Diabetes Control And Complications Trial Research Articles

Beyond HbA1c : using continuous glucose monitoring metrics to enhance interpretation of treatment effect and improve clinical decision-making.

Assessment of glycaemic outcomes in the management of Type 1 and Type 2 diabetes has been revolutionized in the past decade with the increasing availability of accurate, user-friendly continuous glucose monitoring (CGM). This advancement has brought a need for new techniques to appropriately analyse and understand the voluminous and complex CGM data for application in research-related goals and clinical guidance for individuals. Traditionally, HbA1c was established using the Diabetes Control and Complications Trial (DCCT) and other trials as the ultimate measure of glycaemic control in terms of efficacy and, by default, risk of microvascular complications of diabetes. However, it is acknowledged that HbA1c alone is inadequate at describing an individual's daily glycaemic variation and risks for hypo- and hyperglycaemia, and it does not provide the guidance needed to decrease those risks. CGM data provide means by which to characterize an individual's daily glycaemic excursions on a different time scale measured in minutes rather than months. As a consequence, clinical reports, such as the ambulatory glucose profile, increasingly include summary statistics related to averages (mean glucose, time in range) as well as markers related to glycaemic variability (coefficient of variation, standard deviation). However, there is a need to translate those metrics into specific risks that can be addressed in an actionable plan by individuals with diabetes and providers. This review presents several clinical scenarios of glycaemic outcomes from CGM data that can be analysed to describe glycaemic variability and its attendant risks of hyperglycaemia and hypoglycaemia, moving towards relevant interpretation of the complex CGM data streams.

Mediation of the Effect of Glycemia on the Risk of CVD Outcomes in Type 1 Diabetes: The DCCT/EDIC Study.

OBJECTIVEThe Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study has demonstrated the major role of hyperglycemia as a risk factor for clinical cardiovascular outcomes in type 1 diabetes (T1D). We assessed whether and to what extent the effect of glycemia is mediated by other established cardiovascular disease (CVD) risk factors.RESEARCH DESIGN AND METHODSIn the DCCT, 1,441 participants were randomized to receive either intensive or conventional diabetes therapy. The EDIC observational follow-up study enrolled 96% of the surviving DCCT cohort with 94% of the survivors still actively participating after more than 27 years of follow-up. Mediation of the effect of glycemia, as captured by HbA1c, on the subsequent CVD risk was quantified using the relative change in the CVD risk associated with HbA1c between models without and with the potential mediator.RESULTSAdjusted for age, only a few factors (e.g., pulse, triglycerides, albumin excretion rate) explained more than 10% of the effect of glycemia on CVD risk when considered individually. In multivariable models, these traditional risk factors together mediated up to ∼50% of the effect of glycemia on the risk of CVD. However, the association between HbA1c and the risk of CVD remained highly significant even after adjustment for these risk factors.CONCLUSIONSWhile HbA1c is associated with many traditional CVD risk factors, its association with these factors alone cannot explain its effects on risk of CVD. Consequently, aggressive management of traditional nonglycemic CVD risk factors, coupled with aggressive glycemic management, is indicated for individuals with type 1 diabetes.

The Association of Coronary Artery Calcification With Subsequent Incidence of Cardiovascular Disease in Type 1 Diabetes: The DCCT/EDIC Trials

