Impact of the COVID-19 Pandemic on the Effectiveness of a Metabolic Health Telemedicine Intervention for Weight Loss: A Propensity Score Matching Analysis.

Background: Coronavirus disease 2019 (COVID-19) pandemic public health measures such as stay-at-home and mandatory work-from-home orders have been associated with obesogenic lifestyle changes, increased risk of weight gain, and their metabolic sequelae. We sought to assess the impact of this pandemic on weight loss from a telemedicine-delivered very-low-carbohydrate intervention targeting nutritional ketosis (NKI). Methods: A total of 746 patients with a BMI ≥25kg/m2, enrolled between January and March 2020 and treated for at least 1 year with the NKI, were classified as pandemic cohort (PC). A separate cohort of 699 patients who received 1 year of the NKI in the preceding years, enrolled between January and March 2018, were identified as pre-pandemic cohort (Pre-PC). Demographic and clinical data were obtained from medical records to compare the cohorts and assess the outcomes. Using propensity score matching (PSM), balanced and matched groups of 407 patients in the Pre-PC and 407 patients in the PC were generated. Longitudinal change in absolute weight and percentage weight change from baseline to 1 year were assessed. Results: Weight significantly decreased in both PC and Pre-PC at 3, 6, 9, and 12 months. The weight loss trajectory was similar in both PC and Pre-PC with no significant weight differences between the two cohorts at 3, 6, 9, and 12 months. On an average, the PC lost 7.5% body weight while the Pre-PC lost 7.9% over 1 year, and the percent weight loss did not differ between the two cohorts (p = 0.50). Conclusion: A very-low-carbohydrate telemedicine intervention delivered comparable and medically significant weight loss independent of pandemic stress and lifestyle limitations.

Redefining Hypoglycemia in Clinical Trials: Validation of Definitions Recently Adopted by the American Diabetes Association/European Association for the Study of Diabetes.

OBJECTIVE: To determine if the International Hypoglycaemia Study Group (IHSG) level 2 low glucose definition can identify clinically relevant hypoglycemia in clinical trials and offer value as an end point for future trials. RESEARCH DESIGN AND METHODS: A post hoc analysis was performed of the SWITCH (SWITCH 1: n = 501, type 1 diabetes; SWITCH 2: n = 721, type 2 diabetes) and DEVOTE (n = 7,637, type 2 diabetes) trials utilizing the IHSG low glucose definitions. Patients in all trials were randomized to either insulin degludec or insulin glargine 100 units/mL. In the main analysis, the following definitions were compared: 1) American Diabetes Association (ADA) 2005 (plasma glucose [PG] confirmed ≤3.9 mmol/L with symptoms); and 2) IHSG level 2 (PG confirmed <3.0 mmol/L, independent of symptoms). RESULTS: In SWITCH 2, the estimated rate ratios of hypoglycemic events indicated increasing differences between treatments with decreasing PG levels until 3.0 mmol/L, following which no additional treatment differences were observed. Similar results were observed for the SWITCH 1 trial. In SWITCH 2, the IHSG level 2 definition produced a rate ratio that was lower than the ADA 2005 definition. CONCLUSIONS: The IHSG level 2 definition was validated in a series of clinical trials, demonstrating its ability to discriminate between basal insulins. This definition is therefore recommended to be uniformly adopted by regulatory bodies and used in future clinical trials.

Metformin and Type 2 Diabetes Prevention.

IN BRIEF Metformin, an established therapy for the treatment of type 2 diabetes, has demonstrated safety and effectiveness in the prevention or delay of type 2 diabetes in people at high risk. The Diabetes Prevention Program randomized clinical trial demonstrated that intensive lifestyle intervention and metformin therapy reduced progression to diabetes by 58 and 31%, respectively, compared to placebo in people at risk of type 2 diabetes. Although lifestyle intervention was beneficial in all groups, metformin had a selectively greater effect in those who were more obese, had a higher fasting glucose, had a history of gestational diabetes, or were younger. Long-term effects included an 18% diabetes reduction with metformin compared to placebo over 15 years, a reduction in microvascular complications among those who did not progress to diabetes (without difference among treatment arms), and suggestion by coronary calcium assessment of a possible impact on atherosclerosis in men. Although long-term follow-up to assess later-stage outcomes is underway, current efforts to address gaps in evidence and translation remain of significant public health interest.

