Irl B. Hirsch

Continuous glucose monitoring and intensive treatment of type 1 diabetes

BACKGROUND The value of continuous glucose monitoring in the management of type 1 diabetes mellitus has not been determined. METHODS In a multicenter clinical trial, we randomly assigned 322 adults and children who were already receiving intensive therapy for type 1 diabetes to a group with continuous glucose monitoring or to a control group performing home monitoring with a blood glucose meter. All the patients were stratified into three groups according to age and had a glycated hemoglobin level of 7.0 to 10.0%. The primary outcome was the change in the glycated hemoglobin level at 26 weeks. RESULTS The changes in glycated hemoglobin levels in the two study groups varied markedly according to age group (P=0.003), with a significant difference among patients 25 years of age or older that favored the continuous-monitoring group (mean difference in change, -0.53%; 95% confidence interval [CI], -0.71 to -0.35; P<0.001). The between-group difference was not significant among those who were 15 to 24 years of age (mean difference, 0.08; 95% CI, -0.17 to 0.33; P=0.52) or among those who were 8 to 14 years of age (mean difference, -0.13; 95% CI, -0.38 to 0.11; P=0.29). Secondary glycated hemoglobin outcomes were better in the continuous-monitoring group than in the control group among the oldest and youngest patients but not among those who were 15 to 24 years of age. The use of continuous glucose monitoring averaged 6.0 or more days per week for 83% of patients 25 years of age or older, 30% of those 15 to 24 years of age, and 50% of those 8 to 14 years of age. The rate of severe hypoglycemia was low and did not differ between the two study groups; however, the trial was not powered to detect such a difference. CONCLUSIONS Continuous glucose monitoring can be associated with improved glycemic control in adults with type 1 diabetes. Further work is needed to identify barriers to effectiveness of continuous monitoring in children and adolescents. (ClinicalTrials.gov number, NCT00406133.)

Role of Orlistat in the Treatment of Obese Patients With Type 2 Diabetes: A 1-year randomized double-blind study

OBJECTIVE Obesity is an important risk factor for type 2 diabetes. Weight loss in patients with type 2 diabetes is associated with improved glycemic control and reduced cardiovascular disease risk factors, but weight loss is notably difficult to achieve and sustain with caloric restriction and exercise. The purpose of this study was to assess the impact of treatment with orlistat, a pancreatic lipase inhibitor, on weight loss, glycemic control, and serum lipid levels in obese patients with type 2 diabetes on sulfonylurea medications. RESEARCH DESIGN AND METHODS In a multicenter 57-week randomized double-blind placebo-controlled study, 120 mg orlistat or placebo was administered orally three times a day with a mildly hypocaloric diet to 391 obese men and women with type 2 diabetes who were aged > 18 years, had a BMI of 28–40 kg/m2, and were clinically stable on oral sulfonylureas. Changes in body weight, glycemic control, lipid levels, and drug tolerability were measured. RESULTS After 1 year of treatment, the orlistat group lost 6.2 ± 0.45% (mean ± SEM) of initial body weight vs. 4.3 ± 0.49% in the placebo group (P < 0.001). Twice as many patients receiving orlistat (49 vs. 23%) lost ≥ 5% of initial body weight (P < 0.001). Orlistat treatment plus diet compared with placebo plus diet was associated with significant improvement in glycemic control, as reflected in decreases in HbA1c (P < 0.001) and fasting plasma glucose (P < 0.001) and in dosage reductions of oral sulfonylurea medication (P < 0.01). Orlistat therapy also resulted in significantly greater improvements than placebo in several lipid parameters, namely, greater reductions in total cholesterol, (P < 0.001), LDL cholesterol (P < 0.001), triglycerides (P < 0.05), apolipoprotein B (P < 0.001), and the LDL-to-HDL cholesterol ratio (P < 0.001). Mild to moderate and transient gastrointestinal events were reported with orlistat therapy, although their association with study withdrawal was low. Fat-soluble vitamin levels generally remained within the reference range, and vitamin supplementation was required in only a few patients. CONCLUSIONS Orlistat is an effective treatment modality in obese patients with type 2 diabetes with respect to clinically meaningful weight loss and maintenance of weight loss, improved glycemic control, and improved lipid profile.

