{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T14:48:52Z","timestamp":1786718932784,"version":"build-2736575974"},"reference-count":5,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2023,1,27]],"date-time":"2023-01-27T00:00:00Z","timestamp":1674777600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Diabetes Technology & Therapeutics"],"published-print":{"date-parts":[[2023,2]]},"abstract":"\n Objective:<\/jats:title>\n To evaluate optimal continuous glucose monitoring (CGM) sampling duration to estimate glycemia risk index (GRI).<\/jats:p>\n <\/jats:sec>\n \n Methods:<\/jats:title>\n \n Up to 90 days of CGM data from 225 nonpregnant adults with type 1 diabetes (median age 40 years, 60% females, and 20 years of diabetes duration) and not using hybrid closed-loop system were collected. The association between GRI from various sampling periods and GRI using all 90 days of data was determined using the squared value of the Pearson correlation coefficient (\n R<\/jats:italic>\n 2<\/jats:sup>\n ).\n <\/jats:p>\n <\/jats:sec>\n \n Results:<\/jats:title>\n \n With increasing duration of the CGM sampling period, there was higher correlation with the 90-day GRI:\n R<\/jats:italic>\n 2<\/jats:sup>\n of 0.79 for 7 days,\n R<\/jats:italic>\n 2<\/jats:sup>\n of 0.88 for 14 days, and\n R<\/jats:italic>\n 2<\/jats:sup>\n of 0.93 for 30 days. In a sensitivity analysis, correlation (\n r<\/jats:italic>\n ) or correlation coefficient (\n R<\/jats:italic>\n 2<\/jats:sup>\n ) for CGM sampling period for GRI estimation was not different among participants with time <70\u2009mg\/dL of <4% and participants with time <70\u2009mg\/dL of >4%.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion:<\/jats:title>\n Though 14 days of CGM sampling duration is optimal for estimation of GRI, 7 days of CGM data may be enough to estimate GRI to monitor change in quality of glycemia with intervention.<\/jats:p>\n <\/jats:sec>","DOI":"10.1089\/dia.2022.0401","type":"journal-article","created":{"date-parts":[[2022,11,18]],"date-time":"2022-11-18T10:34:40Z","timestamp":1668767680000},"page":"140-142","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":31,"title":["Optimal Sampling Duration for Continuous Glucose Monitoring for the Estimation of Glycemia Risk Index"],"prefix":"10.1177","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3827-7107","authenticated-orcid":false,"given":"Viral N.","family":"Shah","sequence":"first","affiliation":[{"name":"Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Casey","family":"Sakamoto","sequence":"additional","affiliation":[{"name":"Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"Pyle","sequence":"additional","affiliation":[{"name":"Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2023,1,27]]},"reference":[{"key":"e_1_3_5_2_2","doi-asserted-by":"publisher","DOI":"10.1177\/19322968221085273"},{"key":"e_1_3_5_3_2","doi-asserted-by":"publisher","DOI":"10.2337\/dci19-0028"},{"key":"e_1_3_5_4_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2017.0455"},{"key":"e_1_3_5_5_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2022.0093"},{"key":"e_1_3_5_6_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2020.0387"}],"container-title":["Diabetes Technology & Therapeutics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1089\/dia.2022.0401","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1089\/dia.2022.0401","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1089\/dia.2022.0401","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T18:13:50Z","timestamp":1777400030000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1089\/dia.2022.0401"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,27]]},"references-count":5,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,2]]}},"alternative-id":["10.1089\/dia.2022.0401"],"URL":"https:\/\/doi.org\/10.1089\/dia.2022.0401","relation":{},"ISSN":["1520-9156","1557-8593"],"issn-type":[{"value":"1520-9156","type":"print"},{"value":"1557-8593","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,27]]}}}