{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T05:09:31Z","timestamp":1778130571438,"version":"3.51.4"},"reference-count":24,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,11,27]],"date-time":"2023-11-27T00:00:00Z","timestamp":1701043200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,11,27]],"date-time":"2023-11-27T00:00:00Z","timestamp":1701043200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Diabetol Metab Syndr"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background\/ objective<\/jats:title>\n                <jats:p>To evaluate the association of CGM parameters and HbA1c with diabetes complications in patients with Type 1 Diabetes (T1D).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>Patients with T1D using the CGM system Freestyle Libre were included in this analysis. The association of CGM-metrics and HbA1c with diabetes complications (any complication, microvascular complications, or macrovascular complications) was assessed using logistic regression unadjusted and adjusted for age, sex, and diabetes duration (model 1), and further adjusted for hypertension and dyslipidemia (model 2).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>One hundred and sixty-one patients with T1D were included. The mean (\u00b1\u2009SD) age was 37.4\u2009\u00b1\u200913.4 years old and the median T1D duration was 17.7\u2009\u00b1\u200910.6 years. Time in range (TIR) was associated with any complication and microvascular complications in the unadjusted model and in the adjusted models. TIR was associated with retinopathy in the unadjusted model as well as in model 1, and was associated with macrovascular complications only in the unadjusted model. HbA1c was associated with any complications, microvascular complications, and retinopathy in the unadjusted model but not in the adjusted models. HbA1c was associated with macrovascular complications in the unadjusted model and in the adjusted model 1.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>In this cross-sectional analysis of patients with T1D using intermittent scanned CGM, TIR, and HbA1c were associated with complications of diabetes. TIR may be a better predictor than HbA1c of any complication and microvascular complications, while HbA1c may be a better predictor of macrovascular complications.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s13098-023-01219-2","type":"journal-article","created":{"date-parts":[[2023,11,27]],"date-time":"2023-11-27T03:01:42Z","timestamp":1701054102000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Time in range and complications of diabetes: a cross-sectional analysis of patients with Type 1 diabetes"],"prefix":"10.1186","volume":"15","author":[{"given":"Marta Fernandes","family":"Bezerra","sequence":"first","affiliation":[]},{"given":"Celestino","family":"Neves","sequence":"additional","affiliation":[]},{"given":"Jo\u00e3o S\u00e9rgio","family":"Neves","sequence":"additional","affiliation":[]},{"given":"Davide","family":"Carvalho","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,11,27]]},"reference":[{"issue":"Suppl 8","key":"1219_CR1","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1055\/s-2006-956282","volume":"131","author":"R Landgraf","year":"2006","unstructured":"Landgraf R. [HbA1c\u2013the gold standard in the assessment of Diabetes treatment?]. Dtsch Med Wochenschr. 2006;131(Suppl 8):243\u20136.","journal-title":"Dtsch Med Wochenschr"},{"issue":"1","key":"1219_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2337\/diacare.10.1.1","volume":"10","author":"Diabetes Control and Complications Trial (DCCT)","year":"1987","unstructured":"Diabetes Control and Complications Trial (DCCT). Results of feasibility study. The DCCT Research Group. Diabetes Care. 1987;10(1):1\u201319.","journal-title":"Diabetes Care"},{"issue":"1","key":"1219_CR3","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1111\/1753-0407.12846","volume":"11","author":"RA Vigersky","year":"2019","unstructured":"Vigersky RA. Going beyond HbA1c to understand the benefits of advanced Diabetes therapies. J Diabetes. 2019;11(1):23\u201331.","journal-title":"J Diabetes"},{"issue":"2","key":"1219_CR4","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/s00592-020-01605-6","volume":"58","author":"S Lee","year":"2021","unstructured":"Lee S, Liu T, Zhou J, Zhang Q, Wong WT, Tse G. Predictions of Diabetes Complications and mortality using hba1c variability: a 10-year observational cohort study. Acta Diabetol. 2021;58(2):171\u201380.","journal-title":"Acta Diabetol"},{"issue":"8","key":"1219_CR5","doi-asserted-by":"publisher","first-page":"968","DOI":"10.2337\/diab.44.8.968","volume":"44","author":"The relationship of","year":"1995","unstructured":"The relationship of. Glycemic exposure (HbA1c) to the risk of development and progression of retinopathy in the Diabetes control and Complications trial. Diabetes. 