CONSENSUS STATEMENT BY THE AMERICAN ASSOCIATION OF CLINICAL ENDOCRINOLOGISTS AND AMERICAN COLLEGE OF ENDOCRINOLOGY ON THE COMPREHENSIVE TYPE 2 DIABETES MANAGEMENT ALGORITHM--2016 EXECUTIVE SUMMARY.

Abbreviations: A1C = hemoglobin A1C AACE = American Association of Clinical Endocrinologists ACCORD = Action to Control Cardiovascular Risk in Diabetes ACCORD BP = Action to Control Cardiovascular Risk in Diabetes Blood Pressure ACEI = angiotensinconverting enzyme inhibitor AGI = alpha-glucosidase inhibitor apo B = apolipoprotein B ARB = angiotensin II receptor blocker ASCVD = atherosclerotic cardiovascular disease BAS = bile acid sequestrant BMI = body mass index BP = blood pressure CHD = coronary heart disease CKD = chronic kidney disease CVD = cardiovascular disease DKA = diabetic ketoacidosis DPP-4 = dipeptidyl peptidase 4 EPA = eicosapentaenoic acid FDA = Food and Drug Administration GLP-1 = glucagon-like peptide 1 HDL-C = high-density-lipoprotein cholesterol LDL-C = low-densitylipoprotein cholesterol LDL-P = low-density-lipoprotein particle Look AHEAD = Look Action for Health in Diabetes NPH = neutral protamine Hagedorn OSA = obstructive sleep apnea SFU = sulfonylurea SGLT-2 = sodium glucose cotrans...

The relationship of depressive symptoms to symptom reporting, self-care and glucose control in diabetes.

Depressive symptoms are common among patients with diabetes and may have a significant impact on self-management and health outcomes. In this study we predicted that: 1) there would be a significant association between depressive symptoms and diabetes symptom burden, physical functioning, diabetes self-care, and HbA1c levels; and, 2) that the association between depressive symptoms and HbA1c levels would be significantly greater in type 1, as compared to type 2 diabetic patients. This cross-sectional observational study of 276 type 1 and 199 type 2 diabetes patients took place in a tertiary care specialty clinic. We collected self-reported data on depressive symptoms, complications, medical comorbidity, diabetes symptoms, diabetes self-care behaviors, physical functioning, and demographics. From automated data we determined mean HbA1c levels over the prior year. We performed linear regression analyses to assess the association between depressive symptoms and diabetes symptom perception, diabetes self-care behaviors, physical functioning, and glycemic control. Among patients with type 1 and 2 diabetes, depressive symptoms were associated with greater diabetes symptom reporting, poorer physical functioning, and less adherence to exercise regimens and diet. There was a significant association between depressive symptoms and HbA1c levels in type 1, but not type 2 diabetic patients. Because of their association with clinical aspects of diabetes care such as diabetes symptom reporting and adherence to diabetes self-care, depressive symptoms are important to recognize in treating patients with diabetes.

A path model of chronic stress, the metabolic syndrome, and coronary heart disease.

Objective We tested a theoretical stress model cross-sectionally and prospectively that examined whether relationships of chronic stress, psychophysiology, and coronary heart disease (CHD) varied in older adult men (N = 47), older adult women not using hormone replacement therapy (HRT) (N = 64), and older adult women using HRT (N = 41). Method Structural equations examined relationships of CHD with 1) chronic stress (caring for a spouse with Alzheimer’s disease and patient functioning), 2) vulnerability (anger and hostility), 3) social resources (supports), 4) psychological distress (burden, sleep problems, and low uplifts), 5) poor health habits (high-caloric, high-fat diet and limited exercise), and 6) the metabolic syndrome (MS) (blood pressure, obesity, insulin, glucose, and lipids). Results Caregiver men had a greater prevalence of CHD (13/24) than did noncaregiver men (6/23) (p < .05) 27 to 30 months after study entry. This was influenced by pathways from caregiving to distress, distress to the MS, and the MS to CHD. In men, poor health habits predicted the MS 15 to 18 months later, and the MS predicted new CHD cases over 27 to 30 months. In women, no “caregiving-CHD” relationship occurred; however, 15 to 18 months after study entry women not using HRT showed “distress-MS” and “MS-CHD” relationships. In women using HRT, associations did not occur among distress, the MS, and CHD, but poor health habits and the MS were related. Conclusions In older men, pathways occurred from chronic stress to distress to the metabolic syndrome, which in turn predicted CHD. Older women not using HRT showed fewer pathways than men; however, over time, distress, the MS, and CHD were related. No psychophysiological pathways occurred in older women using HRT.

