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 Diabetes Spectrum Journal current issueнет даты
Diabetes Spectrum Journal current issue

 
 
1. Impact of Diabetes on Hospitalized Patients With Chronic Medical ConditionsВт, 24 авг[−]
Автор(?)
AIM

To measure cost and length of stay in patients with and without a diagnosis of diabetes admitted with cardiovascular, pulmonary, or cerebrovascular disease.

METHODS

Retrospective study used International Classification of Diseases, 10th Revision, Clinical Modification codes to identify patients with diabetes, cardiovascular, pulmonary, or cerebrovascular disease. The All Patients Refined Diagnosis Related Groups, which classify patients according to admission diagnosis, severity of illness, and risk of mortality, was used to determine actual (discharge) diagnoses. Total admission cost and length of stay were compared using the Wilcoxon rank-sum test.

RESULTS

Study reviewed 48,572 subjects who met inclusion criteria. When compared with patients without diabetes of similar age, sex, race, risk of mortality, and severity of illness and controlling for length of stay, individuals with diabetes had similar total admission costs. Lengths of stay were similar for individuals with and without diabetes admitted with a diagnosis of cerebrovascular disease or respiratory infection. However, patients with a primary diagnosis of congestive heart failure and a secondary diagnosis of diabetes incurred longer lengths of stay.

CONCLUSION

Individuals with diabetes and congestive heart failure have longer lengths of stay than those without diabetes. To decrease the economic burden of diabetes and chronic conditions, primary care providers and hospitals need to implement guidelines regarding the management of care for individuals with two or more chronic conditions.


2. Patient Markers of Successful Diabetes ManagementВт, 24 авг[−]
Автор(?)
PURPOSE

For individuals with diabetes, diabetes health status may not align with A1C targets. Patients may use nonclinical targets when assessing their diabetes management success. Identifying these targets is important in developing patient-centered management plans. The purpose of this study was to identify patient markers of successful diabetes management among patients in an urban academic health system.

METHODS

A secondary analysis of semistructured interviews was completed with 89 adults with type 1 or type 2 diabetes. Participants had a recent diabetes-related emergency department (ED) visits or hospitalization or were primary care patients with an A1C >7.5%. Interviews were conducted to saturation. Demographic data were collected via self-report and electronic medical records. Interviews were analyzed using conventional content analysis. This analysis focused on patient perceptions of successful management coded to "measuring management success."

RESULTS

Although most participants cited A1C or blood glucose as a marker of successful diabetes management, they had varied understanding of these metrics. Most used a combination of targets from the following categories: 1) A1C, blood glucose, and numbers; 2) engagement in medical care; 3) taking medication and medication types; 4) symptoms; 5) diet, exercise, and weight; and 6) stress management and social support.

CONCLUSION

Individuals not meeting glycemic goals and/or with recent diabetes-related ED visits or hospitalizations had varied understanding of A1C and blood glucose targets. They use multiple additional markers of successful management and had a desire for management discussions that incorporate these markers. These measures should be incorporated into their care plans along with clinical targets.


3. The Diabetes-Specific Risk-Taking Inventory: Piloting a New Measure for Adolescents With Type 1 DiabetesВт, 24 авг[−]
Автор(?)
OBJECTIVE

We sought to develop and pilot a new measure, the Diabetes-Specific Risk-Taking Inventory (DSRI), to assess unhealthy risk-taking behaviors among adolescents with type 1 diabetes.

Methods

Thirteen diabetes health care providers, 30 adolescents with type 1 diabetes (aged 15–19 years, 60% female, mean A1C 8.7% [72 mmol/mol], and 33% on insulin pumps), and the adolescents’ caregivers rated the perceived riskiness of each item on the DSRI. Adolescents completed the DSRI, for which they reported how often they engaged in 34 behaviors that could place them at risk for acute complications of type 1 diabetes or out-of-range blood glucose levels. Adolescents also completed the risk-taking subscale from the Risk-Taking and Self-Harm Inventory for Adolescents, and parents completed the parent-proxy Diabetes Management Questionnaire. Mean A1C during the previous year was obtained via medical chart review.

