Use of the Michigan Neuropathy Screening Instrument as a measure of distal symmetrical peripheral neuropathy in Type 1 diabetes: results from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications

Aims  The Michigan Neuropathy Screening Instrument (MNSI) is used to assess distal symmetrical peripheral neuropathy in diabetes. It includes two separate assessments: a 15‐item self‐administered questionnaire and a lower extremity examination that includes inspection and assessment of vibratory sensation and ankle reflexes. The purpose of this study was to evaluate the performance of the MNSI in detecting distal symmetrical peripheral neuropathy in patients with Type 1 diabetes and to develop new scoring algorithms. Methods  The MNSI was performed by trained personnel at each of the 28 Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications clinical sites. Neurologic examinations and nerve conduction studies were performed during the same year. Confirmed clinical neuropathy was defined by symptoms and signs of distal symmetrical peripheral neuropathy based on the examination of a neurologist and abnormal nerve conduction findings in ≥ 2 anatomically distinct nerves among the sural, peroneal and median nerves. Results  We studied 1184 subjects with Type 1 diabetes. Mean age was 47 years and duration of diabetes was 26 years. Thirty per cent of participants had confirmed clinical neuropathy, 18% had ≥ 4 and 5% had ≥ 7 abnormal responses on the MNSI questionnaire, and 33% had abnormal scores (≥ 2.5) on the MNSI examination. New scoring algorithms were developed and cut points defined to improve the performance of the MNSI questionnaire, examination and the combination of the two. Conclusions  Altering the cut point to define an abnormal test from ≥ 7 abnormal to ≥ 4 abnormal items improves the performance of the MNSI questionnaire. The MNSI is a simple, non‐invasive and valid measure of distal symmetrical peripheral neuropathy in Type 1 diabetes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92152/1/j.1464-5491.2012.03644.x.pd

