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dc.contributor.author이다영-
dc.contributor.authorNamho Kim-
dc.contributor.authorInha Jung-
dc.contributor.author박소영-
dc.contributor.authorYu Ji Hee-
dc.contributor.author서지아-
dc.contributor.authorJihee Kim-
dc.contributor.author김경진-
dc.contributor.author김남훈-
dc.contributor.author류혜진-
dc.contributor.author김신곤-
dc.contributor.author최경묵-
dc.contributor.author백세현-
dc.contributor.author박성민-
dc.contributor.author김난희-
dc.date.accessioned2024-04-16T08:20:24Z-
dc.date.available2024-04-16T08:20:24Z-
dc.date.created2023-12-28-
dc.date.issued2023-11-
dc.identifier.issn2233-6079-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/123076-
dc.description.abstractBackground: There was limited evidence to evaluate the association between lifestyle habits and continuous glucose monitoring (CGM) metrics. Thus, we aimed to depict the behavioral and metabolic determinants of CGM metrics in insulin-treated patients with type 2 diabetes mellitus (T2DM).Methods: This is a prospective observational study. We analyzed data from 122 insulin-treated patients with T2DM. Participants wore Dexcom G6 and Fitbit, and diet information was identified for 10 days. Multivariate-adjusted logistic regression analysis was performed for the simultaneous achievement of CGM-based targets, defined by the percentage of time in terms of hyper, hypoglycemia and glycemic variability (GV). Intake of macronutrients and fiber, step counts, sleep, postprandial C-peptide-to-glucose ratio (PCGR), information about glucose lowering medications and metabolic factors were added to the analyses. Additionally, we evaluated the impact of the distribution of energy and macronutrient during a day, and snack consumption on CGM metrics.Results: Logistic regression analysis revealed that female, participants with high PCGR, low glycosylated hemoglobin (HbA1c) and daytime step count had a higher probability of achieving all targets based on CGM (odds ratios [95% confidence intervals] which were 0.24 [0.09 to 0.65], 1.34 [1.03 to 1.25], 0.95 [0.9 to 0.99], and 1.15 [1.03 to 1.29], respectively). And participants who ate snacks showed a shorter period of hyperglycemia and less GV compared to those without.Conclusion: We confirmed that residual insulin secretion, daytime step count, HbA1c, and women were the most relevant determinants of adequate glycemic control in insulin-treated patients with T2DM. In addition, individuals with snack consumption were exposed to lower times of hyperglycemia and GV.-
dc.languageEnglish-
dc.publisher대한당뇨병학회-
dc.relation.isPartOfDiabetes and Metabolism Journal-
dc.titleClinical and Lifestyle Determinants of Continuous Glucose Monitoring Metrics in Insulin-Treated Patients with Type 2 Diabetes Mellitus-
dc.title.alternativeClinical and Lifestyle Determinants of Continuous Glucose Monitoring Metrics in Insulin-Treated Patients with Type 2 Diabetes Mellitus-
dc.typeArticle-
dc.identifier.doi10.4093/dmj.2022.0273-
dc.type.rimsART-
dc.identifier.bibliographicCitationDiabetes and Metabolism Journal, v.47, no.6, pp.826 - 836-
dc.identifier.kciidART003016991-
dc.identifier.wosid001112931700004-
dc.citation.endPage836-
dc.citation.number6-
dc.citation.startPage826-
dc.citation.titleDiabetes and Metabolism Journal-
dc.citation.volume47-
dc.contributor.affiliatedAuthorNamho Kim-
dc.contributor.affiliatedAuthor박성민-
dc.identifier.scopusid2-s2.0-85178666396-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.isOpenAccessY-
dc.type.docTypeArticle-
dc.subject.keywordPlusDAY GLYCEMIC VARIABILITY-
dc.subject.keywordPlusLOW-CARBOHYDRATE-
dc.subject.keywordPlusDIET-
dc.subject.keywordPlusRISK-
dc.subject.keywordAuthorBlood glucose-
dc.subject.keywordAuthorBlood glucose self-monitoring-
dc.subject.keywordAuthorDiabetes mellitus-
dc.subject.keywordAuthortype 2-
dc.subject.keywordAuthorDiet-
dc.subject.keywordAuthorLife style-
dc.relation.journalWebOfScienceCategoryEndocrinology & Metabolism-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClasskci-

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