Results

Results indicated good content validity and feasibility for using the DSRI in a research context, as 100% of adolescents who consented to the study completed the measure. The DSRI was positively correlated with general risk-taking and negatively correlated with diabetes management, indicating preliminary evidence of convergent validity. The DSRI also correlated with A1C.

Conclusion

This pilot study extends our previous work in developing a conceptual model for illness-specific risk-taking. The DSRI is a promising new measure to assess illness-specific risk-taking, including unhealthy risk-taking behaviors, for adolescents with type 1 diabetes.


4. Diabetes Distress, Daily Functioning, and A1C in Older Black Individuals With Diabetes and Mild Cognitive ImpairmentВт, 24 авг[−]
Автор(?)
OBJECTIVE The purpose of the cross-sectional study was to identify associations of diabetes distress, physical functioning, and cognition with A1C in older Black individuals with diabetes and mild cognitive impairment. METHODS The investigators analyzed previously collected data from 101 older Black individuals with diabetes and mild cognitive impairment. Participants were administered surveys at baseline to assess diabetes distress, physical functioning, and cognitive functioning and had A1C testing. RESULTS The mean age of participants was 68.4 years, and 62% were women. Participants with higher A1C showed worse self-reported daily functioning (r= –0.28, P

5. Perceptions of Diabetes Self-Efficacy and Glycemic Control in Youth With Type 1 DiabetesВт, 24 авг[−]
Автор(?)
Нет описания

6. Leveraging Mechanical Forces to Target Insulin Injection-Induced Lipohypertrophy and FibrosisВт, 24 авг[−]
Автор(?)
Нет описания

7. Social Adaptability Index and Pregnancy Outcomes in Women With Diabetes During PregnancyВт, 24 авг[−]
Автор(?)
OBJECTIVE The social adaptability index (SAI) is a composite indicator capturing an individual s social adaptability within society and socioeconomic status to predict overall health outcomes. The objective of this analysis was to examine whether the SAI is an independent risk factor for adverse pregnancy outcomes in women with and without diabetes during pregnancy. METHODS Data from the 2011–2017 National Survey of Family Growth were analyzed using a cross-sectional methodology. Women aged 18–44 years with a singleton gestation were included in the analysis. Maternal diabetes was defined as either presence of pregestational diabetes or diagnosis of gestational diabetes. The SAI was developed from the following maternal variables: educational level, employment status, income, marital status, and substance abuse. A higher score indicated lower risk. A series of multivariable logistic regression models were run stratified by maternal diabetes status to assess the association between SAI and pregnancy outcomes, including cesarean delivery, macrosomia (birth weight 4,000 g) and preterm birth (

8. Health Care Providers Utilization of and Perspectives on Mobile Health Technology for Diabetes and Pregnancy SupportВт, 24 авг[−]
Автор(?)
OBJECTIVE

Mobile health (mHealth) technology can be an effective tool to deliver behavioral interventions to improve health outcomes for individuals with diabetes. However, there is limited evidence on mHealth for pregnant women managing diabetes or for the role of health care providers (HCPs) in delivering mHealth tools. To prepare for the development of a pregnancy-specific mHealth intervention for diabetes, we sought to understand HCPs’ acceptance, utilization, and design recommendations for how mHealth technology can best be used to support the management of diabetes during pregnancy.

METHODS

Focus groups and individual interviews were conducted with clinical HCPs (obstetricians, nurses, diabetes educators, dietitians, and lactation counselors) who care for low-income pregnant women with diabetes. Data were analyzed using the constant comparative method.

RESULTS

Participants (n= 29) generated five themes and 14 subthemes. Knowledge and acceptance themes included utilization of mobile resources and barriers to HCPs’ adoption. Knowledge of popular pregnancy applications (apps) dominated, while familiarity with and use of diabetes apps varied by profession and proximity to continued education. Technology adoption barriers included lack of credibility, dependence on Internet resources, and reliance on knowledge networks. Design themes addressed user-centered design, responsive and practical education, and clinical integration. Clinicians recommended patient-participatory design, customizable features, data-tracking features, motivational feedback, and bidirectional communication capabilities.