ObjectivesThis study sought to determine the relationship between coronary artery calcium (CAC) scores and subsequent cardiovascular disease (CVD) events in DCCT (Diabetes Control and Complications Trial)/EDIC (Epidemiology of Diabetes Interventions and Complications) participants. BackgroundThe CAC score has been validated for improved risk stratification in general populations; however, this association has not been well studied in type 1 diabetes (T1DM). MethodsComputed tomography (CT) to measure CAC was performed in 1,205 DCCT/EDIC participants at a mean of 42.8 years of age during EDIC years 7 to 9, after the end of DCCT. This study analyzed the association between CAC and time to the first subsequent CVD event or to the first major adverse cardiac event (MACE), a follow-up of 10 to 13 years. CAC was categorized as: 0, >0 to 100, >100 to 300, or >300 Agatston units. ResultsOf 1,156 participants at risk for subsequent CVD, 105 had an initial CVD event (8.5 per 1,000 patient-years); and of 1,187 participants at risk for MACE, 51 had an initial MACE event (3.9 per 1,000 patient-years). Event rates among those with scores of zero (n = 817 [70.7%]) were very low for CVD (5.6 per 1,000 patient years). CAC scores >100 to 300 (hazard ratio [HR]: 4.17, 5.40) and >300 (HR: 6.06, 6.91) were associated with higher risks of CVD and MACE, respectively, compared to CAC of 0 (p < 0.0001). CAC scores >0 to 100 were nominally associated with CVD (HR: 1.71; p = 0.0415) but not with MACE (HR: 1.11; p = 0.8134). Similar results were observed when also adjusted for mean HbA1c and conventional CVD risk factors. The increment in the AUC due to CAC was modest. ConclusionsCAC scores >100 Agatston units were significantly associated with an increased risk of the subsequent occurrence of CVD and MACE in DCCT/EDIC cohort. (Diabetes Control and Complications Trial [DCCT]; NCT00360815; Epidemiology of Diabetes Interventions and Complications [EDIC]; NCT00360893)

Risk Factors for Retinopathy in Type 1 Diabetes: The DCCT/EDIC Study.

The Diabetes Control and Complications Trial (DCCT) demonstrated that intensive therapy reduced the development and progression of retinopathy in type 1 diabetes (T1D) compared with conventional therapy. The Epidemiology of Diabetes Interventions and Complications (EDIC) study observational follow-up showed persistent benefits. In addition to glycemia, we now examine other potential retinopathy risk factors (modifiable and nonmodifiable) over more than 30 years of follow-up in DCCT/EDIC. The retinopathy outcomes were proliferative diabetic retinopathy (PDR), clinically significant macular edema (CSME), and ocular surgery. The survival (event-free) probability was estimated using the Kaplan-Meier method. Cox proportional hazards models assessed the association between risk factors and subsequent risk of retinopathy. Both forward- and backward-selection approaches determined the multivariable models. Rate of ocular events per 1,000 person-years was 12 for PDR, 14.5 for CSME, and 7.6 for ocular surgeries. Approximately 65%, 60%, and 70% of participants remained free of PDR, CSME, and ocular surgery, respectively. The greatest risk factors for PDR in descending order were higher mean HbA1c, longer duration of T1D, elevated albumin excretion rate (AER), and higher mean diastolic blood pressure (DBP). For CSME, risk factors, in descending order, were higher mean HbA1c, longer duration of T1D, and greater age and DBP and, for ocular surgeries, were higher mean HbA1c, older age, and longer duration of T1D. Mean HbA1c was the strongest risk factor for the progression of retinopathy. Although glycemic control is important, elevated AER and DBP were other modifiable risk factors associated with the progression of retinopathy.

Risk Factors for Kidney Disease in Type 1 Diabetes.

In type 1 diabetes (T1D), the course of microalbuminuria is unpredictable and timing of glomerular filtration rate (GFR) loss is uncertain. Thus, there is a need to identify the risk factors associated with the development of more advanced stages of kidney disease through large, long-term systematic analysis. Multivariable Cox proportional hazards models assessed the association of baseline and time-dependent glycemic and nonglycemic risk factors for incident macroalbuminuria and reduced estimated GFR (eGFR; defined as <60 mL/min/1.73 m2) over a mean of 27 years in the Diabetes Control and Complications Trial (DCCT) cohort. Higher mean HbA1c (hazard ratio [HR] 1.969 per 1% higher level [95% CI 1.671-2.319]) and male sex (HR 2.767 [95% CI 1.951-3.923]) were the most significant factors independently associated with incident macroalbuminuria, whereas higher mean triglycerides, higher pulse, higher systolic blood pressure (BP), longer diabetes duration, higher current HbA1c, and lower mean weight had lower magnitude associations. For incident reduced eGFR, higher mean HbA1c (HR 1.952 per 1% higher level [95% CI 1.714-2.223]) followed by higher mean triglycerides, older age, and higher systolic BP were the most significant factors. Although several risk factors associated with macroalbuminuria and reduced eGFR were identified, higher mean glycemic exposure was the strongest determinant of kidney disease among the modifiable risk factors. These findings may inform targeted clinical strategies for the frequency of screening, prevention, and treatment of kidney disease in T1D.