American Association of Clinical Endocrinologists and American Diabetes Association consensus statement on inpatient glycemic control.

This report is being published concurrently in 2009 in Endocrine Practice and Diabetes Care by the American Association of Clinical Endocrinologists and the American Diabetes Association. From the 1Department of Medicine, University of California Los Angeles, Los Angeles, California, 2Department of Medicine, Division of Endocrinology and Metabolism, University of Pittsburgh, Pittsburgh, Pennsylvania, 3Division of Endocrinology and Metabolism, Veterans Affairs Pittsburgh Health Center and University of Pittsburgh School of Nursing PhD Program, Pittsburgh, Pennsylvania, 4Scripps Whittier Diabetes Institute, La Jolla, California, University of California San Diego School of Medicine, San Diego, California, and Diabetes and Endocrine Associates, La Jolla, California, 5Department of Medicine, University of Missouri-Kansas City School of Medicine and Hellman and Rosen Endocrine Associates, North Kansas City, Missouri, 6Department of Medicine, University of Washington School of Medicine, Seattle, Washington, 7Department of Medicine, Section of Endocrinology, Yale University School of Medicine and the Yale Diabetes Center, Yale-New Haven Hospital, New Haven, Connecticut, 8Department of Medicine, Physiology and Biophysics, Division of Clinical and Molecular Endocrinology, Case Western Reserve University, Cleveland, Ohio, 9Clinical Affairs, American Diabetes Association, Alexandria, Virginia, and 10Department of Medicine/Endocrinology, Emory University, Atlanta, Georgia. Address correspondence and reprint requests to Dr. Etie S. Moghissi, 4644 Lincoln Boulevard, Suite 409, Marina del Rey, CA 90292.

Individualizing Glycemic Targets in Type 2 Diabetes Mellitus: Implications of Recent Clinical Trials

One of the first steps in the management of patients with type 2 diabetes mellitus is setting glycemic goals. Professional organizations advise setting specific hemoglobin A(1c) (HbA(1c)) targets for patients, and individualization of these goals has more recently been emphasized. However, the operational meaning of glycemic goals, and specific methods for individualizing them, have not been well-described. Choosing a specific HbA(1c) target range for a given patient requires taking several factors into consideration, including an assessment of the patients risk for hyperglycemia-related complications versus the risks of therapy, all in the context of the overall clinical setting. Comorbid conditions, psychological status, capacity for self-care, economic considerations, and family and social support systems also play a key role in the intensity of therapy. The individualization of HbA(1c) targets has gained more traction after recent clinical trials in older patients with established type 2 diabetes mellitus failed to show a benefit from intensive glucose-lowering therapy on cardiovascular disease (CVD) outcomes. The limited available evidence suggests that near-normal glycemic targets should be the standard for younger patients with relatively recent onset of type 2 diabetes mellitus and little or no micro- or macrovascular complications, with the aim of preventing complications over the many years of life. However, somewhat higher targets should be considered for older patients with long-standing type 2 diabetes mellitus and evidence of CVD (or multiple CVD risk factors). This review explores these issues further and proposes a framework for considering an appropriate and safe HbA(1c) target range for each patient.

