with an increasing versus stable HbA1c trend had a greater mortality risk only in the elderly group (>70), yet in both HbA1c categories (p < 0.01).

CONCLUSIONS

HbA1c variability and trend are important determinants of mortality risk and should be considered when adjusting glycaemic targets.

Identification and Predictors for Cardiovascular Disease Risk Equivalents among Adults With Diabetes Mellitus

OBJECTIVE

We examined diabetes mellitus (DM) as a cardiovascular disease (CVD) risk equivalent based on diabetes severity and other CVD risk factors.

RESEARCH DESIGN AND METHODS

We pooled 4 US cohorts (ARIC, JHS, MESA, FHS-Offspring) and classified subjects by baseline DM/CVD. CVD risks between DM+/CVD- vs. DM-/CVD+ were examined by diabetes severity and in subgroups of other CVD risk factors. We developed an algorithm to identify subjects with CVD risk equivalent diabetes by comparing the relative CVD risk of being DM+/CVD- vs. DM-/CVD+.

RESULTS

The pooled cohort included 27,730 subjects (mean age of 58.5 years, 44.6% male). CVD rates per 1000 person-years were 16.5, 33.4, 43.2 and 71.4 among those with DM-/CVD-, DM+/CVD-, DM-/CVD+ and DM+/CVD+, respectively. Compared with those with DM-/CVD+, CVD risks were similar or higher for those with HbA1c ≥ 7%, diabetes duration ≥10 years, or diabetes medication use while those with less severe diabetes had lower risks. Hazard ratios (95%CI) for DM+/CVD- vs. DM-/CVD+ were 0.96(0.86-1.07), 0.97(0.88-1.07), 0.96(0.82-1.13), 1.18(0.98-1.41), 0.93(0.85-1.02) and 1.00(0.89-1.13) among women, white race, age <55 years, triglycerides ≥2.26 mmol/L, hs-CRP ≥ 2 mg/L and eGFR<60 mL/min/1.73m2, respectively. In DM+/CVD- group, 19.1% had CVD risk equivalent diabetes with a lower risk score but a higher observed CVD risk.

CONCLUSION

Diabetes is a CVD risk equivalent in one-fifth of CVD-free adults living with diabetes. High HbA1c, long diabetes duration, and diabetes medication use were predictors of CVD risk equivalence. Diabetes is a CVD risk equivalent for women, white people, those of younger age, with higher triglycerides or CRP, or reduced kidney function.

Development of a predictive risk model for all-cause mortality in patients with diabetes in Hong Kong

INTRODUCTION

Patients with diabetes mellitus are risk of premature death. In this study, we developed a machine learning-driven predictive risk model for all-cause mortality among patients with type 2 diabetes mellitus using multiparametric approach with data from different domains.

RESEARCH DESIGN AND METHODS

This study used territory-wide data of patients with type 2 diabetes attending public hospitals or their associated ambulatory/outpatient facilities in Hong Kong between January 1, 2009 and December 31, 2009. The primary outcome is all-cause mortality. The association of risk variables and all-cause mortality was assessed using Cox proportional hazards models. Machine and deep learning approaches were used to improve overall survival prediction and were evaluated with fivefold cross validation method.

RESULTS

A total of 273 678 patients (mean age: 65.4±12.7 years, male: 48.2%, median follow-up: 142 (IQR=106-142) months) were included, with 91 155 deaths occurring on follow-up (33.3%; annualized mortality rate: 3.4%/year; 2.7 million patient-years). Multivariate Cox regression found the following significant predictors of all-cause mortality: age, male gender, baseline comorbidities, anemia, mean values of neutrophil-to-lymphocyte ratio, high-density lipoprotein-cholesterol, total cholesterol, triglyceride, HbA1c and fasting blood glucose (FBG), measures of variability of both HbA1c and FBG. The above parameters were incorporated into a score-based predictive risk model that had a c-statistic of 0.73 (95% CI 0.66 to 0.77), which was improved to 0.86 (0.81 to 0.90) and 0.87 (0.84 to 0.91) using random survival forests and deep survival learning models, respectively.

CONCLUSIONS

A multiparametric model incorporating variables from different domains predicted all-cause mortality accurately in type 2 diabetes mellitus. The predictive and modeling capabilities of machine/deep learning survival analysis achieved more accurate predictions.

New Insights into the Role of Visit-to-Visit Glycemic Variability and Blood Pressure Variability in Cardiovascular Disease Risk

PURPOSE OF REVIEW

There is evidence from epidemiologic studies that variability in cardiovascular risk factors influences risk of cardiovascular disease. We review new studies and novel findings in the relationship between visit-to-visit glycemic variability and blood pressure variability and risk of adverse outcomes.

RECENT FINDINGS

Visit-to-visit glycemic variability is consistently linked to macrovascular disease. This relationship has been observed in both clinical trials and retrospective studies of electronic health records. Long-term blood pressure variability also predicts cardiovascular outcomes, and the association appears stronger in those with lower levels of systolic and diastolic function. As epidemiologic evidence increases in support of a role for metabolic risk factor variability in cardiovascular risk, there is a corresponding rise in interest in applying this information toward improving risk factor prediction and treatment. Future investigation of underlying mechanisms for these associations as well as implications for therapy is also warranted. The potential additive contribution of variability of multiple parameters also merits additional scrutiny. As our technology for capturing risk factor variability continues to improve, this will only enhance our understanding of its links with vascular disease and how to best utilize this information to reduce cardiovascular outcomes.