Connecting the Dots: Validation of Time in Range Metrics With Microvascular Outcomes.

The landmark Diabetes Control and Complications Trial (DCCT) identified the relationship between intensive diabetes management for those with type 1 diabetes (T1D) and a delay in the onset or progression of microvascular complications, shifting the paradigm of clinical care for this chronic medical condition (1). Importantly, the data from that trial continue to have a lasting legacy as they can now be analyzed to inform present-day questions. An example of this comes from the article by Beck et al. in this issue of Diabetes Care (2) that concisely states the primary implication of the article in its title, “Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials.” In recent years, and with increasing use of continuous glucose monitoring (CGM), the ability to classify sensor glucose levels into various ranges has been feasible. Yet, some have questioned the validity of using these measures as a surrogate outcome measure in ongoing and future clinical trials. Indeed, some have called for a “modern-day” DCCT assessing whether CGM and a greater time in range (TIR) would result in fewer microvascular end points compared with self-monitoring of blood glucose (with intermittent masked CGM). Unfortunately, the duration of time, funds required, and ethical concerns given clinical equipoise regarding the benefits of the technology would make completion of a rigorous randomized controlled trial a near-impossible feat. Recognizing the wealth of data that the DCCT affords, Beck et al. (2) found a creative solution to assess the hypothesis of whether TIR could serve as an outcome measure for future trials. Specifically, they capitalized on the glucose values captured seven times daily every 3 months during the course of the 6+ years of the DCCT. This allowed them to calculate the percent TIR of glucose values between 70 and 180 mg/dL and show a robust …

Glycemic Control, Cardiac Autoimmunity, and Long-Term Risk of Cardiovascular Disease in Type 1 Diabetes Mellitus.

Poor glycemic control is associated with increased risk of cardiovascular disease (CVD) in type 1 diabetes mellitus (T1DM); however, little is known about mechanisms specific to T1DM. In T1DM, myocardial injury can induce persistent cardiac autoimmunity. Chronic hyperglycemia causes myocardial injury, raising the possibility that hyperglycemia-induced cardiac autoimmunity could contribute to long-term CVD complications in T1DM. We measured the prevalence and profiles of cardiac autoantibodies (AAbs) in longitudinal samples from the DCCT (Diabetes Control and Complications Trial) in participants with mean hemoglobin A1c (HbA1c) ≥9.0% (n=83) and ≤7.0% (n=83) during DCCT. We assessed subsequent coronary artery calcification (measured once during years 7-9 in the post-DCCT EDIC [Epidemiology of Diabetes Interventions and Complications] observational study), high-sensitivity C-reactive protein (measured during EDIC years 4-6), and CVD events (defined as nonfatal myocardial infarction, stroke, death resulting from CVD, heart failure, or coronary artery bypass graft) over a 26-year median follow-up. Cardiac AAbs were also measured in matched patients with type 2 diabetes mellitus with HbA1c ≥9.0% (n=70) and ≤7.0% (n=140) and, as a control for cardiac autoimmunity, patients with Chagas cardiomyopathy (n=51). Apart from HbA1c levels, the DCCT groups shared similar CVD risk factors at the beginning and end of DCCT. The DCCT HbA1c ≥9.0% group showed markedly higher cardiac AAb levels than the HbA1c ≤7.0% group during DCCT, with a progressive increase and decrease in AAb levels over time in the 2 groups, respectively ( P<0.001). In the HbA1c ≥9.0% group, 46%, 22%, and 11% tested positive for ≥1, ≥2, and ≥3 different cardiac AAb types, respectively, similar to patients with Chagas cardiomyopathy, compared with 2%, 1%, and 0% in the HbA1c ≤7.0% group. Glycemic control was not associated with AAb prevalence in type 2 diabetes mellitus. Positivity for ≥2 AAbs during DCCT was associated with increased risk of CVD events (4 of 6; hazard ratio, 16.1; 95% CI, 3.0-88.2) and, in multivariable analyses, with detectable coronary artery calcification (13 of 31; odds ratio, 60.1; 95% CI, 8.4-410.0). Patients with ≥2 AAbs subsequently also showed elevated high-sensitivity C-reactive protein levels (6.0 mg/L versus 1.4 mg/L in patients with ≤1 AAbs; P=0.003). Poor glycemic control is associated with cardiac autoimmunity in T1DM. Furthermore, cardiac AAb positivity is associated with an increased risk of CVD decades later, suggesting a role for autoimmune mechanisms in the development of CVD in T1DM, possibly through inflammatory pathways.