Hypoglycemia: New Definitions and Regulatory Implications.

Hypoglycemia is the limiting factor in controlling glucose levels in Diabetes. Rather than being a side effect, hypoglycemia is the mechanism of action for insulin therapy, with a very narrow therapeutic window. Until recently, regulatory bodies listed hypoglycemia only as an adverse effect of therapy; however, one insulin preparation is now recognized and labelled as reducing the risk of severe hypoglycemia. This paper describes internationally agreed upon definitions for hypoglycemia and proposed regulatory approaches for recognition and labeling of diabetes therapies to facilitate personalized care.

Statin use and risk of developing diabetes: results from the Diabetes Prevention Program.

OBJECTIVE: Several clinical trials of cardiovascular disease prevention with statins have reported increased risk of type 2 diabetes (T2DM) with statin therapy. However, participants in these studies were at relatively low risk for diabetes. Further, diabetes was often based on self-report and was not the primary outcome. It is unknown whether statins similarly modify diabetes risk in higher risk populations. RESEARCH DESIGN AND METHODS: During the Diabetes Prevention Program Outcomes Study (n=3234), the long-term follow-up to a randomized clinical trial of interventions to prevent T2DM, incident diabetes was assessed by annual 75 g oral glucose tolerance testing and semiannual fasting glucose. Lipid profile was measured annually, with statin treatment determined by a participant's own physician outside of the protocol. Statin use was assessed at baseline and semiannual visits. RESULTS: At 10 years, the cumulative incidence of statin initiation prior to diabetes diagnosis was 33%-37% among the randomized treatment groups (p=0.36). Statin use was associated with greater diabetes risk irrespective of treatment group, with pooled HR (95% CI) for incident diabetes of 1.36 (1.17 to 1.58). This risk was not materially altered by adjustment for baseline diabetes risk factors and potential confounders related to indications for statin therapy. CONCLUSIONS: In this population at high risk for diabetes, we observed significantly higher rates of diabetes with statin therapy in all three treatment groups. Confounding by indication for statin use does not appear to explain this relationship. The effect of statins to increase diabetes risk appears to extend to populations at high risk for diabetes. TRIAL REGISTRATION NUMBER: NCT00038727; Results.

Differentiation of Diabetes by Pathophysiology, Natural History, and Prognosis.

The American Diabetes Association, JDRF, the European Association for the Study of Diabetes, and the American Association of Clinical Endocrinologists convened a research symposium, "The Differentiation of Diabetes by Pathophysiology, Natural History and Prognosis" on 10-12 October 2015. International experts in genetics, immunology, metabolism, endocrinology, and systems biology discussed genetic and environmental determinants of type 1 and type 2 diabetes risk and progression, as well as complications. The participants debated how to determine appropriate therapeutic approaches based on disease pathophysiology and stage and defined remaining research gaps hindering a personalized medical approach for diabetes to drive the field to address these gaps. The authors recommend a structure for data stratification to define the phenotypes and genotypes of subtypes of diabetes that will facilitate individualized treatment.

Diabetes Incidence and Glucose Tolerance after Termination of Pioglitazone Therapy: Results from ACT NOW.

CONTEXT: Thiazolidinediones have proven efficacy in preventing diabetes in high-risk individuals. However, the effect of thiazolidinediones on glucose tolerance after cessation of therapy is unclear. OBJECTIVE: To examine the effect of pioglitazone (PIO) on incidence of diabetes after discontinuing therapy in ACT NOW. Design, Settings and Patients: Two-hundred ninety-three subjects (placebo [PLAC], n = 138; PIO, n = 152) completed a median followup of 11.7 mo after study medication was stopped. RESULTS: Diabetes developed in 138 (12.3%) of PLAC vs 17 of 152 PIO patients (11.2%; P = not significant, PIO vs PLAC). However, the cumulative incidence of diabetes from start of study medication to end of washout period remained significantly lower in PIO vs PLAC (10.7 vs 22.3%; P < .005). After therapy was discontinued, 23.0% (35/152) of PIO-treated patients remained normal-glucose tolerant (NGT) vs 13.8% (19/138) of PLAC-treated patients (P = .04). Insulin secretion/insulin resistance index (I0-120/G0-120 × Matsuda index) was markedly lower in subjects with impaired glucose tolerance (IGT) who converted to diabetes during followup vs those who remained IGT or NGT. The decline in-cell function (insulin secretion/insulin resistance index) was similar in subjects with IGT who developed diabetes, irrespective of whether they were treated with PIO or PLAC. CONCLUSIONS: 1) The protective effect of PIO on incidence of diabetes attenuates after discontinuation of therapy, 2) cumulative incidence of diabetes in individuals exposed to PIO remained significantly (56%) lower than PLAC and a greater number of PIO-treated individuals maintained NGT after median followup of 11.4 mo, and 3) low insulin secretion/insulin resistance index is a strong predictor of future diabetes following PIO discontinuation.

