{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T13:38:25Z","timestamp":1777556305797,"version":"3.51.4"},"reference-count":33,"publisher":"SAGE Publications","issue":"12","license":[{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"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":[[2024,12]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>: To analyze the Glycemic Risk Index (GRI) and assess their possible differences according to coefficient of variation (CV) in a cohort of real-life type 1 diabetes mellitus (DM) patient users of intermittently scanned continuous glucose monitoring (isCGM).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Patients and Methods<\/jats:title>\n                    <jats:p>: In total, 447 adult users of isCGM with an adherence \u226570% were included in a cross-sectional study. GRI was calculated with its hypoglycemia (CHypo) and hyperglycemia (CHyper) components. Multivariate linear regression analysis was performed to evaluate the factors associated with GRI.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      Mean age was 44.6 years (standard deviation [SD] 13.7), 57.7% being male; age of DM onset was 24.5 years (SD 14.3) and time of evolution was 20.6 years (SD 12.3). In patients with CV &gt;36% (52.8%) versus CV \u226436% (47.2%), differences were observed in relation to GRI (18.8% [SD 1.9];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt; 0.001), CHypo (2.9% [SD 0.3];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt; 0.001), CHyper (6.3% [SD 1.4];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt; 0.001), and all classical glucometric parameters except time above range level 1. The variables that were independently associated with GRI in patient with CV &gt;36% were time in range (TIR) (\u03b2 = \u22121.49; confidence interval [CI:] 95% \u22121.63 to \u22121.37;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt; 0.001), glucose management indicator (GMI) (\u03b2 = \u22127.22; CI: 95% \u22129.53 to \u22124.91;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt; 0.001), and CV (\u03b2 = 0.85; CI: 95% 0.69 to 1.02;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt; 0.001). However, in patients with CV \u226436%, the variables were age (\u03b2 = 0.15; CI: 95% 0.03 to 0.28;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      = 0.019), age of onset (\u03b2 = \u22120.15; CI: 95% \u22120.28 to \u22120.02;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      = 0.023), TIR (\u03b2 = \u22121.35; CI: 95% \u22121.46 to \u22121.23;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt; 0.001), GMI (\u03b2 = \u22126.67; CI: 95% \u22129.18 to \u22124.15;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt; 0.001), and CV (\u03b2 = 0.33; CI: 95% 0.11 to 0.56;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      = 0.004).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>In this study, the factors independently associated with metabolic control according to GRI are modified by glycemic variability.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1089\/dia.2024.0181","type":"journal-article","created":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T16:19:36Z","timestamp":1719850776000},"page":"960-967","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":4,"title":["Glycemic Risk Index in a Cohort of Patients with Type 1 Diabetes Mellitus Stratified by the Coefficient of Variation: A Real-Life Study"],"prefix":"10.1177","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4601-7997","authenticated-orcid":false,"given":"Sandra","family":"Herranz-Antol\u00edn","sequence":"first","affiliation":[{"name":"Endocrinology and Nutrition Department, University Hospital of Guadalajara, Guadalajara, Spain."},{"name":"Institute for Health Research of Castilla la Mancha (IDISCAM), Guadalajara, Spain."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Clara","family":"Coton-Batres","sequence":"additional","affiliation":[{"name":"Nephrology Department, University Hospital of Guadalajara, Guadalajara, Spain."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mar\u00eda Covadonga","family":"L\u00f3pez-Virgos","sequence":"additional","affiliation":[{"name":"Internal Medicine Department, University Hospital of Guadalajara, Guadalajara, Spain."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ver\u00f3nica","family":"Esteban-Monge","sequence":"additional","affiliation":[{"name":"Internal Medicine Department, University Hospital of Guadalajara, Guadalajara, Spain."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Visitaci\u00f3n","family":"\u00c1lvarez-de Frutos","sequence":"additional","affiliation":[{"name":"Endocrinology and Nutrition Department, University Hospital of Guadalajara, Guadalajara, Spain."},{"name":"Department of Medicine and Medical Specialties, University of Alcal\u00e1, Alcal\u00e1 de Henares, Spain."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leonel","family":"Pekarek","sequence":"additional","affiliation":[{"name":"Department of Medicine and Medical Specialties, University of Alcal\u00e1, Alcal\u00e1 de Henares, Spain."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miguel","family":"Torralba","sequence":"additional","affiliation":[{"name":"Institute for Health Research of Castilla la Mancha (IDISCAM), Guadalajara, Spain."},{"name":"Internal Medicine Department, University Hospital of Guadalajara, Guadalajara, Spain."},{"name":"Department of Medicine and Medical Specialties, University of Alcal\u00e1, Alcal\u00e1 de Henares, Spain."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2024,12,13]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.34172\/hpp.2020.18"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00125-019-4894-1"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1097\/XCE.0000000000000216"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13300-022-01253-9"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1177\/14791641211067418"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmjdrc-2019-001052"},{"issue":"5","key":"e_1_3_2_8_2","first-page":"345","article-title":"Impact of flash glucose monitoring on quality of life and glycaemic control parameters in adults with type 1 diabetes mellitus","volume":"69","author":"Jim\u00e9nez-Sahag\u00fan R","year":"2022","unstructured":"Jim\u00e9nez-Sahag\u00fan R, , G\u00f3mez Hoyos E, , D\u00edaz Soto G, et al. 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The relationship between glycosylated hemoglobin, time-in-range and glycemic variability in type 1 diabetes patients under flash glucose monitoring. 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