Adam Hulman

Prediction of First Cardiovascular Disease Event in Type 1 Diabetes Mellitus: The Steno Type 1 Risk Engine.

Background— Patients with type 1 diabetes mellitus are at increased risk of developing cardiovascular disease (CVD), but they are currently undertreated. There are no risk scores used on a regular basis in clinical practice for assessing the risk of CVD in type 1 diabetes mellitus. Methods and Results— From 4306 clinically diagnosed adult patients with type 1 diabetes mellitus, we developed a prediction model for estimating the risk of first fatal or nonfatal CVD event (ischemic heart disease, ischemic stroke, heart failure, and peripheral artery disease). Detailed clinical data including lifestyle factors were linked to event data from validated national registers. The risk prediction model was developed by using a 2-stage approach. First, a nonparametric, data-driven approach was used to identify potentially informative risk factors and interactions (random forest and survival tree analysis). Second, based on results from the first step, Poisson regression analysis was used to derive the final model. The final CVD prediction model was externally validated in a different population of 2119 patients with type 1 diabetes mellitus. During a median follow-up of 6.8 years (interquartile range, 2.9–10.9) a total of 793 (18.4%) patients developed CVD. The final prediction model included age, sex, diabetes duration, systolic blood pressure, low-density lipoprotein cholesterol, hemoglobin A1c, albuminuria, glomerular filtration rate, smoking, and exercise. Discrimination was excellent for a 5-year CVD event with a C-statistic of 0.826 (95% confidence interval, 0.807–0.845) in the derivation data and a C-statistic of 0.803 (95% confidence interval, 0.767–0.839) in the validation data. The Hosmer-Lemeshow test showed good calibration (P>0.05) in both cohorts. Conclusions— This high-performing CVD risk model allows for the implementation of decision rules in a clinical setting.

Heterogeneity of Pre-diabetes and Type 2 Diabetes: Implications for Prediction, Prevention and Treatment Responsiveness

Type 2 diabetes is a heterogeneous disease with large variation in the relative contributions of insulin resistance and beta cell dysfunction between subgroups and individuals. Some of these differences are reflected in the way people are diagnosed. However, differences in glucose regulation exist among individuals even in those with comparable diagnostic glucose levels. In this review we address the heterogeneity of pre-diabetes and type 2 diabetes with special emphasis on differences in the pathophysiology and treatment responses related to the diagnostic criteria. We also discuss whether novel glycaemic markers of diabetes risk can provide additional information to the established diagnostic criteria. A better understanding of the underlying mechanisms responsible for elevated fasting versus postprandial glucose concentration, as well as knowledge about the expected responsiveness to treatment in individuals with different clinical characteristics at diagnosis, may contribute to optimising strategies for management of hyperglycaemia in both pre-diabetes and type 2 diabetes.

Effect of secular trends on age-related trajectories of cardiovascular risk factors: The Whitehall II longitudinal study 1985-2009

Background: Secular trends in cardiovascular risk factors have been described, but few studies have examined simultaneously the effects of both ageing and secular trends within the same cohort. Methods: Development of cardiovascular risk factors over the past three decades was analysed using serial measurements from 10 308 participants aged from 35 to 80 years over 25 years of follow-up from five clinical examination phases of the Whitehall II study. Changes of body mass index, waist circumference, blood pressure and total and high-density lipoprotein cholesterol distribution characteristics were analysed with quantile regression models in the 57–61 age group. Age-related trajectories of risk factors were assessed by fitting mixed-effects models with adjustment for year of birth to reveal secular trends. Results: Average body mass index and waist circumference increased faster with age in women than in men, but the unfavourable secular trend was more marked in men. Distributions showed a fattening of the right tail in each consecutive phase, meaning a stronger increase in higher percentiles. Despite the higher obesity levels in younger birth cohorts, total cholesterol decreased markedly in the 57–61 age group along the entire distribution rather than in higher extremes only. Conclusion: The past three decades brought strong and heterogeneous changes in cardiovascular risk factor distributions. Secular trends appear to modify age-related trajectories of cardiovascular risk factors, which may be a source of bias in longitudinal analyses.

Heterogeneity in glucose response curves during an oral glucose tolerance test and associated cardiometabolic risk

We aimed to examine heterogeneity in glucose response curves during an oral glucose tolerance test with multiple measurements and to compare cardiometabolic risk profiles between identified glucose response curve groups. We analyzed data from 1,267 individuals without diabetes from five studies in Denmark, the Netherlands and the USA. Each study included between 5 and 11 measurements at different time points during a 2-h oral glucose tolerance test, resulting in 9,602 plasma glucose measurements. Latent class trajectories with a cubic specification for time were fitted to identify different patterns of plasma glucose change during the oral glucose tolerance test. Cardiometabolic risk factor profiles were compared between the identified groups. Using latent class trajectory analysis, five glucose response curves were identified. Despite similar fasting and 2-h values, glucose peaks and peak times varied greatly between groups, ranging from 7–12 mmol/L, and 35–70 min. The group with the lowest and earliest plasma glucose peak had the lowest estimated cardiovascular risk, while the group with the most delayed plasma glucose peak and the highest 2-h value had the highest estimated risk. One group, with normal fasting and 2-h values, exhibited an unusual profile, with the highest glucose peak and the highest proportion of smokers and men. The heterogeneity in glucose response curves and the distinct cardiometabolic risk profiles may reflect different underlying physiologies. Our results warrant more detailed studies to identify the source of the heterogeneity across the different phenotypes and whether these differences play a role in the development of type 2 diabetes and cardiovascular disease.