The Official Journal of ATTD Advanced Technologies &amp; Treatments for Diabetes Conference Berlin, Germany—February 20–23, 2019

The Official Journal of ATTD Advanced Technologies &amp; Treatments for Diabetes Conference <i>Berlin, Germany—February 20–23, 2019</i>

Probing the Meaning of Persistent Propeptide Release in Type 1 Diabetes.

Type 1 diabetes is well recognized to be immune mediated, resulting in destruction of β-cells. That this eradication is not always complete was evident in an early report from the Diabetes Control and Complications Trial (DCCT) showing that 11% of adult participants with type 1 diabetes for more than 5 years had measurable C-peptide in the fasting state and following mixed-meal stimulation, while no adolescents had evidence of such (1). Further, in participants with measurable C-peptide responses, C-peptide declined in all after a year of randomized therapy, with this decline being less in those who received intensive insulin therapy. Subsequently, it was shown in adolescents that 2 weeks of intensive insulin therapy, compared with conventional therapy, resulted in improved β-cell function a year later along with superior glucose control (2). In addition to C-peptide, proinsulin has also been shown to be circulating in individuals with type 1 diabetes at the time of diagnosis and to be still measurable 30 months later (3,4). Thus, there is long-standing evidence that at the time of diagnosis and subsequently, individuals with type 1 diabetes have β-cells still capable of synthesizing proinsulin, and many can process it to C-peptide and insulin. In the current issue of Diabetes Care , Sims et al. (5) report longitudinal findings on proinsulin secretion in type 1 diabetes using a large number of samples from the T1D Exchange. They divided their subjects into three groups based on stimulated C-peptide responses to a mixed meal. We have categorized these groups as having absent, intermediate, and high C-peptide responses, although the latter are a great deal lower than what is observed in healthy people. Individuals in the absent group had C-peptide responses that were below the reliable lower detection limit of the assay, and they were not studied further. These …

Risk Factor Modeling for Cardiovascular Disease in Type 1 Diabetes in the Pittsburgh Epidemiology of Diabetes Complications (EDC) Study: A Comparison With the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study (DCCT/EDIC).

