Development of a Patient-Reported Outcome (PRO) Measure to Assess Emotional Impact of Treatment for Type 2 Diabetes
ConclusionThe EIDTQ-Status and Comparison measures can be used as a supplement to clinical outcomes, such as hemoglobin A1c (HbA1c) and body weight, to provide a broader picture of the patient ’s emotional experience with medication treatment for T2D. (Source: Diabetes Therapy)
Source: Diabetes Therapy - June 23, 2023 Category: Endocrinology Source Type: research
Perceived Future Outcomes of Unsuccessful Treatment and Their Association with Treatment Persistence Among Type-2 Diabetes Patients: A Cross-Sectional Content Analysis
ConclusionPersistent treatment was prevalent among patients with T2DM who mentioned the code “treatment”, suggesting that these patients may anticipate a threat due to the invasiveness of diabetes and thus participate in persistent treatment to avoid this threat. Healthcare professionals should provide appropriate information and supportive conditions to achieve both a reduced feeling o f threat and persistent treatment engagement. (Source: Diabetes Therapy)
Source: Diabetes Therapy - June 20, 2023 Category: Endocrinology Source Type: research
Healthcare Professionals ’ Knowledge of and Attitudes Towards the Use of Time in Range in Diabetes Management: Online Survey Across Seven Countries
ConclusionsOverall, HCPs agreed on the benefits of using TIR for diabetes management. Besides raising awareness among HCPs and people with diabetes, more training and healthcare system updates are needed to facilitate increased TIR use. In addition, integration into clinical guidelines and recognition by regulators and payers are needed. (Source: Diabetes Therapy)
Source: Diabetes Therapy - June 18, 2023 Category: Endocrinology Source Type: research
Pharmacokinetics and Safety of iGlarLixi in Healthy Chinese Participants: Results of a Phase 1 Randomized Study
ConclusioniGlarLixi administration resulted in early absorption of both iGlar and lixisenatide with a good tolerability profile in healthy Chinese participants. These results are consistent with the previously published data from other geographic regions.Trial registrationU1111-1194-9411. (Source: Diabetes Therapy)
Source: Diabetes Therapy - June 17, 2023 Category: Endocrinology Source Type: research
Expanding the Role of Continuous Glucose Monitoring in Modern Diabetes Care Beyond Type 1 Disease
AbstractApplication of continuous glucose monitoring (CGM) has moved diabetes care from a reactive to a proactive process, in which a person with diabetes can prevent episodes of hypoglycemia or hyperglycemia, rather than taking action only once low and high glucose are detected. Consequently, CGM devices are now seen as the standard of care for people with type 1 diabetes mellitus (T1DM). Evidence now supports the use of CGM in people with type 2 diabetes mellitus (T2DM) on any treatment regimen, not just for those on insulin therapy. Expanding the application of CGM to include all people with T1DM or T2DM can support ...
Source: Diabetes Therapy - June 16, 2023 Category: Endocrinology Source Type: research
Atherosclerotic Cardiovascular Disease in Type 2 Diabetes: A Retrospective, Observational Study of Economic and Clinical Burden in Sweden
ConclusionsASCVD is associated with considerable costs, morbidity and mortality in individuals with T2D. These results support structured assessment of ASCVD risk and broader implementation of guideline-recommended treatments in T2D healthcare. (Source: Diabetes Therapy)
Source: Diabetes Therapy - June 16, 2023 Category: Endocrinology Source Type: research
Time in Range Estimation in Patients with Type 2 Diabetes is Improved by Incorporating Fasting and Postprandial Glucose Levels
ConclusionsThe results offered a comprehensive understanding of glucose fluctuations through FPG and PPG compared to HbA1c alone. Our novel TIR prediction model based on random forest regression with FPG, PPG, and HbA1c provides a better prediction performance than the univariate model with solely HbA1c. The results indicate a nonlinear relationship between TIR and glycaemic parameters. Our results suggest that machine learning may have the potential to be used in developing better models for understanding patients ’ disease status and providing necessary interventions for glycaemic control. (Source: Diabetes Therapy)
Source: Diabetes Therapy - June 16, 2023 Category: Endocrinology Source Type: research
Expanding the Role of Continuous Glucose Monitoring in Modern Diabetes Care Beyond Type 1 Disease
AbstractApplication of continuous glucose monitoring (CGM) has moved diabetes care from a reactive to a proactive process, in which a person with diabetes can prevent episodes of hypoglycemia or hyperglycemia, rather than taking action only once low and high glucose are detected. Consequently, CGM devices are now seen as the standard of care for people with type 1 diabetes mellitus (T1DM). Evidence now supports the use of CGM in people with type 2 diabetes mellitus (T2DM) on any treatment regimen, not just for those on insulin therapy. Expanding the application of CGM to include all people with T1DM or T2DM can support ...
Source: Diabetes Therapy - June 16, 2023 Category: Endocrinology Source Type: research
Atherosclerotic Cardiovascular Disease in Type 2 Diabetes: A Retrospective, Observational Study of Economic and Clinical Burden in Sweden
ConclusionsASCVD is associated with considerable costs, morbidity and mortality in individuals with T2D. These results support structured assessment of ASCVD risk and broader implementation of guideline-recommended treatments in T2D healthcare. (Source: Diabetes Therapy)
Source: Diabetes Therapy - June 16, 2023 Category: Endocrinology Source Type: research
Time in Range Estimation in Patients with Type 2 Diabetes is Improved by Incorporating Fasting and Postprandial Glucose Levels
ConclusionsThe results offered a comprehensive understanding of glucose fluctuations through FPG and PPG compared to HbA1c alone. Our novel TIR prediction model based on random forest regression with FPG, PPG, and HbA1c provides a better prediction performance than the univariate model with solely HbA1c. The results indicate a nonlinear relationship between TIR and glycaemic parameters. Our results suggest that machine learning may have the potential to be used in developing better models for understanding patients ’ disease status and providing necessary interventions for glycaemic control. (Source: Diabetes Therapy)
Source: Diabetes Therapy - June 16, 2023 Category: Endocrinology Source Type: research
