scholarly journals Index60 Identifies Individuals at Appreciable Risk for Stage 3 Among an Autoantibody-Positive Population With Normal 2-Hour Glucose Levels: Implications for Current Staging Criteria of Type 1 Diabetes

Diabetes Care ◽  
2021 ◽  
pp. dc210944
Author(s):  
Brandon M. Nathan ◽  
Maria J. Redondo ◽  
Heba Ismail ◽  
Laura Jacobsen ◽  
Emily K. Sims ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glucose Levels ◽  
Positive Population

scholarly journals Index60 Identifies Individuals at Appreciable Risk for Stage 3 Among an Autoantibody-Positive Population With Normal 2-Hour Glucose Levels: Implications for Current Staging Criteria of Type 1 Diabetes

2021 ◽  
Author(s):  
Brandon M. Nathan ◽  
Maria J. Redondo ◽  
Heba Ismail ◽  
Laura Jacobsen ◽  
Emily K. Sims ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Disease Stage ◽  
Composite Measure ◽  
C Peptide ◽  
Glucose Levels ◽  
Younger Age ◽  
Design And Methods ◽  
Hla Dr3 ◽  
Positive Population

<u>Objective</u><b>:</b> We assessed whether Index60, a composite measure of fasting C-peptide, 60-minute C-peptide, and 60-minute glucose, could improve the metabolic staging of type 1 diabetes for progression to clinical disease (stage 3) among autoantibody positive (Ab+) individuals with normal 2-hour glucose values (<140 mg/dL). <p><u>Research Design and Methods</u>: We analyzed 3058 Type 1 Diabetes TrialNet Pathway to Prevention participants, with 2-hour glucose<140 mg/dL and Index60<1.00 values from baseline OGTTs. Characteristics associated with type 1 diabetes (younger age, greater autoantibody positivity [Ab+], higher HLA DR3-DQ2/DR4-DQ8 prevalence, lower C-peptide) were compared among four mutually exclusive groups: top 2-hour glucose quartile only [HI-2HGLU], top Index60 quartile only [HI-IND60], both top quartiles [HI-BOTH], neither top quartile [LO-BOTH]. Additionally, within the 2-hour glucose distribution of <140 mg/dL, and separately within the Index60<1.00 distribution, comparisons were made between those above or below the medians.</p> <p><u>Results</u>: HI-IND60 and HI-BOTH were younger, with greater frequency of >2 Ab+, and lower C-peptide levels than either HI-2HGLU or LO-BOTH (all p<0.001). The cumulative incidence for stage 3 was greater for HI-IND60 and HI-BOTH than either HI-2HGLU or LO-BOTH (all p<0.001). Those with Index60 values above the median were younger, had higher ≥2Ab+ (p<0.001) and DR3-DQ2/DR4-DQ8 prevalence (p<0.001), and lower AUC C-peptide levels (p<0.001) than those below. Those above the 2-hour glucose median had higher AUC C-peptide levels (p<0.001), but otherwise did not differ from those below. </p> <p><u>Conclusion</u>: Index60 identifies individuals with characteristics of type 1 diabetes at appreciable risk for progression who would otherwise be missed by 2-hour glucose staging criteria. </p>

scholarly journals Index60 Identifies Individuals at Appreciable Risk for Stage 3 Among an Autoantibody-Positive Population With Normal 2-Hour Glucose Levels: Implications for Current Staging Criteria of Type 1 Diabetes

2021 ◽  
Author(s):  
Brandon M. Nathan ◽  
Maria J. Redondo ◽  
Heba Ismail ◽  
Laura Jacobsen ◽  
Emily K. Sims ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Disease Stage ◽  
Composite Measure ◽  
C Peptide ◽  
Glucose Levels ◽  
Younger Age ◽  
Design And Methods ◽  
Hla Dr3 ◽  
Positive Population