In a recent Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study report, mean HbA1c was the strongest predictor of cardiovascular disease (CVD) after age. In DCCT/EDIC, mean diabetes duration was 6 years (median 4) at baseline and those with high blood pressure or cholesterol were excluded. We now replicate these analyses in the Pittsburgh Epidemiology of Diabetes Complications (EDC) prospective cohort study of childhood-onset (at <17 years of age) type 1 diabetes, with similar age (mean 27 years in both studies) but longer diabetes duration (mean 19 years and median 18 years) and no CVD risk factor exclusion at baseline. CVD incidence (CVD death, myocardial infarction (MI), stroke, revascularization, angina, or ischemic electrocardiogram) was associated with diabetes duration, most recent albumin excretion rate (AER), updated mean triglycerides, baseline hypertension, baseline LDL cholesterol, and most recent HbA1c Major atherosclerotic cardiovascular events (CVD death, MI, or stroke) were associated with diabetes duration, most recent AER, baseline systolic blood pressure, baseline smoking, and updated mean HbA1c Compared with findings in DCCT/EDIC, traditional risk factors similarly predicted CVD; however AER predominates in EDC and HbA1c in DCCT/EDIC. Thus, the relative impact of HbA1c and kidney disease in type 1 diabetes varies according to diabetes duration.

Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials.

This study evaluated the association of time in range (TIR) of 70-180 mg/dL (3.9-10 mmol/L) with the development or progression of retinopathy and development of microalbuminuria using the Diabetes Control and Complications Trial (DCCT) data set in order to validate the use of TIR as an outcome measure for clinical trials. In the DCCT, blood glucose concentrations were measured at a central laboratory from seven fingerstick samples (seven-point testing: pre- and 90-min postmeals and at bedtime) collected during 1 day every 3 months. Retinopathy progression was assessed every 6 months and urinary microalbuminuria development every 12 months. Proportional hazards models were used to assess the association of TIR and other glycemic metrics, computed from the seven-point fingerstick data, with the rate of development of microvascular complications. Mean TIR of seven-point profiles for the 1,440 participants was 41 ± 16%. The hazard rate of development of retinopathy progression was increased by 64% (95% CI 51-78), and development of the microalbuminuria outcome was increased by 40% (95% CI 25-56), for each 10 percentage points lower TIR (P < 0.001 for each). Results were similar for mean glucose and hyperglycemia metrics. Based on these results, a compelling case can be made that TIR is strongly associated with the risk of microvascular complications and should be an acceptable end point for clinical trials. Although hemoglobin A1c remains a valuable outcome metric in clinical trials, TIR and other glycemic metrics-especially when measured with continuous glucose monitoring-add value as outcome measures in many studies.

Abstract P115: Urinary Angiotensinogen is Increased in Type 1 Diabetes With Mild Albuminuria: Gender Differences

Urinary angiotensinogen (uAOG) can be increased in patients with type 2 diabetes and in hypertension. We wanted to examine uAOG in patients with type 1 diabetes as a possible biomarker of enhanced Renin-Angiotensin system activity within the kidney at an early stage of the disease and study any potential gender differences Methods: Urine samples from the Diabetes Control and Complications Trial (DCCT) that were available at the earliest study visit were obtained from NIDDK repository. Cases (N=103) were participants with microalbuminuria at study initiation (30.2-286.5mg/24hrs). Controls (N=103) were patients with type 1 diabetes with normoalbuminuria (&lt;30mg/24hrs). Controls were matched based on age, gender and insulin arm allocation (intensive vs conventional) when the urine was available at the earliest visit (range 0-8). Wilcoxon Rank Sum test was used for non-parametric variables. Gender differences were examined using Mann Whitney test. Results: At the study visit there were no significant differences in age, gender, Insulin modality and disease duration. Systolic blood pressure was slightly but significantly higher in cases than in controls (median 116, range 92-180 vs 112, range 90-150mmHg, P=0.005). HbA1c was slightly but significantly higher in cases than controls (median 8.0, range 5.2-14.2 vs 7.8, 5-12.6%, P=0.03). The eGFR was normal in both groups but albumin excretion rate (AER) was increased in the cases as compared to the controls. There was a highly significant difference between cases and controls in terms of uAOG (median 6.6, range 1.0-1070 vs 4.0, range 0.1-65.3ng/mg, P&lt;0.001). This difference persisted after adjusting for GFR, systolic blood pressure and HbA1c (P&lt;0.001). Gender analysis revealed that uAOG was higher in females than males (median 11.7, range 1.0-393 vs 5.4, range 1.26-1070ng/mg, P=0.001) Conclusion: We conclude that uAOG is increased in people with type 1 diabetes with normal GFR and microalbuminuria. This increase in uAOG persists after adjustment for blood pressure, GFR and HbA1c. In addition, uAOG is higher in females than males. Gender differences are important for the interpretation of uAOG as a marker of kidney disease in people with type 1 diabetes.