Genetic insights into resting heart rate and its role in cardiovascular disease

Funding Information: We thank all participants for their participation and valuable contributions. This research has been conducted using the UK Biobank Resource under application number 12010. The work of N.V. was supported by NWO VENI grant 016.186.125. We thank 23andMe and the 23andMe Research Team for their contribution sharing their data and performing the GWAS analysis in the 23andMe cohort. P.V. received an unrestricted grant from GlaxoSmithkline to build the CoLaus study. N.J.T. is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215-2001), the MRC Integrative Epidemiology Unit (MC_UU_00011/1) and works within the CRUK Integrative Cancer Epidemiology Program (C18281/A29019). A detailed list of acknowledgements and funding is provided in Supplementary Data per cohort. We also thank all individuals that contributed to the generation of software programs, algorithms and genetic summary statistics. Support for title page creation and format was provided by AuthorArranger, a tool developed at the National Cancer Institute. Authors involved in the funding of the cohorts are listed below. Meta-analyses, Lifelines, PREVEND, UK Biobank: P.v.d.H.; ADDITION-PRO: T.H.; ADVANCE: C.I.; ADVANCE: T.A.; AGES: L.Launer, V.G.; ASCOT: P.Sever, P.B.M.; BC1936: N.G.; BioMe: E.P.B., R.J.F.L.; BRIGHT: P.B.M.; CHS: B.M.P.; CoLaus: P.V.; Croatia-Korcula: O.P., C.H.; DCCT/EDIC: D.R., The DCCT/EDIC Research Group, A.D.P.; DESIR: B.B., P.F.; DGI: L.G.; EPIC-Norfolk: N.J.W.; ERF: C.M.v.D.; Fenland: N.J.W.; FINCAVAS: M.K.; Finrisk: M.P.; FUSION: M.B.; GENOA: P.A.P., S.L.R.K.; GerMIFSs: H.Schunkert, J.E.; GoDARTS: C.N.A.P; GOOD: M.L., C.O.; HBCS: J.G.E.; HERITAGE: T.R., D.C.R., C.B.; HPFS / NHS: P.K.; HRS: D.R.Weir; HYPERGENES: K.S.S., D.C.; InCHIANTI: S.Bandinelli, L.Ferrucci; INGI-CARL: M.P.C.; INGI-FVG: G.G.; JHS: A.Correa; KORA F3: T.M., S.K.; KORA S4: K.Strauch., A.P.; LOLIPOP: J.C.C., J.S.K.; LURIC: W.M.; MESA: J.I.R.; MICROS: A.H.; MPP: O.M.; J.G.S.; NBS: L.A.L.M.K.; NEO: R.d.M.; NESDA: B.W.J.H.P.; NSPHS: Å.J.; ORCADES: J.F.W.; PIVUS: L.L.; PROSPER: P.W.M., J.W.J.; SardiNIA: E.L.L.; SCES: C.Y.C.; SHIP: S.B.F., M.D.; SIMES: T.Y.W.; TRAILS: A.J.O.; TWINS: J.O.; ULSAM: A.P.M., C.Lindgren; YFS: O.T.R., T.L. Funding Information: We thank all participants for their participation and valuable contributions. This research has been conducted using the UK Biobank Resource under application number 12010. The work of N.V. was supported by NWO VENI grant 016.186.125. We thank 23andMe and the 23andMe Research Team for their contribution sharing their data and performing the GWAS analysis in the 23andMe cohort. P.V. received an unrestricted grant from GlaxoSmithkline to build the CoLaus study. N.J.T. is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215-2001), the MRC Integrative Epidemiology Unit (MC_UU_00011/1) and works within the CRUK Integrative Cancer Epidemiology Program (C18281/A29019). A detailed list of acknowledgements and funding is provided in Supplementary Data 1 per cohort. We also thank all individuals that contributed to the generation of software programs, algorithms and genetic summary statistics. Support for title page creation and format was provided by AuthorArranger, a tool developed at the National Cancer Institute. Authors involved in the funding of the cohorts are listed below. Meta-analyses, Lifelines, PREVEND, UK Biobank : P.v.d.H.; ADDITION-PRO : T.H.; ADVANCE : C.I.; ADVANCE : T.A.; AGES : L.Launer, V.G.; ASCOT : P.Sever, P.B.M.; BC1936 : N.G.; BioMe : E.P.B., R.J.F.L.; BRIGHT : P.B.M.; CHS : B.M.P.; CoLaus : P.V.; Croatia-Korcula : O.P., C.H.; DCCT/EDIC : D.R., The DCCT/EDIC Research Group, A.D.P.; DESIR : B.B., P.F.; DGI : L.G.; EPIC-Norfolk : N.J.W.; ERF : C.M.v.D.; Fenland : N.J.W.; FINCAVAS : M.K.; Finrisk : M.P.; FUSION : M.B.; GENOA : P.A.P., S.L.R.K.; GerMIFSs : H.Schunkert, J.E.; GoDARTS : C.N.A.P; GOOD : M.L., C.O.; HBCS : J.G.E.; HERITAGE : T.R., D.C.R., C.B.; HPFS / NHS: P.K.; HRS : D.R.Weir; HYPERGENES : K.S.S., D.C.; InCHIANTI : S.Bandinelli, L.Ferrucci; INGI-CARL: M.P.C.; INGI-FVG: G.G.; JHS: A.Correa; KORA F3: T.M., S.K.; KORA S4 : K.Strauch., A.P.; LOLIPOP : J.C.C., J.S.K.; LURIC : W.M.; MESA : J.I.R.; MICROS : A.H.; MPP : O.M.; J.G.S.; NBS : L.A.L.M.K.; NEO : R.d.M.; NESDA : B.W.J.H.P.; NSPHS : Å.J.; ORCADES : J.F.W.; PIVUS : L.L.; PROSPER : P.W.M., J.W.J.; SardiNIA : E.L.L.; SCES : C.Y.C.; SHIP : S.B.F., M.D.; SIMES : T.Y.W.; TRAILS : A.J.O.; TWINS : J.O.; ULSAM : A.P.M., C.Lindgren; YFS : O.T.R., T.L. Publisher Copyright: © 2023, The Author(s).Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.Peer reviewe

