{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T05:54:00Z","timestamp":1781848440043,"version":"3.54.5"},"reference-count":32,"publisher":"SAGE Publications","issue":"12","license":[{"start":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T00:00:00Z","timestamp":1752537600000},"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 &amp; Therapeutics"],"published-print":{"date-parts":[[2025,12,1]]},"abstract":"<jats:sec>\n                    <jats:title>Introduction:<\/jats:title>\n                    <jats:p>Consensus guidelines recommend reviewing 14 days of continuous glucose monitor (CGM) data when assessing glycemia in people with type 1 diabetes (T1D). Adult studies have shown that 7 days of CGM data provide a reliable assessment of glycemia.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives:<\/jats:title>\n                    <jats:p>To understand the minimum amount of CGM data required to assess glycemia in the pediatric T1D population.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>Real-world Dexcom G6 CGM data were extracted from cloud-based CGM software for 8 time windows (3, 5, 7, 10, 14, 30, 60, and 90 days), all starting on March 1, 2023. Youth &lt;21 years with T1D and \u226570% CGM active time in each window were included. Pearson correlation and interclass correlation coefficients (ICCs) between 14-day data and other windows were calculated. Differences in the percentage of youth within predetermined thresholds of 14-day CGM metrics (\u00b10.3% glucose management indicator [GMI]; \u00b15% time in range [TIR]\/time in tight range; \u00b11% time below range &lt;70 and &lt;54 mg\/dL) were assessed using chi-squared analyses. Sub-analyses were conducted according to categorical groupings of 14-day TIR, coefficient of variation (CV), and age.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>A total of 1316 youth were included (45.0% female, 76.9% non-Hispanic White, median age 14.6 years). Median 14-day CGM active time was 97.2% and GMI and TIR were 7.4% (7.0, 7.9) and 60.5% (48.6, 70.6), respectively. Pearson correlation coefficients and ICCs between 14-day and GMI and TIR for all 8 windows were &gt;0.9; however, categorical agreement as defined by the percentage of subjects acceptable thresholds for GMI and TIR only exceeded 90% at 10 days. Although there was no difference in agreement for CGM metrics according to categorical groupings of age, agreement was stronger for youth with TIR \u226570% and CV &lt;36%.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>Although 14 days of CGM data are considered the gold standard, assessing \u223c9.6 days of data in youth with T1D provides a reliable assessment of glycemia. For youth with higher TIR (\u226570%) and lower CV (&lt;36%), 7-day CGM data may prove sufficient.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1089\/dia.2025.0173","type":"journal-article","created":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T11:59:52Z","timestamp":1752580792000},"page":"973-980","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Minimum Continuous Glucose Monitor Data Required to Assess Glycemic Control in Youth with Type 1 Diabetes"],"prefix":"10.1177","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8333-816X","authenticated-orcid":false,"given":"Sonia","family":"Gera","sequence":"first","affiliation":[{"name":"Children\u2019s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Rearson","sequence":"additional","affiliation":[{"name":"Children\u2019s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert J.","family":"Gallop","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4849-9774","authenticated-orcid":false,"given":"Brynn E.","family":"Marks","sequence":"additional","affiliation":[{"name":"Division of Endocrinology and Diabetes, University of Pennsylvania, Philadelphia, Pennsylvania, USA."},{"name":"Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,7,15]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2018.0384"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.2337\/dc19-2213"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1159\/000487361"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(18)30297-6"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.2337\/dc17-0636"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.2337\/dc18-1581"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1177\/19322968211023171"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2020.0236"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmjdrc-2019-001045"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2018.0310"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.2337\/dci19-0028"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2017.0455"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2020.6940"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa0805017"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.2337\/dc09-0889"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.2337\/dc18-2625"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1111\/pedi.12248"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2022.0284"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1177\/19322968211069177"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2010.0156"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1080\/02664763.2014.920780"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.2331"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcm.2016.02.012"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1159\/000521430"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.2337\/dc19-0083"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1464-5491.2007.02357.x"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.2337\/dc23-S006"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1177\/19322968231200901"},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2018.0079"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2019.0400"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.2337\/dc20-3063"},{"key":"e_1_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.adg2132"}],"container-title":["Diabetes Technology &amp; 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