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Challenges associated with insulin therapy progression among patients with type 2 diabetes: Latin American MOSAIc study baseline data.

ABSTRACT: BACKGROUND:Poor glycemic control in patients with type 2 diabetes is commonly recorded worldwide; Latin America (LA) is not an exception. Barriers to intensifying insulin therapy and which barriers are most likely to negatively impact outcomes are not completely known. The objective was to identify barriers to insulin progression in individuals with type 2 diabetes mellitus (T2DM) in LA countries (Mexico, Brazil, and Argentina). METHODS:MOSAIc is a multinational, non-interventional, prospective, observational study aiming to identify the patient-, physician-, and healthcare-based factors affecting insulin intensification. Eligible patients were ?18 years, had T2DM, and were treated with insulin for ?3 months with/without oral antidiabetic drugs (OADs). Demographic, clinical, and psychosocial data were collected at baseline and regular intervals during the 24-month follow-up period. This paper however, focuses on baseline data analysis. The association between glycated hemoglobin (HbA1c) and selected covariates was assessed. RESULTS:A trend toward a higher level of HbA1c was observed in the LA versus non-LA population (8.40 ± 2.79 versus 8.18 ± 2.28; p ? 0.069). Significant differences were observed in clinical parameters, treatment patterns, and patient-reported outcomes in LA compared with the rest of the cohorts and between Mexico, Brazil, and Argentina. Higher number of insulin injections and lower number of OADs were used, whereas a lower level of knowledge and a higher level of diabetes-related distress were reported in LA. Covariates associated with HbA1c levels included age (-0.0129; p < 0.0001), number of OADs (0.0835; p = 0.0264), higher education level (-0.2261; p = 0.0101), healthy diet (-0.0555; p = 0.0083), self-monitoring blood glucose (-0.0512; p = 0.0033), hurried communication style in the process of care (0.1295; p = 0.0208), number of insulin injections (0.1616; p = 0.0088), adherence (-0.1939; p ? 0.0104), and not filling insulin prescription due to associated cost (0.2651; p = 0.0198). CONCLUSION:MOSAIc baseline data showed that insulin intensification in LA is not optimal and identified several conditions that significantly affect attaining appropriate HbA1c values. Tailored public health strategies, including education, should be developed to overcome such barriers. Trial Registration NCT01400971.

SUBMITTER: Linetzky B

PROVIDER: S-EPMC4957288 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Challenges associated with insulin therapy progression among patients with type 2 diabetes: Latin American MOSAIc study baseline data.

Linetzky Bruno B Curtis Brad B Frechtel Gustavo G Montenegro Renan R Escalante Pulido Miguel M Stempa Oded O de Lana Janaina Martins JM Gagliardino Juan José JJ

Diabetology & metabolic syndrome 20160722

<h4>Background</h4>Poor glycemic control in patients with type 2 diabetes is commonly recorded worldwide; Latin America (LA) is not an exception. Barriers to intensifying insulin therapy and which barriers are most likely to negatively impact outcomes are not completely known. The objective was to identify barriers to insulin progression in individuals with type 2 diabetes mellitus (T2DM) in LA countries (Mexico, Brazil, and Argentina).<h4>Methods</h4>MOSAIc is a multinational, non-interventiona ...[more]

