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  • 11
    Online Resource
    Online Resource
    Utility and precision evidence of technology in the treatment of type 1 diabetes: a systematic review
    Springer Science and Business Media LLC ; 2023
    In:  Communications Medicine Vol. 3, No. 1 ( 2023-10-05)
    Details
    In: Communications Medicine, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2023-10-05)
    Abstract: The greatest change in the treatment of people living with type 1 diabetes in the last decade has been the explosion of technology assisting in all aspects of diabetes therapy, from glucose monitoring to insulin delivery and decision making. As such, the aim of our systematic review was to assess the utility of these technologies as well as identify any precision medicine-directed findings to personalize care. Methods Screening of 835 peer-reviewed articles was followed by systematic review of 70 of them (focusing on randomized trials and extension studies with ≥50 participants from the past 10 years). Results We find that novel technologies, ranging from continuous glucose monitoring systems, insulin pumps and decision support tools to the most advanced hybrid closed loop systems, improve important measures like HbA1c, time in range, and glycemic variability, while reducing hypoglycemia risk. Several studies included person-reported outcomes, allowing assessment of the burden or benefit of the technology in the lives of those with type 1 diabetes, demonstrating positive results or, at a minimum, no increase in self-care burden compared with standard care. Important limitations of the trials to date are their small size, the scarcity of pre-planned or powered analyses in sub-populations such as children, racial/ethnic minorities, people with advanced complications, and variations in baseline glycemic levels. In addition, confounders including education with device initiation, concomitant behavioral modifications, and frequent contact with the healthcare team are rarely described in enough detail to assess their impact. Conclusions Our review highlights the potential of technology in the treatment of people living with type 1 diabetes and provides suggestions for optimization of outcomes and areas of further study for precision medicine-directed technology use in type 1 diabetes.
    Type of Medium: Online Resource
    ISSN: 2730-664X
    URL: Article
    DOI: 10.1038/s43856-023-00358-x
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 3096949-9
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  • 12
    Online Resource
    Online Resource
    Genotype-stratified treatment for monogenic insulin resistance: a systematic review
    Springer Science and Business Media LLC ; 2023
    In:  Communications Medicine Vol. 3, No. 1 ( 2023-10-05)
    Details
    In: Communications Medicine, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2023-10-05)
    Abstract: Monogenic insulin resistance (IR) includes lipodystrophy and disorders of insulin signalling. We sought to assess the effects of interventions in monogenic IR, stratified by genetic aetiology. Methods Systematic review using PubMed, MEDLINE and Embase (1 January 1987 to 23 June 2021). Studies reporting individual-level effects of pharmacologic and/or surgical interventions in monogenic IR were eligible. Individual data were extracted and duplicates were removed. Outcomes were analysed for each gene and intervention, and in aggregate for partial, generalised and all lipodystrophy. Results 10 non-randomised experimental studies, 8 case series, and 23 case reports meet inclusion criteria, all rated as having moderate or serious risk of bias. Metreleptin use is associated with the lowering of triglycerides and haemoglobin A1c (HbA1c) in all lipodystrophy ( n  = 111), partial ( n  = 71) and generalised lipodystrophy ( n  = 41), and in LMNA , PPARG , AGPAT2 or BSCL2 subgroups ( n  = 72,13,21 and 21 respectively). Body Mass Index (BMI) is lowered in partial and generalised lipodystrophy, and in LMNA or BSCL2 , but not PPARG or AGPAT2 subgroups. Thiazolidinediones are associated with improved HbA1c and triglycerides in all lipodystrophy ( n  = 13), improved HbA1c in PPARG ( n  = 5), and improved triglycerides in LMNA ( n  = 7). In INSR -related IR, rhIGF-1, alone or with IGFBP3, is associated with improved HbA1c ( n  = 17). The small size or absence of other genotype-treatment combinations preclude firm conclusions. Conclusions The evidence guiding genotype-specific treatment of monogenic IR is of low to very low quality. Metreleptin and Thiazolidinediones appear to improve metabolic markers in lipodystrophy, and rhIGF-1 appears to lower HbA1c in INSR-related IR. For other interventions, there is insufficient evidence to assess efficacy and risks in aggregated lipodystrophy or genetic subgroups.
    Type of Medium: Online Resource
    ISSN: 2730-664X
    URL: Article
    DOI: 10.1038/s43856-023-00368-9
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 3096949-9
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  • 13
    Online Resource
    Online Resource
    The Rare and Atypical Diabetes Network (RADIANT) Study: Design and Early Results
    American Diabetes Association ; 2023
    In:  Diabetes Care Vol. 46, No. 6 ( 2023-06-01), p. 1265-1270
    Details
    In: Diabetes Care, American Diabetes Association, Vol. 46, No. 6 ( 2023-06-01), p. 1265-1270
    Abstract: The Rare and Atypical Diabetes Network (RADIANT) will perform a study of individuals and, if deemed informative, a study of their family members with uncharacterized forms of diabetes. RESEARCH DESIGN AND METHODS The protocol includes genomic (whole-genome [WGS], RNA, and mitochondrial sequencing), phenotypic (vital signs, biometric measurements, questionnaires, and photography), metabolomics, and metabolic assessments. RESULTS Among 122 with WGS results of 878 enrolled individuals, a likely pathogenic variant in a known diabetes monogenic gene was found in 3 (2.5%), and six new monogenic variants have been identified in the SMAD5, PTPMT1, INS, NFKB1, IGF1R, and PAX6 genes. Frequent phenotypic clusters are lean type 2 diabetes, autoantibody-negative and insulin-deficient diabetes, lipodystrophic diabetes, and new forms of possible monogenic or oligogenic diabetes. CONCLUSIONS The analyses will lead to improved means of atypical diabetes identification. Genetic sequencing can identify new variants, and metabolomics and transcriptomics analysis can identify novel mechanisms and biomarkers for atypical disease.
    Type of Medium: Online Resource
    ISSN: 0149-5992 , 1935-5548
    URL: Article
    DOI: 10.2337/dc22-2440
    Language: English
    Publisher: American Diabetes Association
    Publication Date: 2023
    detail.hit.zdb_id: 1490520-6
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