64 research outputs found

    Risk prediction to inform surveillance of chronic kidney disease in the US Healthcare Safety Net: a cohort study.

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    BackgroundThe capacity of electronic health record (EHR) data to guide targeted surveillance in chronic kidney disease (CKD) is unclear. We sought to leverage EHR data for predicting risk of progressing from CKD to end-stage renal disease (ESRD) to help inform surveillance of CKD among vulnerable patients from the healthcare safety-net.MethodsWe conducted a retrospective cohort study of adults (n = 28,779) with CKD who received care within 2 regional safety-net health systems during 1996-2009 in the Western United States. The primary outcomes were progression to ESRD and death as ascertained by linkage with United States Renal Data System and Social Security Administration Death Master files, respectively, through September 29, 2011. We evaluated the performance of 3 models which included demographic, comorbidity and laboratory data to predict progression of CKD to ESRD in conditions commonly targeted for disease management (hypertension, diabetes, chronic viral diseases and severe CKD) using traditional discriminatory criteria (AUC) and recent criteria intended to guide population health management strategies.ResultsOverall, 1730 persons progressed to end-stage renal disease and 7628 died during median follow-up of 6.6 years. Performance of risk models incorporating common EHR variables was highest in hypertension, intermediate in diabetes and chronic viral diseases, and lowest in severe CKD. Surveillance of persons who were in the highest quintile of ESRD risk yielded 83-94 %, 74-95 %, and 75-82 % of cases who progressed to ESRD among patients with hypertension, diabetes and chronic viral diseases, respectively. Similar surveillance yielded 42-71 % of ESRD cases among those with severe CKD. Discrimination in all conditions was universally high (AUC ≥0.80) when evaluated using traditional criteria.ConclusionsRecently proposed discriminatory criteria account for varying risk distribution and when applied to common clinical conditions may help to inform surveillance of CKD in diverse populations

    The Glucagon Receptor Is Required for the Adaptive Metabolic Response to Fasting

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    SummaryGlucagon receptor (Gcgr) signaling maintains hepatic glucose production during the fasting state; however, the importance of the Gcgr for lipid metabolism is unclear. We show here that fasted Gcgr−/− mice exhibit a significant increase in hepatic triglyceride secretion and fasting increases fatty acid oxidation (FAO) in wild-type (WT) but not in Gcgr−/− mice. Moreover fasting upregulated the expression of FAO-related hepatic mRNA transcripts in Gcgr+/+ but not in Gcgr−/− mice. Exogenous glucagon administration reduced plasma triglycerides in WT mice, inhibited TG synthesis and secretion, and stimulated FA beta oxidation in Gcgr+/+ hepatocytes. The actions of glucagon on TG synthesis and FAO were abolished in PPARα−/− hepatocytes. These findings demonstrate that the Gcgr receptor is required for control of lipid metabolism during the adaptive metabolic response to fasting

    Childhood Height Growth Rate Association With the Risk of Islet Autoimmunity and Development of Type 1 Diabetes

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    ContextRapid growth has been suggested to promote islet autoimmunity and progression to type 1 diabetes (T1D). Childhood growth has not been analyzed separately from the infant growth period in most previous studies, but it may have distinct features due to differences between the stages of development. Objective We aimed to analyze the association of childhood growth with development of islet autoimmunity and progression to T1D diagnosis in children 1 to 8 years of age.MethodsLongitudinal data of childhood growth and development of islet autoimmunity and T1D were analyzed in a prospective cohort study including 10 145 children from Finland, Germany, Sweden, and the United States, 1-8 years of age with at least 3 height and weight measurements and at least 1 measurement of islet autoantibodies. The primary outcome was the appearance of islet autoimmunity and progression from islet autoimmunity to T1D.ResultsRapid increase in height (cm/year) was associated with increased risk of seroconversion to glutamic acid decarboxylase autoantibody, insulin autoantibody, or insulinoma-like antigen-2 autoantibody (hazard ratio [HR] = 1.26 [95% CI = 1.05, 1.51] for 1-3 years of age and HR = 1.48 [95% CI = 1.28, 1.73] for >3 years of age). Furthermore, height rate was positively associated with development of T1D (HR = 1.80 [95% CI = 1.15, 2.81]) in the analyses from seroconversion with insulin autoantibody to diabetes.ConclusionRapid height growth rate in childhood is associated with increased risk of islet autoimmunity and progression to T1D. Further work is needed to investigate the biological mechanism that may explain this association.</p

    Beta cell function in participants with single or multiple islet autoantibodies at baseline in the TEDDY Family Prevention Study: TEFA

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    AimThe aim of the present study was to assess beta cell function based on an oral glucose tolerance test (OGTT) in participants with single islet autoantibody or an intravenous glucose tolerance test (IvGTT) in participants with multiple islet autoantibodies.Materials and methodsHealthy participants in Sweden and Finland, between 2 and 49.99 years of age previously identified as positive for a single (n = 30) autoantibody to either insulin, glutamic acid decarboxylase, islet antigen-2, zinc transporter 8 or islet cell antibodies or multiple autoantibodies (n = 46), were included. Participants positive for a single autoantibody underwent a 6-point OGTT while participants positive for multiple autoantibodies underwent an IvGTT. Glucose, insulin and C-peptide were measured from OGTT and IvGTT samples.ResultsAll participants positive for a single autoantibody had a normal glucose tolerance test with 120 minutes glucose below 7.70 mmol/L and HbA1c values within the normal range (ConclusionParticipants positive for a single autoantibody appeared to have a normal beta cell function. Participants positive for three or more autoantibodies had a lower FPIR as compared to participants with two autoantibodies, supporting the view that their beta cell function had deteriorated.</p