Management and efficacy of intensified insulin therapy starting in outpatients

Diabetic patients under multiple injection insulin therapy (i.e., intensified insulin therapy, IIT) usually start this treatment during hospitalization. We report here on the logistics, efficacy, and safety of IIT, started in outpatients. Over 8 months, 52 type I and type II diabetics were followed up whose insulin regimens consecutively had been changed from conventional therapy to IIT. Two different IIT strategies were compared: free mixtures of regular and intermediate (12 hrs)-acting insulin versus the basal and prandial insulin treatment with preprandial injections of regular insulin, and ultralente (24 hrs-acting) or intermediate insulin for the basal demand. After 8 months HbA1 levels had decreased from 10.6%±2.4% to 8.0%±1.3% (means±SD). There was no difference between the two regimens with respect to metabolic control; but type II patients maintained the lowered HbA1 levels better than type I patients. Only two patients were hospitalized during the follow-up time because of severe hypoglycemia. An increase of body weight due to the diet liberalization during IIT became a problem in one-third of the patients. Our results suggest that outpatient initiation of IIT is safe and efficacious with respect to near-normoglycemic control. Weight control may become a problem in IIT patients

A model to estimate the lifetime health outcomes of patients with Type 2 diabetes: the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS no. 68)

<i>Aims/hypothesis</i> The aim of this study was to develop a simulation model for Type 2 diabetes that can be used to estimate the likely occurrence of major diabetes-related complications over a lifetime, in order to calculate health economic outcomes such as quality-adjusted life expectancy. <i>Methods</i> Equations for forecasting the occurrence of seven diabetes-related complications and death were estimated using data on 3642 patients from the United Kingdom Prospective Diabetes Study (UKPDS). After examining the internal validity, the UKPDS Outcomes Model was used to simulate the mean difference in expected quality-adjusted life years between the UKPDS regimens of intensive and conventional blood glucose control. <i>Results</i> The models forecasts fell within the 95% confidence interval for the occurrence of observed events during the UKPDS follow-up period. When the model was used to simulate event history over patients lifetimes, those treated with a regimen of conventional glucose control could expect 16.35 undiscounted quality-adjusted life years, and those receiving treatment with intensive glucose control could expect 16.62 quality-adjusted life years, a difference of 0.27 (95% CI: –0.48 to 1.03). <i>Conclusions/interpretations</i> The UKPDS Outcomes Model is able to simulate event histories that closely match observed outcomes in the UKPDS and that can be extrapolated over patients lifetimes. Its validity in estimating outcomes in other groups of patients, however, remains to be evaluated. The model allows simulation of a range of long-term outcomes, which should assist in informing future economic evaluations of interventions in Type 2 diabetes

Prevalence of diabetic peripheral neuropathy and relation to glycemic control therapies at baseline in the BARI 2D cohort

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74968/1/j.1529-8027.2009.00200.x.pd

Skin collagen advanced glycation endproducts (AGEs) and the long-term progression of sub-clinical cardiovascular disease in type 1 diabetes

BACKGROUND: We recently reported strong associations between eight skin collagen AGEs and two solubility markers from skin biopsies obtained at DCCT study closeout and the long-term progression of microvascular disease in EDIC, despite adjustment for mean glycemia. Herein we investigated the hypothesis that some of these AGEs (fluorescence to be reported elsewhere) correlate with long-term subclinical cardiovascular disease (CVD) measurements, i.e. coronary artery calcium score (CAC) at EDIC year 7-9 (n = 187), change of carotid intima-media thickness (IMT) from EDIC year 1 to year 6 and 12 (n = 127), and cardiac MRI outcomes at EDIC year 15-16 (n = 142). METHODS: Skin collagen AGE measurements obtained from stored specimens were related to clinical data from the DCCT/EDIC using Spearman correlations and multivariable logistic regression analyses. RESULTS: Spearman correlations showed furosine (early glycation) was associated with future mean CAC (p \u3c 0.05) and CAC \u3e0 (p = 0.39), but not with CAC score100. Glucosepane and pentosidine crosslinks, methylglyoxal hydroimidazolones (MG-H1) and pepsin solubility (inversely) correlated with IMT change from year 1 to 6(all P \u3c 0.05). Left ventricular (LV) mass (cMRI) correlated with MG-H1, and inversely with pepsin solubility (both p \u3c 0.05), while the ratio LV mass/end diastolic volume correlated with furosine and MG-H1 (both p \u3c 0.05), and highly with CML (p \u3c 0.01). In multivariate analysis only furosine (p = 0.01) was associated with CAC. In contrast IMT was inversely associated with lower collagen pepsin solubility and positively with glucosepane, CONCLUSIONS: In type 1 diabetes, multiple AGEs are associated with IMT progression in spite of adjustment for A1c implying a likely participatory role of glycation and AGE mediated crosslinking on matrix accumulation in coronary arteries. This may also apply to functional cardiac MRI outcomes, especially left ventricular mass. In contrast, early glycation measured by furosine, but not AGEs, was associated with CAC score, implying hyperglycemia as a risk factor in calcium deposition perhaps via processes independent of glycation. TRIAL REGISTRATION: Registered at Clinical trial reg. nos. NCT00360815 and NCT00360893, http://www.clinicaltrials.gov

