46 research outputs found

    Utility of using electrocardiogram measures of heart rate variability as a measure of cardiovascular autonomic neuropathy in type 1 diabetes patients

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    AIMS/INTRODUCTION: Cardiovascular autonomic neuropathy (CAN) is a predictor of cardiovascular disease and mortality. Cardiovascular reflex tests (CARTs) are the gold standard for the diagnosis of CAN, but might not be feasible in large research cohorts or in clinical care. We investigated whether measures of heart rate variability obtained from standard electrocardiogram (ECG) recordings provide a reliable measure of CAN. MATERIALS AND METHODS: Standardized CARTs (R-R response to paced breathing, Valsalva, postural changes) and digitized 12-lead resting ECGs were obtained concomitantly in Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications participants (n = 311). Standard deviation of normally conducted R-R intervals (SDNN) and the root mean square of successive differences between normal-to-normal R-R intervals (rMSSD) were measured from ECG. Sensitivity, specificity, probability of correct classification and Kappa statistics evaluated the agreement between ECG-derived CAN and CARTs-defined CAN. RESULTS: Participants with CARTs-defined CAN had significantly lower SDNN and rMSSD compared with those without CAN (P \u3c 0.001). The optimal cut-off points of ECG-derived CAN were \u3c17.13 and \u3c24.94 ms for SDNN and rMSSD, respectively. SDNN plays a dominant role in defining CAN, with an area under the curve of 0.73, indicating fair test performance. The Kappa statistic for SDNN was 0.41 (95% confidence interval 0.30-0.51) for the optimal cut-off point, showing fair agreement with CARTs-defined CAN. Combining SDNN and rMSSD optimal cut-off points does not provide additional predictive power for CAN. CONCLUSIONS: These analyses are the first to show the agreement between indices of heart rate variability derived from ECGs and the gold standard CARTs, thus supporting potential use as a measure of CAN in clinical research and clinical care

    Quality Control Measures over 30 Years in a Multicenter Clinical Study: Results from the Diabetes Control and Complications Trial / Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study.

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    Implementation of multicenter and/or longitudinal studies requires an effective quality assurance program to identify trends, data inconsistencies and process variability of results over time. The Diabetes Control and Complications Trial (DCCT) and the follow-up Epidemiology of Diabetes Interventions and Complications (EDIC) study represent over 30 years of data collection among a cohort of participants across 27 clinical centers. The quality assurance plan is overseen by the Data Coordinating Center and is implemented across the clinical centers and central reading units. Each central unit incorporates specific DCCT/EDIC quality monitoring activities into their routine quality assurance plan. The results are reviewed by a data quality assurance committee whose function is to identify variances in quality that may impact study results from the central units as well as within and across clinical centers, and to recommend implementation of corrective procedures when necessary. Over the 30-year period, changes to the methods, equipment, or clinical procedures have been required to keep procedures current and ensure continued collection of scientifically valid and clinically relevant results. Pilot testing to compare historic processes with contemporary alternatives is performed and comparability is validated prior to incorporation of new procedures into the study. Details of the quality assurance plan across and within the clinical and central reading units are described, and quality outcomes for core measures analyzed by the central reading units (e.g. biochemical samples, fundus photographs, ECGs) are presented

    Moderation of the effect of glycemia on the risk of cardiovascular disease in type 1 diabetes: The DCCT/EDIC study.

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    Aims: We assessed whether and to what extent established cardiovascular disease (CVD) risk factors moderate (enhance/reduce) the effect of hyperglycemia on CVD outcomes in the long-term follow-up of the Diabetes Control and Complications Trial type 1 diabetes (T1D) cohort (N = 1441). Methods: Moderation of the effect of glycemia on subsequent risk of major adverse cardiovascular events (MACE: fatal or non-fatal myocardial infarction or stroke) and any-CVD (MACE plus confirmed angina, silent MI, revascularization, or congestive heart failure) was assessed separately using interaction terms between HbA1c and other risk factors in Cox proportional hazards models. Results: Over a median follow-up of 29 years, there were 120 MACE cases and 239 any-CVD cases. Higher pulse, higher triglycerides, use of calcium channel blockers, and presence of neuropathy individually enhanced (p \u3c 0.01) the effect of glycemia on any-CVD. Higher pulse and triglyceride levels, albumin excretion rate, hypertension, and no family history of type 2 diabetes enhanced (p \u3c 0.01) the effect of glycemia on MACE. Conclusions: Such moderation analyses identify subgroups with increased CVD risk who might especially benefit from earlier and/or more intensive glycemic control. Interventions treating modifiable moderating factors may independently reduce the risk of CVD and also reduce the risk associated with a higher HbA1c

    Utility of using electrocardiogram measures of heart rate variability as a measure of cardiovascular autonomic neuropathy in type 1 diabetes patients