    Prognostic imaging biomarkers for diabetic kidney disease (iBEAt):study protocol

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    Background: Diabetic kidney disease (DKD) remains one of the leading causes of premature death in diabetes. DKD is classified on albuminuria and reduced kidney function (estimated glomerular filtration rate (eGFR)) but these have modest value for predicting future renal status. There is an unmet need for biomarkers that can be used in clinical settings which also improve prediction of renal decline on top of routinely available data, particularly in the early stages. The iBEAt study of the BEAt-DKD project aims to determine whether renal imaging biomarkers (magnetic resonance imaging (MRI) and ultrasound (US)) provide insight into the pathogenesis and heterogeneity of DKD (primary aim) and whether they have potential as prognostic biomarkers in DKD (secondary aim). Methods: iBEAt is a prospective multi-centre observational cohort study recruiting 500 patients with type 2 diabetes (T2D) and eGFR ≥30 ml/min/1.73m2. At baseline, blood and urine will be collected, clinical examinations will be performed, and medical history will be obtained. These assessments will be repeated annually for 3 years. At baseline each participant will also undergo quantitative renal MRI and US with central processing of MRI images. Biological samples will be stored in a central laboratory for biomarker and validation studies, and data in a central data depository. Data analysis will explore the potential associations between imaging biomarkers and renal function, and whether the imaging biomarkers improve the prediction of DKD progression. Ancillary substudies will: (1) validate imaging biomarkers against renal histopathology; (2) validate MRI based renal blood flow measurements against H2O15 positron-emission tomography (PET); (3) validate methods for (semi-)automated processing of renal MRI; (4) examine longitudinal changes in imaging biomarkers; (5) examine whether glycocalyx and microvascular measures are associated with imaging biomarkers and eGFR decline; (6) explore whether the findings in T2D can be extrapolated to type 1 diabetes. Discussion: iBEAt is the largest DKD imaging study to date and will provide valuable insights into the progression and heterogeneity of DKD. The results may contribute to a more personalised approach to DKD management in patients with T2D. Trial registration: Clinicaltrials.gov (NCT03716401)

    Evaluating prediction performance of longitudinal biomarkers under cohort and two-phase study designs

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    Thesis (Ph.D.)--University of Washington, 2015Risk prediction and evaluation of predictions based on longitudinal biomarkers are of interest in treatment selection, preventive medicine and management of chronic diseases. Methods to evaluate risk predictions in a longitudinal setting are limited to the area under the receiver operating characteristic curves and prediction error. In this dissertation, we evaluate two approaches to risk prediction in the longitudinal setting: joint modeling and partly conditional modeling. We develop estimation procedures for more flexible and robust partly conditional models, demonstrate their adaptability and applicability, and provide a smoothing technique to account for measurement error in marker data. We develop nonparametric estimators of clinically relevant measures of prediction quality in the longitudinal setting under cohort, case-cohort, stratified case-cohort and nested case-control study designs. We provide resampling-based inference procedures for all estimators under the four study designs. We evaluate our methods using simulation studies and illustrate them on the End Stage Renal Disease Study dataset and a nested case-control study within the HALT-C clinical trial

    Homelessness and Risk of End-stage Renal Disease

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    To identify homeless people with chronic kidney disease (CKD) who were at highest risk for end-stage renal disease (ESRD), we studied 982 homeless and 15,674 domiciled people with CKD receiving public health care. We developed four risk prediction models for the primary outcome of ESRD. Overall, 71 homeless and 888 domiciled people progressed to ESRD during follow-up (median: 6.6 years). Homeless people with CKD experienced significantly higher incidence rates of ESRD than poor but domiciled peers. Most homeless people who developed progressive CKD were readily identifiable well before ESRD using a prediction model with five common variables. We estimated that program following homeless people in the highest decile of ESRD risk would have captured 64-85% of those who eventually progressed to ESRD within five years. Thus, an approach targeting homeless people at high risk for ESRD appears feasible and could reduce substantial morbidity and costs incurred by this highly vulnerable group

    Parental anxiety after 5 years of participation in a longitudinal study of children at high risk of type 1 diabetes

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    Aim: Parents of children participating in screening studies may experience increased levels of anxiety. The aim of this study was to assess parental anxiety levels after 5 years of participation in the Diabetes Prediction in Skåne study. Associations between parental anxiety about their child developing type 1 diabetes and clinical, demographic, and immunological factors were analyzed. Method: Mothers and fathers of participating 5-year-old children answered a questionnaire regarding parental anxiety associated with their child's increased risk of type 1 diabetes. Anxiety levels were assessed using the State Anxiety Inventory scale. Data were analyzed using logistic and multinomial regression. Results: Parents of 2088 5-year-old children participated. Both parents answered the questionnaire for 91.2% (n = 1904) of children. In 67.1% of families, neither parent reported being anxious that their child had an increased risk of developing type 1 diabetes. Anxiety was higher in mothers of children positive for autoantibodies (OR 2.21 95% CI 1.41, 3.48, P <.001) and those perceiving their child had a higher risk for type 1 diabetes (2.01; 1.29, 3.13, P =.002). Frequency of worry was associated with parental anxiety (mothers 5.33; 3.48, 8.17, P <.001, fathers 5.27; 3.51, 7.92, P <.001). Having a family member with type 1 diabetes and having lower education level were also associated with increased anxiety. Conclusions: Diabetes in the family, the child's autoantibody status, education level, frequency of worry and risk perception where associated with higher parental anxiety. These findings add to our understanding of the impact of screening for type 1 diabetes in children on parental anxiety
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