Diabetes and its various comorbidities are responsible for a substantial societal financial burden. Healthcare and managed care providers must take responsibility for and address the high healthcare costs attributed to diabetes care. They can work together to improve diabetes-related patient care and reduce costs. Newer therapeutic agents and those used as combination therapy may decrease direct costs by improving glycemic control and preventing negative outcomes associated with diabetes comorbidities. Additional diabetes education, increased time to review medication adherence and diabetes monitoring, and having affordable care are all necessary to improve the care of individuals with diabetes.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Survival Disparity and the Unique Genomic and Microbiome Profiles of Colon Cancer in Appalachian Kentucky.
J Am Coll Surg
January 2025
Department of Surgery, University of Kentucky Medical Center, Lexington, KY.
Background: Colon cancer is a leading cause of mortality in Appalachian Kentucky. Studies suggest that the microbiome may influence cancer outcomes. We investigate differential gene expression, the tumor microbiome, and the association between the two as potential drivers of disparities in colon cancer outcomes.
View Article and Find Full Text PDFCharacteristics of patients with undiagnosed stage 3 chronic kidney disease: results from an observational study (REVEAL-CKD) in China.
Lancet Reg Health West Pac
January 2025
Division of Nephrology, National Clinical Research Centre for Kidney Disease, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Background: Early diagnosis of chronic kidney disease (CKD) is crucial for timely intervention to delay disease progression and improve patient outcomes. However, data for clinical characteristics of Chinese patients with undiagnosed, early-stage CKD are lacking.
Methods: REVEAL-CKD is a multinational, observational study using real-world data in selected countries to describe factors associated with undiagnosed stage 3 CKD, time to diagnosis, and CKD management post diagnosis.
Dates fruit effects on dyslipidemia among patients with Type-2 diabetes mellitus: A systematic review and meta-analysis of randomized trials.
Pak J Med Sci
January 2025
Amirah Alhowiti Assistant Professor of Family Medicine, Department of Family and Community Medicine, Faculty of Medicine, University of Tabuk, Saudi Arabia.
Objectives: Dyslipidemias are major risk factors for cardiovascular disease, and other comorbidities. The focus on food and nutrition to prevent and treat cardiovascular risk factors including dyslipidemia is a paradigm shift. This is the first meta-analysis to assess the association of dates fruit and dyslipidemia in Type-2 diabetes.
View Article and Find Full Text PDFAntin-diabetic cognitive dysfunction effects and underpinning mechanisms of phytogenic bioactive peptides: a review.
Front Nutr
January 2025
College of Food Science and Technology, Yunan Agricultural University, Kunming, China.
Diabetic cognitive dysfunction is one of the important comorbidities and complications of diabetes, which is mainly manifested by loss of learning ability and memory, behavioural disorders, and may even develop into dementia. While traditional anti-diabetic medications are effective in improving cognition and memory, long-term use of these medications can be accompanied by undesirable side effects. Therefore, there is an urgent need to find safe and effective alternative therapies.
View Article and Find Full Text PDFA Machine Learning Model for Predicting Prognosis in HCC Patients With Diabetes After TACE.
J Hepatocell Carcinoma
January 2025
Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, 430022, People's Republic of China.
Purpose: Type II diabetes mellitus (T2DM) has been found to increase the mortality of patients with hepatocellular carcinoma (HCC). Therefore, this study aimed to establish and validate a machine learning-based explainable prediction model of prognosis in patients with HCC and T2DM undergoing transarterial chemoembolization (TACE).
Patients And Methods: The prediction model was developed using data from the derivation cohort comprising patients from three medical centers, followed by external validation utilizing patient data extracted from another center.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!