<u>Objective</u><b>:</b> We assessed whether Index60, a composite measure of fasting C-peptide, 60-minute C-peptide, and 60-minute glucose, could improve the metabolic staging of type 1 diabetes for progression to clinical disease (stage 3) among autoantibody positive (Ab+) individuals with normal 2-hour glucose values (<140 mg/dL). <p><u>Research Design and Methods</u>: We analyzed 3058 Type 1 Diabetes TrialNet Pathway to Prevention participants, with 2-hour glucose<140 mg/dL and Index60<1.00 values from baseline OGTTs. Characteristics associated with type 1 diabetes (younger age, greater autoantibody positivity [Ab+], higher HLA DR3-DQ2/DR4-DQ8 prevalence, lower C-peptide) were compared among four mutually exclusive groups: top 2-hour glucose quartile only [HI-2HGLU], top Index60 quartile only [HI-IND60], both top quartiles [HI-BOTH], neither top quartile [LO-BOTH]. Additionally, within the 2-hour glucose distribution of <140 mg/dL, and separately within the Index60<1.00 distribution, comparisons were made between those above or below the medians.</p> <p><u>Results</u>: HI-IND60 and HI-BOTH were younger, with greater frequency of >2 Ab+, and lower C-peptide levels than either HI-2HGLU or LO-BOTH (all p<0.001). The cumulative incidence for stage 3 was greater for HI-IND60 and HI-BOTH than either HI-2HGLU or LO-BOTH (all p<0.001). Those with Index60 values above the median were younger, had higher ≥2Ab+ (p<0.001) and DR3-DQ2/DR4-DQ8 prevalence (p<0.001), and lower AUC C-peptide levels (p<0.001) than those below. Those above the 2-hour glucose median had higher AUC C-peptide levels (p<0.001), but otherwise did not differ from those below. </p> <p><u>Conclusion</u>: Index60 identifies individuals with characteristics of type 1 diabetes at appreciable risk for progression who would otherwise be missed by 2-hour glucose staging criteria. </p>

776-P: Characteristics of Overnight Blood Glucose Levels Are Related to Sleep Quality in People with Type 1 Diabetes

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 776-P
Author(s):  
RACHEL BRANDT ◽  
MINSUN PARK ◽  
LAURIE T. QUINN ◽  
MINSEUNG CHU ◽  
YOUNGKWAN SONG ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Sleep Quality ◽  
Glucose Levels ◽  
Blood Glucose Levels

Effects of glycemic control on target organ responses to epinephrine in type 1 diabetes

2005 ◽  
Vol 289 (2) ◽  
pp. E258-E265 ◽  
Author(s):  
Deanna Aftab Guy ◽  
Darleen Sandoval ◽  
M. A. Richardson ◽  
Donna Tate ◽  
Stephen N. Davis
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Blood Pressure Response ◽  
Severe Hypoglycemia ◽  
Glucose Production ◽  
Endogenous Glucose Production ◽  
Target Organ ◽  
Epinephrine Infusion ◽  
Glucose Levels

Severe hypoglycemia occurs in intensively treated patients with type 1 diabetes mellitus (T1DM) due in part to deficient epinephrine counterregulatory responses. Previously, we have found that T1DM patients demonstrated a spectrum of altered responses to epinephrine at a variety of target organs compared with nondiabetic healthy subjects. What is not known is whether intensive glycemic control further modifies target organ responses in individuals with T1DM. Therefore, the aim of this study is to assess whether there is tissue specific (liver, muscle, adipose tissue, pancreas and cardiovascular) resistance to epinephrine in intensively controlled (IC) T1DM compared with those with conventional control (CC). Eight IC patients (age 33 ± 4 yr, BMI 24 ± 2 kg/m2, Hb A1C6.7 ± 0.1%), and 11 CC patients (age 35 ± 3 yr, BMI 25 ± 1 kg/m2, Hb A1C9.6 ± 0.1%) underwent two separate randomized, single-blind, 2-h hyperinsulinemic euglycemic clamp studies with (EPI) and without (NO EPI) epinephrine infusion. Epinephrine levels during EPI were similar in all groups (5,197 ± 344 pmol/l). Glucose (5.3 ± 0.1 mmol/l) and insulin levels (515 ± 44 pmol/l) were similar in all groups during the glucose clamps. Endogenous glucose production (EGP) and glucose uptake (Rd) were determined using [3-H3]glucose. Muscle biopsy was performed at the end of each study. IC had a significantly reduced EGP and Rdresponses to EPI compared with CC. Glucagon responses to EPI were similarly blunted in both IC and CC. Free fatty acid and glycerol response to EPI was greater in CC compared with IC. There was a significantly greater systolic blood pressure response to EPI in CC. We conclude that, despite similar epinephrine, insulin, and glucose levels, intensively treated T1DM patients had reduced cardiovascular, skeletal muscle, hepatic, and adipose target organ responses to EPI compared with conventionally treated T1DM patients.