Burden of Urological Complications in Men and Women With Long-standing Type 1 Diabetes in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Cohort.

OBJECTIVEType 1 diabetes has been associated with high rates of urinary and sexual problems, but the cumulative burden and overlap of these complications are unknown. We sought to determine prevalence of urological complications in persons with type 1 diabetes, associations with clinical and diabetes-related factors, and rates of emergence, persistence, and remission.RESEARCH DESIGN AND METHODSThis ancillary longitudinal study among participants in the Diabetes Control and Complications Trial (DCCT) and observational follow-up study Epidemiology of Diabetes Interventions and Complications (EDIC) (652 women and 713 men) was conducted in 2003 and 2010/2011. Urinary incontinence (UI), lower urinary tract symptoms, urinary tract infection, female sexual dysfunction, erectile dysfunction, low male sexual desire, and orgasmic dysfunction were measured with validated instruments. Logistic regression determined association of complications with demographics and clinical characteristics.RESULTSOf sexually active women completing the 2010/2011 survey, 35% reported no complications, 39% had one, 19% two, 5% three, and 2% four. In men, 31% had no complications, 36% had one, 22% two, 9% three, and 3% four. Sexual dysfunction was most prevalent (42% women and 45% men) followed by UI in women (31%) and low sexual desire in men (40%). Urological complications were associated with age, BMI, and HbA1c. Remission rates ranged from 4 to 12% over the 7-year interval between surveys.CONCLUSIONSUrological complications are prevalent and frequently co-occur in persons with type 1 diabetes. Remission rates in a minority subset indicate a rationale for future studies to mitigate the onset or impact of urological complications of diabetes.

Primum Non Nocere: Refocusing Our Attention on Severe Hypoglycemia Prevention.

Severe hypoglycemia, defined as low blood glucose requiring assistance for recovery, is arguably the most dangerous complication of type 1 diabetes as it can result in permanent cognitive impairment, seizure, coma, accidents, and death (1,2). Since the Diabetes Control and Complications Trial (DCCT) demonstrated that intensive intervention to normalize glucose prevents long-term complications but at the price of a threefold increase in the rate of severe hypoglycemia (3), hypoglycemia has been recognized as the major limitation to achieving tight glycemic control. Severe hypoglycemia remains prevalent among adults with type 1 diabetes, ranging from ∼1.4% per year in the DCCT/EDIC (Epidemiology of Diabetes Interventions and Complications) follow-up cohort (4) to ∼8% in the T1D Exchange clinic registry (5). One the greatest risk factors for severe hypoglycemia is impaired awareness of hypoglycemia (6), which increases risk up to sixfold (7,8). Hypoglycemia unawareness results from deficient counterregulation (9), where falling glucose fails to activate the autonomic nervous system to produce neuroglycopenic symptoms that normally help patients identify and respond to episodes (i.e., sweating, palpitations, hunger) (2). An estimated 20–25% of adults with type 1 diabetes have impaired hypoglycemia awareness (8), which increases to more than 50% after 25 years of disease duration (10). Screening for hypoglycemia unawareness to identify patients at increased risk of severe hypoglycemic events should be part of routine diabetes care. Self-identified impairment in awareness tends to agree with clinical evaluation (11). Therefore, hypoglycemia unawareness can be easily and effectively screened using multiple, self-administered methods (11). These range from single questions (i.e., “Do you know when your hypos are coming?” [7] and “Can you feel when you are low?” [12]) to longer assessments characterizing hypoglycemia exposure and the glycemic threshold for symptomatic response, as in the 8-item Clarke questionnaire (11 …