Invasively Measured Aortic Systolic Blood Pressure and Office Systolic Blood Pressure in Cardiovascular Risk Assessment: A Prospective Cohort Study

Aortic systolic blood pressure (BP) represents the hemodynamic cardiac and cerebral burden more directly than office systolic BP. Whether invasively measured aortic systolic BP confers additional prognostic value beyond office BP remains debated. In this study, office systolic BP and invasively measured aortic systolic BP were recorded in 21 908 patients (mean age: 63 years; 58% men; 14% with diabetes mellitus) with stable angina pectoris undergoing elective coronary angiography during January 2001 to December 2012. Multivariate Cox models were used to assess the association with incident myocardial infarction, stroke, and death. Discrimination and reclassification were assessed using Harrell’s C and the Continuous Net Reclassification Index. Data were analyzed with and without stratification by diabetes mellitus status. During a median follow-up period of 3.7 years (range: 0.1–10.8 years), 422 strokes, 511 myocardial infarctions, and 1530 deaths occurred. Both office and aortic systolic BP were associated with stroke in patients with diabetes mellitus (hazard ratio per 10 mm Hg, 1.18 [95% confidence interval, 1.07–1.30] and 1.14 [95% confidence interval, 1.05–1.24], respectively) and with myocardial infarction in patients without diabetes mellitus (hazard ratio, 1.07 [95% confidence interval, 1.02–1.12] and 1.05 [95% confidence interval, 1.01–1.10], respectively). In models including both BP measurements, aortic BP lost statistical significance and aortic BP did not confer improvement in either C-statistics or net reclassification analysis. In conclusion, invasively measured aortic systolic BP does not add prognostic information about cardiovascular outcomes and all-cause mortality compared with office BP in patients with stable angina pectoris, either with or without diabetes mellitus.

Glucose patterns during the OGTT and risk of future diabetes in an urban Indian population: The CARRS study.

AIMS Traditionally, fasting and 2-hour post challenge plasma glucose have been used to diagnose diabetes. However, evidence indicates that clinically relevant pathophysiological information can be obtained by adding intermediate time-points to a standard oral glucose tolerance test (OGTT). METHODS We studied a population-based sample of 3666 Asian Indians without diabetes from the CARRS-Chennai Study, India. Participants underwent a three-point (fasting, 30-min, and 2-h) OGTT at baseline. Patterns of glycemic response during OGTT were identified using latent class mixed-effects models. After a median follow-up of two years, participants had a second OGTT. Logistic regression adjusted for diabetes risk factors was used to compare risk of incident diabetes among participants in different latent classes. RESULTS We identified four latent classes with different glucose patterns (Classes 1-4). Glucose values for Classes 1, 2, and 4 ranked consistently at all three time-points, but at gradually higher levels. However, Class 3 represented a distinct pattern, characterized by high 30-min (30minPG), normal fasting (FPG) and 2-h (2hPG) plasma glucose, moderately high insulin sensitivity, and low acute insulin response. Approximately 22% of participants were categorized as Class 3, and had a 10-fold risk of diabetes compared to the group with the most favorable glucose response, despite 92.5% of Class 3 participants having normal glucose tolerance (NGT) at baseline. CONCLUSIONS Elevated 30minPG is associated with high risk of incident diabetes, even in individuals classified as NGT by a traditional OGTT. Assessing 30minPG may identify a subgroup of high-risk individuals who remained unidentified by traditional measures.

Association between coffee or caffeine consumption and fecundity and fertility: a systematic review and dose–response meta-analysis