Kidney Disease and Increased Mortality Risk in Type 2 Diabetes

Type 2 diabetes associates with increased risk of mortality, but how kidney disease contributes to this mortality risk among individuals with type 2 diabetes is not completely understood. Here, we examined 10-year cumulative mortality by diabetes and kidney disease status for 15,046 participants in the Third National Health and Nutrition Examination Survey (NHANES III) by linking baseline data from NHANES III with the National Death Index. Kidney disease, defined as urinary albumin/creatinine ratio ≥30 mg/g and/or estimated GFR ≤60 ml/min per 1.73 m(2), was present in 9.4% and 42.3% of individuals without and with type 2 diabetes, respectively. Among people without diabetes or kidney disease (reference group), 10-year cumulative all-cause mortality was 7.7% (95% confidence interval [95% CI], 7.0%-8.3%), standardized to population age, sex, and race. Among individuals with diabetes but without kidney disease, standardized mortality was 11.5% (95% CI, 7.9%-15.2%), representing an absolute risk difference with the reference group of 3.9% (95% CI, 0.1%-7.7%), adjusted for demographics, and 3.4% (95% CI, -0.3% to 7.0%) when further adjusted for smoking, BP, and cholesterol. Among individuals with both diabetes and kidney disease, standardized mortality was 31.1% (95% CI, 24.7%-37.5%), representing an absolute risk difference with the reference group of 23.4% (95% CI, 17.0%-29.9%), adjusted for demographics, and 23.4% (95% CI, 17.2%-29.6%) when further adjusted. We observed similar patterns for cardiovascular and noncardiovascular mortality. In conclusion, those with kidney disease predominantly account for the increased mortality observed in type 2 diabetes.

The effect of continuous glucose monitoring in well-controlled type 1 diabetes.

OBJECTIVE The potential benefits of continuous glucose monitoring (CGM) in the management of adults and children with well-controlled type 1 diabetes have not been examined. RESEARCH DESIGN AND METHODS A total of 129 adults and children with intensively treated type 1 diabetes (age range 8–69 years) and A1C <7.0% were randomly assigned to either continuous or standard glucose monitoring for 26 weeks. The main study outcomes were time with glucose level ≤70 mg/dl, A1C level, and severe hypoglycemic events. RESULTS At 26 weeks, biochemical hypoglycemia (≤70 mg/dl) was less frequent in the CGM group than in the control group (median 54 vs. 91 min/day), but the difference was not statistically significant (P = 0.16). Median time with a glucose level ≤60 mg/dl was 18 versus 35 min/day, respectively (P = 0.05). Time out of range (≤70 or >180 mg/dl) was significantly lower in the CGM group than in the control group (377 vs. 491 min/day, P = 0.003). There was a significant treatment group difference favoring the CGM group in mean A1C at 26 weeks adjusted for baseline (P < 0.001). One or more severe hypoglycemic events occurred in 10 and 11% of the two groups, respectively (P = 1.0). Four outcome measures combining A1C and hypoglycemia data favored the CGM group in comparison with the control group (P < 0.001, 0.007, 0.005, and 0.003). CONCLUSIONS Most outcomes, including those combining A1C and hypoglycemia, favored the CGM group. The weight of evidence suggests that CGM is beneficial for individuals with type 1 diabetes who have already achieved excellent control with A1C <7.0%.

Euglycemic Diabetic Ketoacidosis: A Potential Complication of Treatment With Sodium–Glucose Cotransporter 2 Inhibition

OBJECTIVE Sodium–glucose cotransporter 2 (SGLT-2) inhibitors are the most recently approved antihyperglycemic medications. We sought to describe their association with euglycemic diabetic ketoacidosis (euDKA) in hopes that it will enhance recognition of this potentially life-threatening complication. RESEARCH DESIGN AND METHODS Cases identified incidentally are described. RESULTS We identified 13 episodes of SGLT-2 inhibitor–associated euDKA or ketosis in nine individuals, seven with type 1 diabetes and two with type 2 diabetes, from various practices across the U.S. The absence of significant hyperglycemia in these patients delayed recognition of the emergent nature of the problem by patients and providers. CONCLUSIONS SGLT-2 inhibitors seem to be associated with euglycemic DKA and ketosis, perhaps as a consequence of their noninsulin-dependent glucose clearance, hyperglucagonemia, and volume depletion. Patients with type 1 or type 2 diabetes who experience nausea, vomiting, or malaise or develop a metabolic acidosis in the setting of SGLT-2 inhibitor therapy should be promptly evaluated for the presence of urine and/or serum ketones. SGLT-2 inhibitors should only be used with great caution, extensive counseling, and close monitoring in the setting of type 1 diabetes.