32-LB: Interstitial Glucose Levels during Exercise in Persons with and without Type 1 Diabetes

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 32-LB
Author(s):  
MICHAEL RIDDELL ◽  
ZHAOMIAN LI ◽  
NINOSCHKA DSOUZA ◽  
CHRISTOPHER YEUNG ◽  
DURMALOUK KESIBI ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glucose Levels ◽  
Interstitial Glucose

Type I Diabetes Mellitus

2019 ◽  
Author(s):  
Joseph I. Wolfsdorf ◽  
Katharine Garvey
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Type 1 Diabetes Mellitus ◽  
Diabetic Ketoacidosis ◽  
Autoimmune Diabetes ◽  
Type I ◽  
Insulin Deficiency ◽  
Glucose Levels

Type 1 diabetes mellitus is characterized by severe insulin deficiency, making patients dependent on exogenous insulin replacement for survival. These patients can experience life-threatening events when their glucose levels are significantly abnormal. Type 1 diabetes accounts for 5 to 10% of all diabetes cases, with type 2 accounting for most of the remainder. This review details the pathophysiology, stabilization and assessment, diagnosis and treatment, disposition and outcomes of patients with Type 1 diabetes mellitus. Figures show the opposing actions of insulin and glucagon on substrate flow and plasma levels; plasma glucose, insulin and C-peptide levels throughout the day; the structure of human proinsulin; current view of the pathogenesis of Type 1 autoimmune diabetes mellitus; pathways that lead from insulin deficiency to the major clinical manifestations of Type 1 diabetes mellitus; relationship between hemoglobin A1c values at the end of a 3-month period and calculated average glucose levels during the 3-month period; different combinations of various insulin preparations used to establish glycemic control; and basal-bolus and insulin pump regimens. Tables list the etiologic classification of Type 1 diabetes mellitus, typical laboratory findings and monitoring in diabetic ketoacidosis, criteria for the diagnosis of Type 1 diabetes, clinical goals of Type 1 diabetes treatment, and insulin preparations. This review contains 10 figures, 9 tables, and 40 references. Keywords: Type 1 diabetes mellitus, optimal glycemic control, hypoglycemia, hyperglycemia, polyuria, polydipsia, polyphagia, HbA1c, medical nutrition therapy, Diabetic Ketoacidosis

T1D Hypoglycemia Prediction Algorithms: A Systematic Review (Preprint)

2021 ◽  
Author(s):  
Stella Tsichlaki ◽  
Lefteris Koumakis ◽  
Manolis Tsiknakis
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Digital Libraries ◽  
Predictive Models ◽  
Real Life ◽  
Blood Glucose Monitoring ◽  
Detection Techniques ◽  
Glucose Levels ◽  
Wide Range

BACKGROUND Diabetes is a chronic condition that necessitates regular monitoring and self-management of the patient's blood glucose levels. People with type 1 diabetes (T1D) can live a productive life if they receive proper diabetes care. Nonetheless, a loose glycemic control might increase the risk of developing hypoglycemia. This incident can occur due to a variety of causes, such as taking additional doses of insulin, skipping meals, or over-exercising. Mainly, the symptoms of hypoglycemia range from mild dysphoria to more severe conditions, if not detected in a timely manner. OBJECTIVE In this review, we report on innovative detection techniques and tactics for identifying and preventing hypoglycemic episodes, focusing on type 1 diabetes. METHODS A systematic literature search following the PRISMA guidelines was performed focusing on the “PUBMED”, “Google Scholar”, “IEEE Xplore” and “ACM” digital libraries to find articles about technologies related to hypoglycemia detection in type 1 diabetes patients. RESULTS The presented approaches have been utilized or devised to enhance blood glucose monitoring and boost its efficacy to forecast future glucose levels, which could aid the prediction of future episodes of hypoglycemia. We detected nineteen predictive models for hypoglycemia, specifically on type 1 diabetes, utilizing a wide range of algorithmic methodologies, spanning from statistics (10%) to machine learning (52%) and deep learning (38%). The algorithms employed most are the kalman filtering and classification models (SVM, KNN, random forests). The performance of the predictive models was found overall to be satisfactory, reaching accuracies between 70% and 99% which proves that such technologies are capable to facilitate the prediction of T1D hypoglycemia. CONCLUSIONS It is evident that CGM can improve the glucose control in diabetes but predictive models for hypo- and hyper- glycemia using only mainstream noninvasive sensors such as wristbands and smartwatches are foreseen to be the next step for mHealth in T1D. Prospective studies are required to demonstrate the value of such models in real-life mHealth interventions.

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