American Diabetes Association and JDRF Research Symposium: Diabetes and the Microbiome.

From 27-29 October 2014, more than 100 people gathered in Chicago, IL, to participate in a research symposium titled "Diabetes and the Microbiome," jointly sponsored by the American Diabetes Association and JDRF. The conference brought together international scholars and trainees from multiple disciplines, including microbiology, bioinformatics, endocrinology, metabolism, and immunology, to share the current understanding of host-microbe interactions and their influences on diabetes and metabolism. Notably, this gathering was the first to assemble specialists with distinct expertise in type 1 diabetes, type 2 diabetes, immunology, and microbiology with the goal of discussing and defining potential pathophysiologies linking the microbiome and diabetes. In addition to reviewing existing evidence in the field, speakers presented their own original research to provide a comprehensive view of the current understanding of the topics under discussion.Presentations and discussions throughout the conference reflected a number of important concepts. The microbiota in any host represent a complex ecosystem with a high degree of interindividual variability. Different microbial communities, comprising bacteria, archaea, viruses, and fungi, occupy separate niches in and on the human body. Individually and collectively, these microbes provide benefits to the host-including nutrient harvest from food and protection against pathogens. They are dynamically regulated by both host genes and the environment, and they critically influence both physiology and lifelong health. The objective of the symposium was to discuss the relationship between the host and the microbiome-the combination of microbiota and their biomolecular environment and ecology-specifically with regard to metabolic and immunological systems and to define the critical research needed to understand and potentially target the microbiome in the prevention and treatment of diabetes. In this report, we present meeting highlights in the following areas: 1) relationships between diabetes and the microbiome, 2) bioinformatic tools, resources, and study design considerations, 3) microbial programming of the immune system, 4) the microbiome and energy balance, 5) interventions, and 6) limitations, unanswered questions, and resource and policy needs.

Staging presymptomatic type 1 diabetes: a scientific statement of JDRF, the Endocrine Society, and the American Diabetes Association.

Insights from prospective, longitudinal studies of individuals at risk for developing type 1 diabetes have demonstrated that the disease is a continuum that progresses sequentially at variable but predictable rates through distinct identifiable stages prior to the onset of symptoms. Stage 1 is defined as the presence of ß-cell autoimmunity as evidenced by the presence of two or more islet autoantibodies with normoglycemia and is presymptomatic, stage 2 as the presence of ß-cell autoimmunity with dysglycemia and is presymptomatic, and stage 3 as onset of symptomatic disease. Adoption of this staging classification provides a standardized taxonomy for type 1 diabetes and will aid the development of therapies and the design of clinical trials to prevent symptomatic disease, promote precision medicine, and provide a framework for an optimized benefit/risk ratio that will impact regulatory approval, reimbursement, and adoption of interventions in the early stages of type 1 diabetes to prevent symptomatic disease.

The CardioMetabolic Health Alliance: Working Toward a New Care Model for the Metabolic Syndrome.

The Cardiometabolic Think Tank was convened on June 20, 2014, in Washington, DC, as a "call to action" activity focused on defining new patient care models and approaches to address contemporary issues of cardiometabolic risk and disease. Individual experts representing >20 professional organizations participated in this roundtable discussion. The Think Tank consensus was that the metabolic syndrome (MetS) is a complex pathophysiological state comprised of a cluster of clinically measured and typically unmeasured risk factors, is progressive in its course, and is associated with serious and extensive comorbidity, but tends to be clinically under-recognized. The ideal patient care model for MetS must accurately identify those at risk before MetS develops and must recognize subtypes and stages of MetS to more effectively direct prevention and therapies. This new MetS care model introduces both affirmed and emerging concepts that will require consensus development, validation, and optimization in the future.

