{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T06:24:40Z","timestamp":1779344680631,"version":"3.51.4"},"reference-count":16,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP21K08539"],"award-info":[{"award-number":["JP21K08539"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP21K08567"],"award-info":[{"award-number":["JP21K08567"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP21K08589"],"award-info":[{"award-number":["JP21K08589"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Continuous glucose monitoring (CGM) values obtained from CGM systems using the same sensor but with different internal algorithms (the first- and third-generation FreeStyle Libre (1st-gen-libre and 3rd-gen-libre, respectively)) were compared. We used 19,819 paired and simultaneously measured CGM values of 13 patients with diabetes. The average CGM value was significantly higher (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.0001) and the time below range (CGM value\u2009&lt;\u200970\u00a0mg\/dL) was significantly lower (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.0001) with the 3rd-gen-libre than with the 1st-gen-libre. There was a significant correlation (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.0001) between the CGM values of the 3rd-gen-libre (y-axis, mg\/dL) and 1st-gen-libre (x-axis, mg\/dL) using the following formula: y\u2009=\u20090.9728x\u2009+\u200910.024. On assessing the association between glycated hemoglobin (HbA1c (%), y-axis) and the average CGM values (x-axis, mg\/dL) by applying the obtained equation to previously reported 1st-gen-libre data and converting it to 3rd-gen-libre data, we obtained the equation y\u2009=\u20090.02628x\u2009+\u20093.233, indicating that the glucose management indicator reported in the West may be underestimated compared with the laboratory-measured HbA1c in the Japanese population. Glucose values from the same sensor were found to be significantly different between readers with different algorithms, and the calculation of CGM-related indices may need to be individualized for each device.<\/jats:p>","DOI":"10.1038\/s41598-024-55124-3","type":"journal-article","created":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T13:03:49Z","timestamp":1709298229000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Glucose values from the same continuous glucose monitoring sensor significantly differ among readers with different generations of algorithm"],"prefix":"10.1038","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2466-1228","authenticated-orcid":false,"given":"Naru","family":"Babaya","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shinsuke","family":"Noso","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yoshihisa","family":"Hiromine","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yasunori","family":"Taketomo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fumimaru","family":"Niwano","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sawa","family":"Yoshida","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sara","family":"Yasutake","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yumiko","family":"Kawabata","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Norikazu","family":"Maeda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiroshi","family":"Ikegami","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,3,1]]},"reference":[{"key":"55124_CR1","doi-asserted-by":"crossref","unstructured":"Diabetes Control and Complications Trial (DCCT)\/Epidemiology of Diabetes Interventions and Complications (EDIC) Study Research Group. Intensive diabetes treatment and cardiovascular outcomes in type 1 diabetes: The DCCT\/EDIC study 30-year follow-up. Diabetes Care 39, 686\u2013693 (2016).","DOI":"10.2337\/dc15-1990"},{"key":"55124_CR2","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1111\/dom.14638","volume":"24","author":"F Gomez-Peralta","year":"2022","unstructured":"Gomez-Peralta, F. et al. Understanding the clinical implications of differences between glucose management indicator and glycated haemoglobin. Diabetes Obes. Metab. 24, 599\u2013608 (2022).","journal-title":"Diabetes Obes. Metab."},{"key":"55124_CR3","doi-asserted-by":"publisher","first-page":"596","DOI":"10.1111\/dom.14906","volume":"25","author":"D Rodbard","year":"2023","unstructured":"Rodbard, D. Continuous glucose monitoring metrics (mean glucose, time above range and time in range) are superior to glycated haemoglobin for assessment of therapeutic efficacy. Diabetes Obes. Metab. 25, 596\u2013601 (2023).","journal-title":"Diabetes Obes. Metab."},{"key":"55124_CR4","doi-asserted-by":"publisher","first-page":"e2221","DOI":"10.1210\/clinem\/dgac034","volume":"107","author":"M Yapanis","year":"2022","unstructured":"Yapanis, M., James, S., Craig, M. E., O\u2019Neal, D. & Ekinci, E. I. Complications of diabetes and metrics of glycemic management derived from continuous glucose monitoring. J. Clin. Endocrinol. Metab. 107, e2221\u2013e2236 (2022).","journal-title":"J. Clin. Endocrinol. Metab."},{"key":"55124_CR5","doi-asserted-by":"publisher","first-page":"2254","DOI":"10.1016\/S0140-6736(16)31535-5","volume":"388","author":"J Bolinder","year":"2016","unstructured":"Bolinder, J., Antuna, R., Geelhoed-Duijvestijn, P., Kroger, J. & Weitgasser, R. Novel glucose-sensing technology and hypoglycaemia in type 1 diabetes: a multicentre, non-masked, randomised controlled trial. Lancet 388, 2254\u20132263 (2016).","journal-title":"Lancet"},{"key":"55124_CR6","doi-asserted-by":"publisher","first-page":"659","DOI":"10.2337\/dc21-0629","volume":"45","author":"RA Gubitosi-Klug","year":"2022","unstructured":"Gubitosi-Klug, R. A. et al. Continuous glucose monitoring in adults with type 1 diabetes with 35 years duration from the DCCT\/EDIC study. Diabetes Care 45, 659\u2013665 (2022).","journal-title":"Diabetes Care"},{"key":"55124_CR7","doi-asserted-by":"publisher","first-page":"787","DOI":"10.1089\/dia.2014.0378","volume":"17","author":"T Bailey","year":"2015","unstructured":"Bailey, T., Bode, B. W., Christiansen, M. P., Klaff, L. J. & Alva, S. The performance and usability of a factory-calibrated flash glucose monitoring system. Diabetes Technol. Ther. 17, 787\u2013794 (2015).","journal-title":"Diabetes Technol. 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