{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T13:36:53Z","timestamp":1777556213878,"version":"3.51.4"},"reference-count":5,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2023,2,28]],"date-time":"2023-02-28T00:00:00Z","timestamp":1677542400000},"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":[[2023,3]]},"abstract":"\n Objective:<\/jats:title>\n \n While it is recognized that there is a strong relationship between the amount of time glucose levels are <70 mg\/dL (T\n <70<\/jats:sup>\n ) and the amount of time <54 mg\/dL (T\n <54<\/jats:sup>\n ), the association has not been well quantified.\n <\/jats:p>\n <\/jats:sec>\n \n Methods:<\/jats:title>\n \n Datasets with Dexcom continuous glucose monitoring (CGM) data from nine type 1 diabetes randomized trials were pooled to evaluate the relationship between CGM-measured T\n <70<\/jats:sup>\n and T\n <54<\/jats:sup>\n . Penalized B-spline regression lines were fitted to assess the relationship between T\n <70<\/jats:sup>\n and T\n <54<\/jats:sup>\n for blinded CGM use, unblinded CGM use without an automated insulin delivery (AID) system, and unblinded CGM use with an AID system.\n <\/jats:p>\n <\/jats:sec>\n \n Results:<\/jats:title>\n \n For blinded data, the T\n <54<\/jats:sup>\n : T\n <70<\/jats:sup>\n ratio varied from 19% when the amount of T\n <70<\/jats:sup>\n was <1% to 44% when the amount of T\n <70<\/jats:sup>\n was \u22657% whereas for unblinded data the ratio varied from 15% to 42%, respectively. When T\n <70<\/jats:sup>\n was 4%, the predicted T\n <54<\/jats:sup>\n was 1.18%, 0.94%, and 0.91% for the blinded, unblinded, and AID data, respectively (\n P<\/jats:italic>\n <0.001 comparing blinded versus unblinded and AID).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions:<\/jats:title>\n \n The T\n <54<\/jats:sup>\n : T\n <70<\/jats:sup>\n ratio increases with greater T\n <70<\/jats:sup>\n , and the ratio generally is higher with blinded than unblinded CGM data, with the latter appearing to be similar to AID system data. The finding of greater T\n <54<\/jats:sup>\n for a given T\n <70<\/jats:sup>\n with blinded CGM data is presumed to be due to an action being taken by the unblinded CGM user and\/or by the AID system to minimize hypoglycemia which will have the effect of reducing the amount of T\n <54<\/jats:sup>\n .\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1089\/dia.2022.0462","type":"journal-article","created":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:45:15Z","timestamp":1672224315000},"page":"157-160","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["The Relationship Between Percent Time <70\u2009mg\/dL and Percent Time <54\u2009mg\/dL Measured by Continuous Glucose Monitoring"],"prefix":"10.1177","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5194-8446","authenticated-orcid":false,"given":"Roy W.","family":"Beck","sequence":"first","affiliation":[{"name":"JAEB Center for Health Research, Tampa, Florida, USA."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan","family":"Raghinaru","sequence":"additional","affiliation":[{"name":"JAEB Center for Health Research, Tampa, Florida, USA."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5325-7200","authenticated-orcid":false,"given":"Peter","family":"Calhoun","sequence":"additional","affiliation":[{"name":"JAEB Center for Health Research, Tampa, Florida, USA."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9050-5584","authenticated-orcid":false,"given":"Richard M.","family":"Bergenstal","sequence":"additional","affiliation":[{"name":"International Diabetes Center, HealthPartners Institute, Minneapolis, Minnesota, USA."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2023,2,28]]},"reference":[{"key":"e_1_3_5_2_2","doi-asserted-by":"publisher","DOI":"10.2337\/dc16-2215"},{"key":"e_1_3_5_3_2","doi-asserted-by":"publisher","DOI":"10.2337\/dc10-1111"},{"key":"e_1_3_5_4_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2012.0062"},{"key":"e_1_3_5_5_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2019.0440"},{"key":"e_1_3_5_6_2","doi-asserted-by":"publisher","DOI":"10.2337\/dc20-0016"}],"container-title":["Diabetes Technology & Therapeutics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1089\/dia.2022.0462","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1089\/dia.2022.0462","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1089\/dia.2022.0462","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T18:13:53Z","timestamp":1777400033000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1089\/dia.2022.0462"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,28]]},"references-count":5,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,3]]}},"alternative-id":["10.1089\/dia.2022.0462"],"URL":"https:\/\/doi.org\/10.1089\/dia.2022.0462","relation":{},"ISSN":["1520-9156","1557-8593"],"issn-type":[{"value":"1520-9156","type":"print"},{"value":"1557-8593","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,28]]}}}