COMPARISON OF HBA1C LEVEL USING TURBIDIMETRY INHIBITION IMMUNOASSAY, LATEX AGGLUTINATION INHIBITION METHOD AND HPLC METHOD

According to the National Glycohemoglobin Standardization Program (NGSP) and The Diabetes Control and Complication Trial(DCCT) the standard method of measuring HbA1c is High-Performance Liquid Chromatography (HPLC), but HPLC requiresparticular instrument investments, trained staff, long and relatively expensive sample processing. This an instrument that hassimilar performance to HPLC but its operation process is relatively simple and not costly. The purpose of this study was to analysethe HbA1c level using Turbidimetry Inhibition Immunoassay (TII) method and the HPLC method; to analyse HbA1 level using LatexAgglutination Inhibition (LAI) method and HPLC method. This research was conducted with a cross-sectional design during theperiod of March-April 2017. The total sample consisted of 160 samples divided into two groups. For the first group, HbA1c levelusing TII method and HPLC method was measured. For the second group, HbA1c level was measured using LAI method and HPLCmethod.The data obtained were analyzed using the Paired T-test. There was a significant difference between HbA1c levels usingTII method and HPLC method {8.12(2.53)% vs. 8.49(2.63)%, p&lt;0.001}. There was no significant differences between HbA1c levelsusing LAI method and HPLC method {7.52(1.95%) vs. 7.47(2.00)%, p&gt;0.05}. This research concluded that there was a differencebetween the HbA1c levels using TII method and HPLC method, but no difference between HbA1c levels using LAI method and HPLC method.

Risk Factors for Major Atherosclerotic Cardiovascular Events (MACE) in Type 1 Diabetes (T1D)—The Pittsburgh Epidemiology of Diabetes Complications (EDC) Study

The Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications follow-up study (EDIC) recently reported that after age mean HbA1c was the strongest predictor of MACE over 27 year of follow-up. The DCCT/EDIC cohort had a short T1D duration at baseline (mean 6 yr) and those with high blood pressure or cholesterol were excluded so it is unclear if these results apply to longer T1D durations and without risk factor exclusion. We thus replicated these analyses in the Pittsburgh EDC study a prospective cohort study of childhood onset (&amp;lt;17 yr) T1D with 25 year of follow-up and similar age (mean 27 year in both studies) but longer T1D duration (mean 18 yr) at baseline. EDC participants were diagnosed 1950-1980 (n=658 49% women) and examined at 1986-88 baseline. Follow-up exams occurred at 2, 4, 6, 8, 10, 18 and 25 years. MACE incidence (CVD death, MI, stroke) was ascertained by death certificate or self reported and confirmed with medical records. Participants with prevalent CVD were excluded (n=54). Baseline (BL), time varying updated mean (UM) and time varying most recent (MR) risk factors were assessed in Cox models as in DCCT/EDIC. In EDC 18% (107) developed MACE vs. 6% in DCCT/EDIC. The final multivariable model for MACE comprised BL T1D duration (HR 1.1, p&amp;lt;.001), MR albumin excretion rate (AER) (HR 1.3, p&amp;lt;.001), UM SBP (HR 1.03, p&amp;lt;.001), BL smoking (HR 1.9, p=0.003), UM LDLc (HR 1.01, p=0.03) and UM HbA1c (HR 1.2, p=0.03). In DCCT/EDIC the HbA1c effect size was larger while T1D duration, UM SBP, MR (not UM as in EDC) LDLc and MR (not BL as in EDC) smoking predicted with similar effect sizes. ACE inhibitors (protective) and pulse rate also predicted MACE in DCCT/EDIC. While AER was a strong predictor in EDC no renal markers were significant in DCCT/EDIC. These results suggest that at longer T1D duration much of the HbA1c effect on MACE risk is mediated through other factors as recently reported by DCCT/EDIC. Disclosure R.G. Miller: None. T.J. Orchard: None.