Objective The aim was to investigate whether coffee or caffeine consumption is associated with reproductive endpoints among women with natural fertility (ie, time to pregnancy [TTP] and spontaneous abortion [SAB]) and among women in fertility treatment (ie, clinical pregnancy rate or live birth rate). Design This study was a systematic review and dose–response meta-analysis including data from case–control and cohort studies. Methods An extensive literature search was conducted in MEDLINE and Embase, with no time and language restrictions. Also, reference lists were searched manually. Two independent reviewers assessed the manuscript quality using the Newcastle–Ottawa Scale (NOS). A two-stage dose–response meta-analysis was applied to assess a potential association between coffee/caffeine consumption and the outcomes: TTP, SAB, clinical pregnancy, and live birth. Heterogeneity between studies was assessed using Cochrane Q-test and I2 statistics. Publication bias was assessed using Egger’s regression test. Results The pooled results showed that coffee/caffeine consumption is associated with a significantly increased risk of SAB for 300 mg caffeine/day (relative risk [RR]: 1.37, 95% confidence interval [95% CI]: 1.19; 1.57) and for 600 mg caffeine/day (RR: 2.32, 95% CI: 1.62; 3.31). No association was found between coffee/caffeine consumption and outcomes of fertility treatment (based on two studies). No clear association was found between exposure to coffee/caffeine and natural fertility as measured by fecundability odds ratio (based on three studies) or waiting TTP (based on two studies). Conclusion Results from this meta-analysis support the growing evidence of an association between coffee/caffeine intake and the risk of SAB. However, viewing the reproductive capacity in a broader perspective, there seems to be little, if any, association between coffee/caffeine consumption and fecundity. In general, results from this study are supportive of a precautionary principle advised by health organizations such as European Food Safety Authority (EFSA) and World Health Organization (WHO), although the advised limit of a maximum of two to three cups of coffee/200–300 mg caffeine per day may be too high.

Clustering of microvascular complications in Type 1 diabetes mellitus

AIMS To describe to what extent microvascular complications exhibit clustering in persons with Type 1 diabetes, and to assess whether the presence of one complication modified the strength of the association between the other two. METHODS We conducted a cross-sectional analysis of the electronic medical records of 2276 persons with Type 1 diabetes treated in a specialized care hospital in Denmark in 2013. We used log-linear analysis to describe associations between diabetic kidney disease, neuropathy and retinopathy and logistic regression models to quantify the magnitude of associations adjusting for potential confounders. RESULTS The median duration of diabetes was 24 years and median HbA1c was 63 mmol/mol (7.9%). We found strong indication of clustering and found no evidence that presence of one complication modified the association between the other two. In models adjusted for diabetes duration and HbA1c, persons with neuropathy had an OR of 2.15 (95% CI: 1.73-2.66) for concurrent diabetic kidney disease. Those with retinopathy had an OR of 2.49 (1.92-3.24) for diabetic kidney disease and of 2.66 (1.94-3.64) for neuropathy. CONCLUSIONS Microvascular complications in persons with Type 1 diabetes exhibit strong clustering. However, the association between any pair of complications is not modified by the presence of the third.

Assessment of time to glucose peak during an oral glucose tolerance test

Marlise E. A. van Eersel1 Susanne H. Meeuwisse–Pasterkamp2 Anneke C. Muller Kobold3 Linda C. Meiners4 Wilfred F. den Dunnen5 Leo J. Hofland6 Gerrit van den Berg1 1Department of Endocrinology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands 2Department of Internal Medicine, Antonius Hospital Sneek, Sneek, The Netherlands 3Department of Laboratory Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands 4Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands 5Department of Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands 6Department of Internal Medicine, Division of Endocrinology, University Medical Center Rotterdam, Erasmus Medical Center, Rotterdam, The Netherlands

Prediction of First Cardiovascular Disease Event in Type 1 Diabetes: The Steno T1 Risk Engine

Background— Patients with type 1 diabetes mellitus are at increased risk of developing cardiovascular disease (CVD), but they are currently undertreated. There are no risk scores used on a regular basis in clinical practice for assessing the risk of CVD in type 1 diabetes mellitus. Methods and Results— From 4306 clinically diagnosed adult patients with type 1 diabetes mellitus, we developed a prediction model for estimating the risk of first fatal or nonfatal CVD event (ischemic heart disease, ischemic stroke, heart failure, and peripheral artery disease). Detailed clinical data including lifestyle factors were linked to event data from validated national registers. The risk prediction model was developed by using a 2-stage approach. First, a nonparametric, data-driven approach was used to identify potentially informative risk factors and interactions (random forest and survival tree analysis). Second, based on results from the first step, Poisson regression analysis was used to derive the final model. The final CVD prediction model was externally validated in a different population of 2119 patients with type 1 diabetes mellitus. During a median follow-up of 6.8 years (interquartile range, 2.9–10.9) a total of 793 (18.4%) patients developed CVD. The final prediction model included age, sex, diabetes duration, systolic blood pressure, low-density lipoprotein cholesterol, hemoglobin A1c, albuminuria, glomerular filtration rate, smoking, and exercise. Discrimination was excellent for a 5-year CVD event with a C-statistic of 0.826 (95% confidence interval, 0.807–0.845) in the derivation data and a C-statistic of 0.803 (95% confidence interval, 0.767–0.839) in the validation data. The Hosmer-Lemeshow test showed good calibration (P>0.05) in both cohorts. Conclusions— This high-performing CVD risk model allows for the implementation of decision rules in a clinical setting.