Aims: On the basis of the Diabetes Versorgungs-Evaluation (DIVE) and Diabetes-Patienten-Verlaufsdokumentation (DPV) datasets, we aimed to explore the impact of differences in treatment modalities on outcomes in Germany and put these into a global context.
Methods: The 2014 to 2016 DIVE and DPV databases were combined, and a total of 127 838 patients 18 years and older was analysed with respect to demographics, cardiovascular risk factors, comorbidities, treatments, and outcomes, separately for each German state. Estimates were expressed as adjusted least squares means together with 95% confidence intervals.
Results: Saarland dataset recorded the lowest mean HbA (6.7%; 6.6%-6.8%; 50 mmol/mol, 49-51 mmol/mol), Saxony-Anhalt showed the highest (8.3%; 8.2%-8.3%; 67 mmol/mol, 66-67 mmol/mol). The highest percentage of hypoglycaemic events was reported in Mecklenburg-West Pomerania (MWP) (4.7%; 3.9%-5.7%), the lowest in Thuringia (0.9%; 0.2%-3.4%). Metformin and sulfonylurea accounted for 36.4% to 53.3% of anti-diabetic treatments across states; other antihyperglycaemic drugs such as DPP-4 inhibitors, SGLT2 inhibitors, and GLP-1 analogues were used most often in MWP (40.0%; 37.8%-42.1%) and least in Rhineland-Palatinate (13.6%; 13.0%-14.2%). Treatment with insulin (alone or in combination) was reported most often in MWP (78.2%; 76.4%-80.0%) and least in Thuringia (26.0%; 20.1%-32.9%).
Conclusions: Federal states in Germany are heterogeneous concerning diabetes treatment and associated outcomes. These data should stimulate further discussion about how optimal diabetes care can be implemented in all areas of Germany, to achieve good treatment outcomes in all federal states.
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http://dx.doi.org/10.1002/dmrr.3049 | DOI Listing |
Sci Rep
December 2024
Division of Joint Surgery and Sports Medicine, Department of Orthopedic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
Lines of evidence have indicated that type 2 diabetes mellitus (T2DM) is an independent risk factor for osteoarthritis (OA) progression. However, the study focused on the relationship between T2DM and OA at the transcriptional level remains empty. We downloaded OA- and T2DM-related bulk RNA-sequencing and single-cell RNA sequencing data from the Gene Expression Omnibus (GEO) dataset.
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December 2024
School of Science, Xi'an Technological University, Xi'an, 710021, PR China.
This paper introduces a class of insulin-glucose-glucocorticoid impulsive systems in the treatment of patients with diabetes to consider the effect of glucocorticoids. The existence and uniqueness of the positive periodic solution of the impulsive model at double fixed time is confirmed for type 1 diabetes mellitus (T1DM) using the [Formula: see text] function. Further, the global asymptotic stability of the positive periodic solution is achieved following Floquet multiplier theory and comparison principle.
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December 2024
Computer Science Department, Indiana University, Bloomington, IN, USA.
Pediatric diabetes I is an endemic and an especially difficult disease; indeed, at this point, there does not exist a cure, but only careful management that relies on anticipating hypoglycemia. The changing physiology of children producing unique blood glucose signatures, coupled with inconsistent activities, e.g.
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December 2024
Department of Endocrinology and Metabolism, Chengdu First People's Hospital, No.18 North Vientiane Road, High-Tech Zone, Chengdu, 610000, Sichuan, China.
We aimed to determine the association between anion gap-to-calcium ratio (ACR) and 30-day mortality in sepsis patients with diabetes mellitus (DM). Data for sepsis patients diagnosed with DM was extracted from Medical Information Mart for Intensive Care Database IV. After screening, 4429 eligible subjects were included in our study finally.
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December 2024
Upstream Lab, MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.
Background: Machine learning (ML) is increasingly used in population and public health to support epidemiological studies, surveillance, and evaluation. Our objective was to conduct a scoping review to identify studies that use ML in population health, with a focus on its use in non-communicable diseases (NCDs). We also examine potential algorithmic biases in model design, training, and implementation, as well as efforts to mitigate these biases.
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