CONCLUSION

Although HCPs strongly embraced mHealth tools as an adjunct to obstetric care for women with diabetes, they also expressed limited knowledge and apprehension about patient engagement. HCP recommendations and concerns must critically inform the development of meaningful tools for this population.


9. Cardiovascular Outcomes Trials of Incretin-Based TherapiesВт, 24 авг[−]
Автор(?)

The cardiovascular (CV) safety of glucagon-like peptide 1 (GLP-1) receptor agonists has been established in robust cardiovascular outcomes trials (CVOTs) in patients with type 2 diabetes at high CV risk. The GLP-1 receptor agonists liraglutide, dulaglutide, and injectable semaglutide demonstrated a significant CV benefit in these trials and now have indications to reduce the risk of major adverse CV events, including CV death, myocardial infarction, and stroke in adult patients with type 2 diabetes and established cardiovascular disease or high CV risk (dulaglutide). The dipeptidyl peptidase 4 inhibitors have also demonstrated CV safety in dedicated CVOTs but have not been associated with any CV benefit. Guidelines for the treatment of type 2 diabetes have evolved from a glucocentric focus to one that now focuses on reducing overall CV risk by personalizing therapy and using drugs such as GLP-1 receptor agonists with proven CV benefits.


10. About Ralph A. Defronzo, MD: Guest EditorВт, 24 авг[−]
Нет описания

11. Sodium-Glucose Cotransporter 2 Inhibitors and the KidneyВт, 24 авг[−]
Автор(?)
Diabetic kidney disease (DKD) accounts for about half of individuals entering end-stage renal disease programs. Patients with DKD frequently have associated microvascular complications and are at very high risk for developing macrovascular complications. Comprehensive treatment involves slowing or preventing the decline in glomerular filtration rate (GFR) and preventing macrovascular and further microvascular complications. Maintaining an A1C

12. Lessons Learned From Major Clinical Outcomes Trials Involving Sodium-Glucose Cotransporter 2 InhibitorsВт, 24 авг[−]
Автор(?)

Diabetes is a known risk factor for the development of cardiovascular and chronic kidney disease. Sodium–glucose cotransporter 2 inhibitors are glucose-lowering medications that have been demonstrated to improve clinical cardiovascular and renal outcomes. This article reviews recent large clinical trials involving these medications and explains their impact on type 2 diabetes treatment guidelines.


13. Antihyperglycemic Algorithms for Type 2 Diabetes: Focus on Nonglycemic OutcomesВт, 24 авг[−]
Автор(?)

Type 2 diabetes management continues to increase in complexity as more pharmacologic medication classes become available and high-quality clinical trials are completed. Because many antihyperglycemic agents could be appropriate for a given patient, expert treatment guidance is indispensable. Algorithms can help to guide clinicians toward initiating more evidence-based therapy and critically thinking about patient-centered factors that may influence their medication choices. High-quality cardiovascular, renal, and heart failure outcomes trials completed in the past several years have changed the paradigm of how we think about antihyperglycemic agents. Considerations for atherosclerotic cardiovascular disease, heart failure, and renal insufficiency now figure prominently in treatment algorithms for type 2 diabetes, and the results of recent outcomes trials have significantly transformed algorithmic guidelines published by diabetes, endocrinology, and cardiology associations.


14. Cardioprotective Effects of Pioglitazone in Type 2 DiabetesВт, 24 авг[−]
Автор(?)

Antidiabetic medications that improve glycemic control as well as cardiovascular outcomes will be the mainstay of treatment for type 2 diabetes moving forward. This article reviews the beneficial effects of the thiazolidinedione pioglitazone of ameliorating hyperglycemia and improving cardiovascular risk factors. While the newer sodium–glucose cotransporter 2 inhibitor and glucagon-like peptide 1 receptor agonist drug classes have confirmed cardiovascular benefits, pioglitazone also has been shown to reduce major adverse cardiovascular events, in both people with type 2 diabetes and nondiabetic subjects with insulin resistance. Adverse effects associated with pioglitazone can be mitigated by its use at a lower dose and in combination with antidiabetic agents from other drug classes.


15. Preface: Cardiorenal Considerations for Type 2 Diabetes--Time to Exit the Dark AgesВт, 24 авг[−]
Автор(?)
Нет описания


 
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