Mats Martinell

Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables

BACKGROUND Diabetes is presently classified into two main forms, type 1 and type 2 diabetes, but type 2 diabetes in particular is highly heterogeneous. A refined classification could provide a powerful tool to individualise treatment regimens and identify individuals with increased risk of complications at diagnosis. METHODS We did data-driven cluster analysis (k-means and hierarchical clustering) in patients with newly diagnosed diabetes (n=8980) from the Swedish All New Diabetics in Scania cohort. Clusters were based on six variables (glutamate decarboxylase antibodies, age at diagnosis, BMI, HbA1c, and homoeostatic model assessment 2 estimates of β-cell function and insulin resistance), and were related to prospective data from patient records on development of complications and prescription of medication. Replication was done in three independent cohorts: the Scania Diabetes Registry (n=1466), All New Diabetics in Uppsala (n=844), and Diabetes Registry Vaasa (n=3485). Cox regression and logistic regression were used to compare time to medication, time to reaching the treatment goal, and risk of diabetic complications and genetic associations. FINDINGS We identified five replicable clusters of patients with diabetes, which had significantly different patient characteristics and risk of diabetic complications. In particular, individuals in cluster 3 (most resistant to insulin) had significantly higher risk of diabetic kidney disease than individuals in clusters 4 and 5, but had been prescribed similar diabetes treatment. Cluster 2 (insulin deficient) had the highest risk of retinopathy. In support of the clustering, genetic associations in the clusters differed from those seen in traditional type 2 diabetes. INTERPRETATION We stratified patients into five subgroups with differing disease progression and risk of diabetic complications. This new substratification might eventually help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes. FUNDING Swedish Research Council, European Research Council, Vinnova, Academy of Finland, Novo Nordisk Foundation, Scania University Hospital, Sigrid Juselius Foundation, Innovative Medicines Initiative 2 Joint Undertaking, Vasa Hospital district, Jakobstadsnejden Heart Foundation, Folkhälsan Research Foundation, Ollqvist Foundation, and Swedish Foundation for Strategic Research.

Increased Circulating Betatrophin Concentrations in Patients with Type 2 Diabetes

Betatrophin has recently been described as a key hormone to stimulate beta-cell mass expansion in response to insulin resistance and obesity in mice. The finding has generated an interest in the development of antidiabetic drugs with betatrophin as the active component. However, the circulating levels of betatrophin in patients with type 2 diabetes are not well known. Betatrophin concentrations in plasma of 27 type 2 diabetes patients and 18 gender-, age-, and BMI-matched controls were measured. Study participants were characterized with regard to BMI, waist and hip circumference, blood pressure, and fasting plasma blood lipids, creatinine, glucose, HbA1c, and C-peptide. HOMA2 indices were calculated. Betatrophin was 40% higher in patients with type 2 diabetes (893 ± 80 versus 639 ± 66 pg/mL). Betatrophin positively correlated with age in the controls and with HbA1c in the type 2 diabetes patients. All study participants were insulin resistant with mean HOMA2B IR in both groups exceeding 2 and HOMA2%S < 50%. Control individuals had impaired fasting glucose concentrations. In this report on betatrophin concentrations in type 2 diabetes and insulin resistance, elevated betatrophin levels were measured in the patients with type 2 diabetes. Future studies are clearly needed to delineate the exact role, if any, of betatrophin in regulating human beta-cell mass.

Prevalence and incidence of Type 2 diabetes and its complications 1996-2003-estimates from a Swedish population-based study

Aims  To determine the prevalence and incidence of Type 2 diabetes and its complications in Uppsala county, Sweden between 1996 and 2003.

Resource use and costs of type 2 diabetes in Sweden – estimates from population-based register data

Aims:  To examine medical resource use of Swedish patients with type 2 diabetes during 2000–2004 and to estimate annual costs of care.

Time to insulin treatment and factors associated with insulin prescription in Swedish patients with type 2 diabetes

AIMS The purpose of this study was to investigate the time between the start of OAD treatment and the initiation of insulin therapy and to identify the factors associated with insulin prescription among Swedish patients with type 2 diabetes in Uppsala County. METHODS Retrospective, population-based, primary-care data gathered within the Swedish RECAP-DM study were used to identify type 2 diabetic patients who initiated OAD treatment. A Kaplan-Meier survival estimate for time to initiation of insulin therapy was generated and factors associated with insulin prescription were tested using a Cox proportional-hazards model. RESULTS Within 6 years of starting OAD treatment, an estimated 25% of Swedish patients with type 2 diabetes will be prescribed insulin (95% CI: 0.23-0.26) and, within 10 years, this figure will rise to 42% (95% CI: 0.39-0.45). The probability of insulin prescription was increased in patients aged less than 65 years (HR=1.24, 95% CI: 1.03-1.50) and in those who initiated OAD treatment with more than one agent (HR=2.71, 95% CI: 2.15-3.43). HbA(1c) at the time of starting OAD treatment was also related to the probability of insulin prescription (HR=1.20, 95% CI: 1.146-1.25). CONCLUSION Many type 2 diabetic patients who begin treatment with an OAD will eventually be prescribed insulin. Age, disease severity and the type of prior treatment may affect the rate of the transition.