A novel insulin resistance index to monitor changes in insulin sensitivity and glucose tolerance: the ACT NOW study.

OBJECTIVE: The objective was to test the clinical utility of Quantose M(Q) to monitor changes in insulin sensitivity after pioglitazone therapy in prediabetic subjects. Quantose M(Q) is derived from fasting measurements of insulin, α-hydroxybutyrate, linoleoyl-glycerophosphocholine, and oleate, three nonglucose metabolites shown to correlate with insulin-stimulated glucose disposal. RESEARCH DESIGN AND METHODS: Participants were 428 of the total of 602 ACT NOW impaired glucose tolerance (IGT) subjects randomized to pioglitazone (45 mg/d) or placebo and followed for 2.4 years. At baseline and study end, fasting plasma metabolites required for determination of Quantose, glycated hemoglobin, and oral glucose tolerance test with frequent plasma insulin and glucose measurements to calculate the Matsuda index of insulin sensitivity were obtained. RESULTS: Pioglitazone treatment lowered IGT conversion to diabetes (hazard ratio = 0.25; 95% confidence interval = 0.13-0.50; P < .0001). Although glycated hemoglobin did not track with insulin sensitivity, Quantose M(Q) increased in pioglitazone-treated subjects (by 1.45 [3.45] mg·min(-1)·kgwbm(-1)) (median [interquartile range]) (P < .001 vs placebo), as did the Matsuda index (by 3.05 [4.77] units; P < .0001). Quantose M(Q) correlated with the Matsuda index at baseline and change in the Matsuda index from baseline (rho, 0.85 and 0.79, respectively; P < .0001) and was progressively higher across closeout glucose tolerance status (diabetes, IGT, normal glucose tolerance). In logistic models including only anthropometric and fasting measurements, Quantose M(Q) outperformed both Matsuda and fasting insulin in predicting incident diabetes. CONCLUSIONS: In IGT subjects, Quantose M(Q) parallels changes in insulin sensitivity and glucose tolerance with pioglitazone therapy. Due to its strong correlation with improved insulin sensitivity and its ease of use, Quantose M(Q) may serve as a useful clinical test to identify and monitor therapy in insulin-resistant patients.

Association of modifiable risk factors and left ventricular ejection fraction among hospitalized Native Hawaiians and Pacific Islanders with heart failure.

BACKGROUND: Heart failure (HF) disproportionately affects Native Hawaiians and Other Pacific Islanders (NHOPIs). This study examines risk factors associated with left ventricular ejection fraction (LVEF) among 151 hospitalized NHOPI HF patients enrolled at a single tertiary care hospital between June 2006 and April 2010. METHODS: Enrollment criteria: (1) NHOPI by self-identification. (2) Age ≥ 21 yrs. (3) Diagnosis of HF defined: (a) left ventricular ejection fraction (LVEF) ≤ 40% or LVEF ≤ 60% with abnormal diastolic function and (b) classic HF signs/symptoms. LVEF was measured by echocardiography within 6 weeks of hospitalization. Clinical measures, medical history, and questionnaires were assessed using standardized protocols. Linear regression modeling was used to examine the association of significant correlates of LVEF, which were then included en bloc into the final model. A P-value < .05 was considered statistically significant. RESULTS: Of 151 participants, 69% were men, mean age 54.3 ± 13.5 years, blood pressure 112 ± 20/69 ± 15 mmHg, and body mass index (BMI) 36.9 ± 9 kg/m(2). Twenty-five percent of participants were smokers, 45% used alcohol and 23% reported a history of methamphetamine use. Clinically, 72% had hypertension, 49% were diabetic and 37% had a prior myocardial infarction. Nearly 60% had moderate to severe LVEF (< 35%). Higher LVEF was independently associated with female sex and greater BMI (P < .04) while pacemaker/defibrillator and methamphetamine use was independently associated with lower LVEF (P < .05). CONCLUSIONS: Methamphetamine use and BMI may be important modifiable risk factors associated with LVEF and may be important targets for improving HF morbidity and mortality.