What are the clinical, quality-of-life, and cost consequences of 30 years of excellent vs. poor glycemic control in type 1 diabetes?

ObjectiveThe Diabetes Control and Complications Trial (DCCT) demonstrated that intensive therapy for type 1 diabetes delayed the development of microvascular and neuropathic complications compared to conventional therapy. At the end of DCCT, all participants were trained in intensive therapy, care was transferred to community providers, and the difference in HbA1c between treatment groups narrowed and disappeared. Our objective was to describe the outcomes and the quality-of-life and costs associated with those outcomes in participants who maintained excellent vs. poor glycemic control over 30 years. Research design and methodsWe assessed the incidence of retinopathy, nephropathy, neuropathy, cardiovascular disease, acute metabolic complications, death, quality-of-life, and costs in the tertile of DCCT intensive therapy participants who achieved a mean updated HbA1c of <7.2% (55 mmol/mol) and the tertile of DCCT conventional therapy participants (n = 240) who achieved a mean updated HbA1c of >8.8% (73 mmol/mol) over 30 years. ResultsThirty years of excellent vs. poor glycemic control substantially reduced the incidence of retinopathy requiring laser therapy (5% vs. 45%), end-stage renal disease (0% vs. 5%), clinical neuropathy (15% vs. 50%), myocardial infarction (3% vs. 5%), stroke (0.4% vs. 2%), and death (6% vs. 20%). It also resulted in a gain of ~1.62 quality-adjusted life-years and averted ~$90,900 in costs of complications per participant. ConclusionsThirty years of excellent vs. poor glycemic control for T1DM can substantially reduce the incidence of complications, comorbidities, and death, improve quality-of-life, and reduce costs. These estimates represent the benefits that may be achieved with excellent glycemic control.

Accumulation of advanced glycation end products is associated with macrovascular events and glycaemic control with microvascular complications in Type 2 diabetes mellitus.

The United Kingdom Prospective Diabetes Study (UKPDS) study showed that glycaemic control (HbA1c ) can predict vascular complications in Type 2 diabetes mellitus. The Diabetes Control and Complications Trial (DCCT) study showed that accumulation of advanced glycation end products (AGEs) from skin biopsies predicts vascular complications in Type 1 diabetes. Previously, we showed that tissue AGEs can be measured non-invasively using skin autofluorescence (SAF). The aim of this study was to compare the predictive value of HbA1c and SAF for new macrovascular events and microvascular complications in people with Type2 diabetes. A prospective cohort study of 563 participants, median age 64years [interquartile range (IQR) 57-72], diabetes duration of 13years, from five Dutch hospitals was performed. After a median follow-up of 5.1 (IQR 4.3-5.9)years, 79 (15%) participants had died and 49 (9%) were lost to follow-up. Some 133 (26%) developed a microvascular complication and 189 (37%) a macrovascular event. Tertiles of HbA1c were significantly associated with development of microvascular complications (log rank P=0.022), but not with macrovascular events. Tertiles of SAF were significantly associated with macrovascular events (log rank P=0.003). Cox regression analysis showed SAF was associated with macrovascular events: crude hazard ratio (HR) 1.53 (P<0.001) per unit increase, HR 1.28 (P=0.03) after correction for UKPDS score. HbA1c was predictive for microvascular complications: crude HR 1.20 (P=0.004), HR 1.20 (P=0.004) after correction for UKPDS score. This study shows that tissue accumulation of AGEs, assessed by SAF, is associated with development of macrovascular events in people with Type2 diabetes, whereas HbA1c is associated with the development of microvascular complications.

Diabetes and Pregnancy

Diabetes and Pregnancy

Cardiovascular Protection in People With Diabetes.

Cardiovascular Protection in People With Diabetes.