PMID: 27453733

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Project description:OBJECTIVE:Evaluate the efficacy and safety of the dual sodium-glucose cotransporter 1 (SGLT1) and SGLT2 inhibitor sotagliflozin in combination with optimized insulin in type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS:The inTandem1 trial, a double-blind, 52-week phase 3 trial, randomized North American adults with T1D to placebo (n = 268), sotagliflozin 200 mg (n = 263), or sotagliflozin 400 mg (n = 262) after 6 weeks of insulin optimization. The primary end point was HbA1c change from baseline at 24 weeks. HbA1c, weight, and safety were also assessed through 52 weeks. RESULTS:From a mean baseline of 7.57%, placebo-adjusted HbA1c reductions were 0.36% and 0.41% with sotagliflozin 200 and 400 mg, respectively, at 24 weeks and 0.25% and 0.31% at 52 weeks (all P < 0.001). Among patients with a baseline HbA1c ?7.0%, an HbA1c <7% was achieved by 15.7%, 27.2%, and 40.3% of patients receiving placebo, sotagliflozin 200 mg, and sotagliflozin 400 mg, respectively (P ? 0.003 vs. placebo) at 24 weeks. At 52 weeks, mean treatment differences between sotagliflozin 400 mg and placebo were -1.08 mmol/L for fasting plasma glucose, -4.32 kg for weight, and -15.63% for bolus insulin dose and -11.87% for basal insulin dose (all P < 0.001). Diabetes Treatment Satisfaction Questionnaire scores increased significantly by 2.5 points with sotagliflozin versus placebo (P < 0.001) at 24 weeks. Genital mycotic infections and diarrhea occurred more frequently with sotagliflozin. Adjudicated diabetic ketoacidosis (DKA) occurred in 9 (3.4%) and 11 (4.2%) patients receiving sotagliflozin 200 and 400 mg, respectively, and in 1 (0.4%) receiving placebo. Severe hypoglycemia occurred in 17 (6.5%) patients from each sotagliflozin group and 26 (9.7%) patients receiving placebo. CONCLUSIONS:In a 1-year T1D study, sotagliflozin combined with optimized insulin therapy was associated with sustained HbA1c reduction, weight loss, lower insulin dose, fewer episodes of severe hypoglycemia, improved patient-reported outcomes, and more DKA relative to placebo (ClinicalTrials.gov, NCT02384941).

Project description:BackgroundNovel influenza surveillance systems that leverage Internet-based real-time data sources including Internet search frequencies, social-network information, and crowd-sourced flu surveillance tools have shown improved accuracy over the past few years in data-rich countries like the United States. These systems not only track flu activity accurately, but they also report flu estimates a week or more ahead of the publication of reports produced by healthcare-based systems, such as those implemented and managed by the Centers for Disease Control and Prevention. Previous work has shown that the predictive capabilities of novel flu surveillance systems, like Google Flu Trends (GFT), in developing countries in Latin America have not yet delivered acceptable flu estimates.ObjectiveThe aim of this study was to show that recent methodological improvements on the use of Internet search engine information to track diseases can lead to improved retrospective flu estimates in multiple countries in Latin America.MethodsA machine learning-based methodology that uses flu-related Internet search activity and historical information to monitor flu activity, named ARGO (AutoRegression with Google search), was extended to generate flu predictions for 8 Latin American countries (Argentina, Bolivia, Brazil, Chile, Mexico, Paraguay, Peru, and Uruguay) for the time period: January 2012 to December of 2016. These retrospective (out-of-sample) Influenza activity predictions were compared with historically observed flu suspected cases in each country, as reported by Flunet, an influenza surveillance database maintained by the World Health Organization. For a baseline comparison, retrospective (out-of-sample) flu estimates were produced for the same time period using autoregressive models that only leverage historical flu activity information.ResultsOur results show that ARGO-like models' predictive power outperform autoregressive models in 6 out of 8 countries in the 2012-2016 time period. Moreover, ARGO significantly improves on historical flu estimates produced by the now discontinued GFT for the time period of 2012-2015, where GFT information is publicly available.ConclusionsWe demonstrate here that a self-correcting machine learning method, leveraging Internet-based disease-related search activity and historical flu trends, has the potential to produce reliable and timely flu estimates in multiple Latin American countries. This methodology may prove helpful to local public health officials who design and implement interventions aimed at mitigating the effects of influenza outbreaks. Our methodology generally outperforms both the now-discontinued tool GFT, and autoregressive methodologies that exploit only historical flu activity to produce future disease estimates.

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Challenges associated with insulin therapy progression among patients with type 2 diabetes: Latin American MOSAIc study baseline data.

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Challenges associated with insulin therapy progression among patients with type 2 diabetes: Latin American MOSAIc study baseline data.

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