The "Health Management Plan"(HMP) for caring diabetic patient was begun by the National Health Insurance (NHI) in Taiwan in order to maximize the effectiveness of limited medical resources. This study describes the clinical experience of the nurse-directed diabetic HMP program and analyzes factors associated with the outcome. One hundred and thirty-six patients, all of whom had participated in the diabetic HMP program at least 5 times, were enrolled in the study. The effect of the HMP was evaluated by comparing hemoglobin A1C status before and after %) maintained their hemoglobin A1C status over the course of HMP participation. Diabetic patients with regular exercise habits showed a 2.8-fold increased chance of outcome improvement compared with those who did not exercise regularly. The chance of outcome improvement in patients with complications was found to be one-third that of patients who had no complications (Odds ratio: 0.3, 95% CI: 0.1-1.0). This study found that specially trained nurses, following agreed upon protocols and algorithms and collaborating with medical team members, can effectively concentrate on providing comprehensive and effective diabetes care.
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Int J Cardiol
December 2024
Brigham and Women's Hospital Heart and Vascular Center, Boston, MA, USA; Baim Institute for Clinical Research, Boston, MA, USA. Electronic address:
Background: Patients with a history of coronary revascularization are at a higher risk for subsequent cardiovascular events and all-cause mortality. Lowering LDL-cholesterol (LDL-C) levels post-revascularization significantly reduces these risks.
Methods: This analysis compared LDL-C-lowering therapies at baseline and over time among patients with and without prior coronary revascularization in the GOULD registry (a prospective multicenter cohort study).
Diabetologia
December 2024
University of Miami Miller School of Medicine, University of Miami, Miami, FL, USA.
Aims/hypothesis: Many studies of type 1 diabetes pathogenesis focus on individuals with high-risk HLA haplotypes. We tested the hypothesis that, among islet autoantibody-positive individuals, lacking HLA-DRB1*04-DQA1*03-DQB1*0302 (HLA-DR4-DQ8) and/or HLA-DRB1*0301-DQA1*0501-DQB1*0201 (HLA-DR3-DQ2) is associated with phenotypic differences, compared with those who have these high-risk HLA haplotypes.
Methods: We classified autoantibody-positive relatives of individuals with type 1 diabetes into four groups based on having both HLA-DR4-DQ8 and HLA-DR3-DQ2 (DR3/DR4; n=1263), HLA-DR4-DQ8 but not HLA-DR3-DQ2 (DR4/non-DR3; n=2340), HLA-DR3-DQ2 but not HLA-DR4-DQ8 (DR3/non-DR4; n=1607) and neither HLA-DR3-DQ2 nor HLA-DR4-DQ8 (DRX/DRX; n=1294).
Cureus
October 2024
School of Pharmacy, Social and Administrative Sciences Division, University of Wisconsin-Madison, Madison, USA.
Background Adolescents with type 1 diabetes mellitus (T1DM) experience stress from general life stressors and diabetes-specific stressors. This stress manifests in a range of ways, such as mood swings, heightened frustration, strained familial relationships, and difficulties in T1DM self-management, which then leads to worse health outcomes. There is small to moderate evidence that frequent use of mental health applications (MHapps) improves mental and physical health outcomes.
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November 2024
Klinik für Innere Medizin III, Kardiologie, Angiologie und Internistische Intensivmedizin, Universitätsklinikum des Saarlandes, Universität des Saarlandes, Homburg, Germany (D.V., L.L., M.B., F.M.).
BMJ Open
September 2024
Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany
Objectives: To validate and test the generalisability of the SASKit-ML pipeline, a prepublished feature selection and machine learning pipeline for the prediction of health deterioration after a stroke or pancreatic adenocarcinoma event, by using it to identify biomarkers of health deterioration in chronic disease.
Design: This is a validation study using a predefined protocol applied to multiple publicly available datasets, including longitudinal data from cohorts with type 2 diabetes (T2D), inflammatory bowel disease (IBD), rheumatoid arthritis (RA) and various cancers. The datasets were chosen to mimic as closely as possible the SASKit cohort, a prospective, longitudinal cohort study.
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