Association between hemoglobin A1c variability and hypoglycemia-related hospitalizations in veterans with diabetes mellitus

INTRODUCTION

To study the impact of hemoglobin A1c (A1c) variability on the risk of hypoglycemia-related hospitalization (HRH) in veterans with diabetes mellitus.

RESEARCH DESIGN AND METHODS

342 059 veterans with diabetes aged 65 years or older were identified for a retrospective cohort study. All participants had a 3-year baseline period from January 1, 2005 to December 31, 2016, during which they had at least four A1c tests. A1c variability measures included coefficient of variation (A1c CV), A1c SD, and adjusted A1c SD. HRH was identified during a 2-year follow-up period from Medicare and the Veterans Health Administration through validated algorithms of International Classification of Diseases (ICD)-9 and ICD-10 codes. Logistic regression modeling was used to evaluate the relationship between A1c variability and HRH risk while controlling for relevant clinical covariates.

RESULTS

2871 patients had one or more HRH in the 2-year follow-up period. HRH risk increased with greater A1c variability, and this was consistent across A1c CV, A1c SD, and adjusted A1c SD. Average A1c levels were also independently associated with HRH, with levels <7.0% (53 mmol/mol) having lower risk and >9% (75 mmol/mol) with greater risk. The relationships between A1c variability remained significant after controlling for average A1c levels and prior HRH during the baseline period.

CONCLUSION

Increasing A1c variability and elevated A1c levels are associated with a greater risk of HRH in older adults with diabetes. Clinicians should consider A1c variability when assessing patients for risk of severe hypoglycemia.

Long-term variability of glycemic markers and risk of all-cause mortality in type 2 diabetes: the Look AHEAD study

INTRODUCTION

Glycemic variability may predict poor outcomes in type 2 diabetes. We evaluated the associations of long-term variability in glycosylated hemoglobin (HbA_1C) and fasting plasma glucose (FPG) with cardiovascular disease (CVD) and death among individuals with type 2 diabetes.

RESEARCH DESIGN AND METHODS

We conducted a secondary, prospective cohort analysis of the Look AHEAD (Action for Health in Diabetes) data, including 3560 participants who attended four visits (baseline, 12 months, 24 months, and 36 months) at the outset. Variability of HbA_1C and FPG was assessed using four indices across measurements from four study visits. Participants without CVD during the first 36 months were followed for incident outcomes including a CVD composite (myocardial infarction, stroke, hospitalization for angina, and CVD-related deaths), heart failure (HF), and deaths.

RESULTS

Over a median follow-up of 6.8 years, there were 164 deaths from any cause, 33 CVD-related deaths, 91 HF events, and 340 participants experienced the CVD composite. Adjusted HRs comparing the highest to lowest quartile of SD of HbA_1C were 2.10 (95% CI 1.26 to 3.51), 3.43 (95% CI 0.95 to 12.38), 1.01 (95% CI 0.69 to 1.46), and 1.71 (95% CI 0.69 to 4.24) for all-cause mortality, CVD mortality, CVD composite and HF, respectively. The equivalent HRs for highest versus lowest quartile of SD of FPG were 1.66 (95% CI 0.96 to 2.85), 2.20 (95% CI 0.67 to 7.25), 0.94 (95% CI 0.65 to 1.35), and 2.05 (95% CI 0.80 to 5.31), respectively.

CONCLUSIONS

A greater variability in HbA_1C was associated with elevated risk of mortality. Our findings underscore the need to achieve normal and consistent glycemic control to improve clinical outcomes among individuals with type 2 diabetes.

Comparative predictive ability of visit-to-visit HbA1c variability measures for microvascular disease risk in type 2 diabetes

BACKGROUND

To assess the associations of various HbA1c measures, including a single baseline HbA1c value, overall mean, yearly updated means, standard deviation (HbA1c-SD), coefficient of variation (HbA1c-CV), and HbA1c variability score (HVS), with microvascular disease (MVD) risk in patients with type 2 diabetes.

METHODS

Linked data between National Cheng Kung University Hospital and Taiwan's National Health Insurance Research Database were utilized to identify the study cohort. The primary outcome was the composite MVD events (retinopathy, nephropathy, or neuropathy) occurring during the study follow-up. Cox model analyses were performed to assess the associations between HbA1c measures and MVD risk, with adjustment for patients' baseline HbA1c, demographics, comorbidities/complications, and treatments.

RESULTS

In the models without adjustment for baseline HbA1c, all HbA1c variability and mean measures were significantly associated with MVD risk, except HVS. With adjustment for baseline HbA1c, HbA1c-CV had the strongest association with MVD risk. For every unit of increase in HbA1c-CV, the MVD risk significantly increased by 3.42- and 2.81-fold based on the models without and with adjustment for baseline HbA1c, respectively. The associations of HbA1c variability and mean measures with MVD risk in patients with baseline HbA1c < 7.5% (58 mmol/mol) were stronger compared with those in patients with baseline HbA1c ≥ 7.5% (58 mmol/mol).

CONCLUSIONS

HbA1c variability, especially HbA1c-CV, can supplement conventional baseline HbA1c measure for explaining MVD risk. HbA1c variability may play a greater role in MVD outcomes among patients with relatively optimal baseline glycemic control compared to those with relatively poor baseline glycemic control.