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  • 1.
    Ahlqvist, Emma
    et al.
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Storm, Petter
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Käräjämäki, Annemarie
    Department of Primary Health Care, Vaasa Central Hospital, Finland.
    Martinell, Mats
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Family Medicine and Preventive Medicine.
    Dorkhan, Mozhgan
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Carlsson, Annelie
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, SE-22185 Lund, Sweden.
    Vikman, Petter
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Prasad, Rashmi
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Mansour Aly, Dina
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Almgren, Peter
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Wessman, Ylva
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Shaat, Nael
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Spegel, Peter
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Mulder, Hindrik
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Lindholm, Eero
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Melander, Olle
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Hansson, Ola
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Malmqvist, Ulf
    Clinical Research and Trial Center, Lund University Hospital, Sweden.
    Lernmark, Åke
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Lahti, Kaj
    Department of Primary Health Care, Vaasa Central Hospital, Finland.
    Forsén, Tom
    Department of Primary Health Care, Vaasa Central Hospital, Finland.
    Tuomi, Tiinamaija
    Abdominal Center, Endocrinology, Helsinki University Central Hospital; Research Program for Diabetes and Obesity, University of Helsinki, Helsinki, Finland.
    Rosengren, Anders
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Groop, Leif
    Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.
    Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables2018In: The Lancet Diabetes and Endocrinology, ISSN 2213-8587, E-ISSN 2213-8595, Vol. 6, no 5, p. 361-369Article in journal (Refereed)
    Abstract [en]

     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.

  • 2.
    Martinell, Mats
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Family Medicine and Preventive Medicine.
    Dorkhan, Mozhgan
    Lund Univ, Dept Clin Sci Malmo, Uppsala, Sweden..
    Stålhammar, Jan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Family Medicine and Preventive Medicine.
    Storm, Petter
    Lund Univ, Dept Clin Sci Malmo, Uppsala, Sweden..
    Groop, Leif
    Lund Univ, Dept Clin Sci Malmo, Uppsala, Sweden..
    Gustavsson, Carin
    Lund Univ, Dept Clin Sci Malmo, Uppsala, Sweden..
    Prevalence and risk factors for diabetic retinopathy at diagnosis (DRAD) in patients recently diagnosed with type 2 diabetes (T2D) or latent autoimmune diabetes in the adult (LADA)2016In: Journal of diabetes and its complications, ISSN 1056-8727, E-ISSN 1873-460X, Vol. 30, no 8, p. 1456-1461Article in journal (Refereed)
    Abstract [en]

    PURPOSE: 

    To study prevalence of diabetic retinopathy (DR) at diagnosis (DRAD) and to estimate contributing risk by sociodemographic, cardiovascular and metabolic characteristics present in patients recently diagnosed with type 2 diabetes (T2D) or latent autoimmune diabetes in the adult (LADA).

    METHODS: 

    Patients (n=2174) recently diagnosed T2D (93%) or LADA (7%) were included upon arrival for their baseline DR screening. Fundus photographs of 4902 eyes were graded by a senior ophthalmologist according to the International Diabetic Retinopathy Disease Severity Scale. Official registers held by Statistics Sweden provided sociodemographic variables. The National Patient Register and Swedish Prescribed Drug Register were used to assess cardiovascular risk. Beta cell function (HOMA2%b) and insulin sensitivity (HOMA2%s) were estimated from fasting (f) C-Peptide using the homeostasis model assessment (HOMA) 2 calculator. Odds ratios (OR) for DRAD were estimated using generalized estimating equation models.

    RESULTS: 

    The prevalence of DRAD was 12% (7% mild and 5% moderate) and of diabetic macular edema it was 11% (all within vascular arch). The prevalence did not significantly differ between T2D and LADA. Due to sample size, the regression analysis of LADA patients did not yield any significant estimates. In T2D low educational level (≤9years) increased risk for DRAD by 44% (OR 1.44; 95% CI 1.07-1.93) and <50% beta-cell function adjusted for HbA1c and insulin sensitivity at diagnosis increased the risk by 77% (OR 1.77; 95% CI 1.28-2.44). For every unit increase in BMI, risk for DRAD decreased by 3% (OR 0.97; 95% CI 0.95-0.99).

    CONCLUSIONS: 

    DRAD prevalence in patients recently diagnosed with T2D or is 12%. Low educational level and low beta cell function at diagnosis are risk factors for DRAD. Estimation of beta cell function from (f)C-Peptide and (f)P-Glucose may be a valuable tool in identifying patients at risk for DRAD.

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