    No full text
    Aims/Introduction: Cardiovascular autonomic neuropathy (CAN) is a predictor of cardiovascular disease and mortality. Cardiovascular reflex tests (CARTs) are the gold standard for the diagnosis of CAN, but might not be feasible in large research cohorts or in clinical care. We investigated whether measures of heart rate variability obtained from standard electrocardiogram (ECG) recordings provide a reliable measure of CAN. Materials and Methods: Standardized CARTs (R-R response to paced breathing, Valsalva, postural changes) and digitized 12-lead resting ECGs were obtained concomitantly in Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications participants (n = 311). Standard deviation of normally conducted R-R intervals (SDNN) and the root mean square of successive differences between normal-to-normal R-R intervals (rMSSD) were measured from ECG. Sensitivity, specificity, probability of correct classification and Kappa statistics evaluated the agreement between ECG-derived CAN and CARTs-defined CAN. Results: Participants with CARTs-defined CAN had significantly lower SDNN and rMSSD compared with those without CAN (P \u3c 0.001). The optimal cut-off points of ECG-derived CAN were \u3c17.13 and \u3c24.94 ms for SDNN and rMSSD, respectively. SDNN plays a dominant role in defining CAN, with an area under the curve of 0.73, indicating fair test performance. The Kappa statistic for SDNN was 0.41 (95% confidence interval 0.30–0.51) for the optimal cut-off point, showing fair agreement with CARTs-defined CAN. Combining SDNN and rMSSD optimal cut-off points does not provide additional predictive power for CAN. Conclusions: These analyses are the first to show the agreement between indices of heart rate variability derived from ECGs and the gold standard CARTs, thus supporting potential use as a measure of CAN in clinical research and clinical care

    Type 1 diabetes and oral health: Findings from the Epidemiology of Diabetes Interventions and Complications (EDIC) study

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    OBJECTIVE: To describe long-term oral health outcomes and examine associations between sociodemographic factors, clinical characteristics, and markers of diabetes control on tooth loss in participants with type 1 diabetes enrolled in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study. RESEARCH DESIGN AND METHODS: Oral health outcomes related to tooth loss were reported at annual visits during EDIC years 22-26 (2015-2019). Generalized estimating equation models were used to assess the association of individual risk factors and tooth loss, over repeated time points. RESULTS: A total of 165 (17%) participants with type 1 diabetes reported 221 oral health outcomes related to tooth loss over a five-year period. After controlling for age and current tobacco use, the presence of diabetic peripheral neuropathy was significantly associated with an increased odds of tooth loss (OR = 1.88, 95% CI 1.24, 2.87) while higher mean HDL/LDL cholesterol ratio was significantly associated with a decreased odds of tooth loss (OR = 0.87, 95% CI = 0.79, 0.97). CONCLUSIONS: These findings suggest that diabetes-related complications, either resulting from or independent of poor glycemia, may be directly associated with oral health conditions, and support the need for individuals with type 1 diabetes and providers to implement lifestyle and medical interventions to reduce oral health risks

    Optimal Frequency of Urinary Albumin Screening in Type 1 Diabetes

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    OBJECTIVE: Kidney disease screening recommendations include annual urine testing for albuminuria after 5 years\u27 duration of type 1 diabetes. We aimed to determine a simple, risk factor-based screening schedule that optimizes early detection and testing frequency. RESEARCH DESIGN AND METHODS: Urinary albumin excretion measurements from 1,343 participants in the Diabetes Control and Complications Trial and its long-term follow-up were used to create piecewise-exponential incidence models assuming 6-month constant hazards. Likelihood of the onset of moderately or severely elevated albuminuria (confirmed albumin excretion rate AER ≥30 or ≥300 mg/24 h, respectively) and its risk factors were used to identify individualized screening schedules. Time with undetected albuminuria and number of tests were compared with annual screening. RESULTS: The 3-year cumulative incidence of elevated albuminuria following normoalbuminuria at any time during the study was 3.2%, which was strongly associated with higher glycated hemoglobin (HbA1c) and AER. Personalized screening in 2 years for those with current AER ≤10 mg/24 h and HbA1c ≤8% (low risk [0.6% three-year cumulative incidence]), in 6 months for those with AER 21-30 mg/24 h or HbA1c ≥9% (high risk [8.9% three-year cumulative incidence]), and in 1 year for all others (average risk [2.4% three-year cumulative incidence]) was associated with 34.9% reduction in time with undetected albuminuria and 20.4% reduction in testing frequency as compared with annual screening. Stratification by categories of HbA1c or AER alone was associated with reductions of lesser magnitude. CONCLUSIONS: A personalized alternative to annual screening in type 1 diabetes can substantially reduce both the time with undetected kidney disease and the frequency of urine testing. ARTICLE HIGHLIGHTS: Kidney disease screening recommendations include annual urine testing for albuminuria after 5 years\u27 duration of type 1 diabetes. We investigated simple screening schedules that optimize early detection and testing frequency. Personalized screening in 2 years for those with current AER ≤10 mg/24 h and HbA1c ≤8%, in 6 months for those with AER 21-30 mg/24 h or HbA1c ≥9%, and in 1 year for all others yielded 34.9% reduction in time with undetected albuminuria and 20.4% fewer evaluations compared with annual screening. A personalized alternative to annual screening in type 1 diabetes can substantially reduce both the time with undetected kidney disease and the frequency of urine testing
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