Automated data extraction—A feasible way to construct patient registers of primary care utilization

Abstract Introduction. Electronic medical records (EMRs) enable analysis of health care data by using data mining techniques to build research databases. Though the reliability of the data extraction process is crucial for the credibility of the final analysis, there are few published validations of this process. In this paper we validate the performance of an automated data mining tool on EMR in a primary care setting. Methods. The Pygargus Customized eXtraction Program (CXP) was programmed to find and then extract data from patients meeting criteria for type 2 diabetes mellitus (T2DM) at one primary health care clinic (PHC). The ability of CXP to extract relevant cases was assessed by comparing cases extracted by an EMR integrated search engine. The concordance of extracted data with the original EMR source was manually controlled. Results. Prevalence of T2DM was 4.0%, which correspond well to previous estimations. By searching for drug prescriptions, diagnosis codes, and laboratory values, 38%, 53%, and 91% of relevant cases were found, respectively. The sensitivity of CXP regarding extraction of relevant cases was 100%. The specificity was 99.9% due to 12 non-T2DM cases extracted. The congruity at single-item level was 99.6%. The 13 incorrect data items were all located in the same structural module. Conclusion. The CXP is a reliable and accurate data mining tool to extract selective data from EMR.

The impact of acute myocardial infarction and stroke on health care costs in patients with type 2 diabetes in Sweden

Background Estimates of the economic impact of cardiovascular events in patients with type 2 diabetes are scarce. The aim of this study was to determine the health care costs associated with acute myocardial infarction (AMI) and stroke in patients with type 2 diabetes in Sweden. Design Population-based open cohort study of 9941 patients with type 2 diabetes retrospectively identified in primary care records at 26 centres in Uppsala County. Methods Episodes of AMI and stroke suffered by study patients were tracked in the Swedish National Inpatient Register. Annual per patient costs of health care were computed for the years 2000-2004 using register data covering inpatient care, outpatient hospital care, primary care and drugs. Panel data regression was applied to determine the impact of suffering a first or repeat AMI or stroke on health care costs during the year of the event and in subsequent years. Results Total health care costs of patients suffering a first AMI/stroke increased by 4.1/6.5 during the year of the event [95% confidence interval (CI): 3.1-5.4/4.9-8.5] and by 1.1/1.4 during subsequent years (95% CI: 1.0-1.3/1.2-1.6), controlling for age, sex, the event of amputation and presence of renal failure, heart failure and diabetic eye disease. Total health care costs of patients suffering a first or repeat AMI/stroke increased by 4.1/6.4 during the year of an event (95% CI: 3.2-5.2/5.0-8.1) but were not significantly higher during subsequent years. Conclusion Estimates of the costs related to major cardiovascular complications of type 2 diabetes are critical input to economic evaluations.

Coffee consumption and the risk of latent autoimmune diabetes in adults-results from a Swedish case-control study

Coffee consumption is associated with a reduced risk of Type 2 diabetes. Our aim was to investigate if coffee intake may also reduce the risk of latent autoimmune diabetes in adults, an autoimmune form of diabetes with features of Type 2 diabetes.

Betatrophin in Diabetes Mellitus: the Epidemiological Evidence in Humans.

The prevalence of type 2 diabetes is increasing worldwide, and while numerous treatments exist, none of the current pharmacologic therapies is curative. Pharmacologic approaches that increase beta cell mass may present an avenue for actual cure. There have been numerous reports on factors that can induce beta cell proliferation in rodents, whereas there are still very limited data on the occurrence of beta cell proliferation in humans. The recent discovery of the hormone betatrophin, which in mice counteracted glucose intolerance induced by insulin resistance by potently stimulating beta cell proliferation, has boosted the hope for a new target for drug development for the treatment of diabetes mellitus in humans. With the encouraging preclinical findings as a background, this review presents the available clinical data on betatrophin and discusses its possible role in humans.

Prevalence of lipid abnormalities before and after introduction of lipid modifying therapy among Swedish patients with dyslipidemia (PRIMULA)

BackgroundData on the prevalence of dyslipidemia and attainment of goal/normal lipid levels in a Swedish population are scarce. The objective of this study is to estimate the prevalence of dyslipidemia and attainment of goal/normal lipid levels in patients treated with lipid modifying therapy (LMT).MethodsThis longitudinal retrospective observational study covers time periods before and after treatment. Data were collected from 1994-2007 electronic patient records in public primary healthcare centers in Uppsala County, Sweden. Patients were included if they had been treated with LMT and had at least one lipid abnormality indicating dyslipidemia and if complete lipid profile data were available. Thresholds levels for lipids were defined as per Swedish guidelines.ResultsAmong 5,424 patients included, at baseline, the prevalence of dyslipidemia (≥1 lipid abnormality) was by definition 100%, while this figure was 82% at follow-up. At baseline, 60% had elevated low-density lipoprotein (LDL-C) combined with low high-density lipoprotein (HDL-C) and/or elevated triglycerides (TG s), corresponding figure at follow-up was 36%. Low HDL-C and/or elevated TGs at follow-up remained at 69% for patients with type 2 diabetes mellitus (T2DM), 50% among patients with coronary heart disease (CHD) and 66% among patients with 10 year CHD risk >20%. Of the total sample, 40% attained goal levels of LDL-C and 18% attained goal/normal levels on all three lipid parameters.ConclusionsFocusing therapy on LDL-C reduction allows 40% of patients to achieve LDL-C goal and helps reducing triglyceride levels. Almost 60% of patients experience persistent HDL-C and/or triglyceride abnormality independently of LDL-C levels and could be candidates for additional treatments.