Significance of Epicardial and Intrathoracic Adipose Tissue Volume among Type 1 Diabetes Patients in the DCCT/EDIC: A Pilot Study.

Introduction Type 1 diabetes (T1DM) patients are at increased risk of coronary artery disease (CAD). This pilot study sought to evaluate the relationship between epicardial adipose tissue (EAT) and intra-thoracic adipose tissue (IAT) volumes and cardio-metabolic risk factors in T1DM. Method EAT/IAT volumes in 100 patients, underwent non-contrast cardiac computed tomography in the Diabetes Control and Complications Trial /Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study were measured by a certified reader. Fat was defined as pixels’ density of -30 to -190 Hounsfield Unit. The associations were assessed using–Pearson partial correlation and linear regression models adjusted for gender and age with inverse probability sample weighting. Results The weighted mean age was 43 years (range 32–57) and 53% were male. Adjusted for gender, Pearson correlation analysis showed a significant correlation between age and EAT/IAT volumes (both p Conclusion T1DM patients with greater BMI, WTH ratio, weighted HbA1c level, triglyceride level and AER≥300/ESRD had significantly larger EAT/IAT volumes. Larger sample size studies are recommended to evaluate independency

Quality of life in Type 1 (insulin-dependent) diabetic patients prior to and after pancreas and kidney transplantation in relation to organ function

Improvement of the quality of life in Type 1 (insulin-dependent) diabetic patients with severe late complications is one of the main goals of pancreas and/or kidney grafting. To assess the influences of these treatment modalities on the different aspects of the quality of life a cross-sectional study in 157 patients was conducted. They were categorized into patients pre-transplant without dialysis (n=29; Group A), pre-transplant under dialysis (n=44; Group B), post-transplant with pancreas and kidney functioning (n=31; Group C), post-transplant with functioning kidney, but insulin therapy (n=29; Group D), post-transplant under dialysis and insulin therapy again (n=15; Group E) and patients after single pancreas transplantation and rejection, with good renal function, but insulin therapy (n=9; Group F). All patients answered a mailed, self-administered questionnaire (217 questions) consisting of a broad spectrum of rehabilitation criteria. The results indicate a better quality of life in Groups C and D as compared to the other groups. In general the scores are highest in C, but without any significant difference to D. Impressive significant differences between C or D and the other groups were found especially in their satisfaction with physical capacity, leisure-time activities or the overall quality of life. The satisfaction with the latter is highest in C (mean±SEM: 4.0±0.2 on a 1 to 5-rating scale; significantly different from A: 3.1±0.1, B: 2.7±0.2 and E: 2.6±0.3; p<0.01), followed by D (3.8±0.2; significantly different from B and E; p<0.01). Group F shows a mean of 3.1±0.4, which is not significantly different from C. The percentages of patients in each group, who are not working: A: 38 %, B: 64 %, C: 74 %, D: 66 %, E: 87 % and F: 78 % indicate that there is no marked improvement in the vocational situation after successful grafting