1995;44(8):968\u201383.","journal-title":"Diabetes"},{"issue":"6","key":"1219_CR6","doi-asserted-by":"publisher","first-page":"393","DOI":"10.3343\/alm.2013.33.6.393","volume":"33","author":"C Weykamp","year":"2013","unstructured":"Weykamp C. HbA1c: a review of analytical and clinical aspects. Ann Lab Med. 2013;33(6):393\u2013400.","journal-title":"Ann Lab Med"},{"issue":"8","key":"1219_CR7","doi-asserted-by":"publisher","first-page":"1299","DOI":"10.2337\/dc15-2727","volume":"39","author":"KJ Welsh","year":"2016","unstructured":"Welsh KJ, Kirkman MS, Sacks DB. Role of Glycated Proteins in the diagnosis and management of Diabetes: research gaps and future directions. Diabetes Care. 2016;39(8):1299\u2013306.","journal-title":"Diabetes Care"},{"issue":"6","key":"1219_CR8","doi-asserted-by":"publisher","first-page":"518","DOI":"10.1016\/j.amjms.2018.09.010","volume":"356","author":"GE Umpierrez","year":"2018","unstructured":"Umpierrez GE. Glycemic variability: how to measure and its clinical implication for type 2 Diabetes. Am J Med Sci. 2018;356(6):518\u201327.","journal-title":"Am J Med Sci"},{"issue":"8","key":"1219_CR9","doi-asserted-by":"publisher","first-page":"1593","DOI":"10.2337\/dci19-0028","volume":"42","author":"T Battelino","year":"2019","unstructured":"Battelino T, Danne T, Bergenstal RM, Amiel SA, Beck R, Biester T, et al. Clinical targets for continuous glucose Monitoring Data Interpretation: recommendations from the International Consensus on Time in Range. Diabetes Care. 2019;42(8):1593\u2013603.","journal-title":"Diabetes Care"},{"issue":"2","key":"1219_CR10","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1007\/s00125-019-05027-0","volume":"63","author":"A Advani","year":"2020","unstructured":"Advani A. Positioning time in range in Diabetes management. Diabetologia. 2020;63(2):242\u201352.","journal-title":"Diabetologia"},{"issue":"S3","key":"1219_CR11","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1089\/dia.2017.0035","volume":"19","author":"D Rodbard","year":"2017","unstructured":"Rodbard D. Continuous glucose monitoring: a review of recent studies demonstrating Improved Glycemic outcomes. Diabetes Technol Ther. 2017;19(S3):25\u2013s37.","journal-title":"Diabetes Technol Ther"},{"issue":"5","key":"1219_CR12","doi-asserted-by":"publisher","first-page":"439","DOI":"10.2337\/cd20-0042","volume":"38","author":"EE Wright Jr","year":"2020","unstructured":"Wright EE Jr., Morgan K, Fu DK, Wilkins N, Guffey WJ. Time in Range: how to measure it, how to report it, and its practical application in clinical decision-making. Clin Diabetes. 2020;38(5):439\u201348.","journal-title":"Clin Diabetes"},{"issue":"2","key":"1219_CR13","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1089\/dia.2018.0310","volume":"21","author":"RA Vigersky","year":"2019","unstructured":"Vigersky RA, McMahon C. The relationship of Hemoglobin A1C to Time-in-range in patients with Diabetes. Diabetes Technol Ther. 2019;21(2):81\u20135.","journal-title":"Diabetes Technol Ther"},{"issue":"7","key":"1219_CR14","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1089\/dia.2020.0236","volume":"22","author":"C Fabris","year":"2020","unstructured":"Fabris C, Heinemann L, Beck R, Cobelli C, Kovatchev B. Estimation of Hemoglobin A1c from Continuous Glucose Monitoring Data in individuals with type 1 Diabetes: is Time in Range all we need? Diabetes Technol Ther. 2020;22(7):501\u20138.","journal-title":"Diabetes Technol Ther"},{"issue":"3","key":"1219_CR15","doi-asserted-by":"publisher","first-page":"400","DOI":"10.2337\/dc18-1444","volume":"42","author":"RW Beck","year":"2019","unstructured":"Beck RW, Bergenstal RM, Riddlesworth TD, Kollman C, Li Z, Brown AS, et al. Validation of Time in Range as an Outcome measure for Diabetes clinical trials. Diabetes Care. 2019;42(3):400\u20135.","journal-title":"Diabetes Care"},{"issue":"6","key":"1219_CR16","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 ME, O\u2019Neal D, Ekinci EI. Complications of Diabetes and Metrics of Glycemic Management Derived from continuous glucose monitoring. J Clin Endocrinol Metab. 2022;107(6):e2221\u2013e36.","journal-title":"J Clin Endocrinol Metab"},{"issue":"11","key":"1219_CR17","doi-asserted-by":"publisher","first-page":"2370","DOI":"10.2337\/dc18-1131","volume":"41","author":"J Lu","year":"2018","unstructured":"Lu J, Ma X, Zhou J, Zhang L, Mo Y, Ying L, et al. Association of Time in Range, as assessed by continuous glucose monitoring, with Diabetic Retinopathy in Type 2 Diabetes. Diabetes Care. 2018;41(11):2370\u20136.","journal-title":"Diabetes Care"},{"issue":"10","key":"1219_CR18","doi-asserted-by":"publisher","first-page":"768","DOI":"10.1089\/dia.2019.0499","volume":"22","author":"JH Yoo","year":"2020","unstructured":"Yoo JH, Choi MS, Ahn J, Park SW, Kim Y, Hur KY, et al. Association between continuous glucose monitoring-derived time in Range, other Core Metrics, and Albuminuria in Type 2 Diabetes. Diabetes Technol Ther. 2020;22(10):768\u201376.","journal-title":"Diabetes Technol Ther"},{"issue":"2","key":"1219_CR19","doi-asserted-by":"publisher","first-page":"e570","DOI":"10.1210\/clinem\/dgab688","volume":"107","author":"A El Malahi","year":"2022","unstructured":"El Malahi A, Van Elsen M, Charleer S, Dirinck E, Ledeganck K, Keymeulen B, et al. Relationship between Time in Range, Glycemic Variability, HbA1c, and Complications in adults with type 1 Diabetes Mellitus. J Clin Endocrinol Metab. 2022;107(2):e570\u2013e81.","journal-title":"J Clin Endocrinol Metab"},{"issue":"6","key":"1219_CR20","doi-asserted-by":"publisher","first-page":"1615","DOI":"10.2337\/diabetes.54.6.1615","volume":"54","author":"M Brownlee","year":"2005","unstructured":"Brownlee M. The pathobiology of diabetic Complications: a unifying mechanism. Diabetes. 2005;54(6):1615\u201325.","journal-title":"Diabetes"},{"issue":"3","key":"1219_CR21","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1016\/j.ecl.2021.05.005","volume":"50","author":"W Crasto","year":"2021","unstructured":"Crasto W, Patel V, Davies MJ, Khunti K. Prevention of Microvascular Complications of Diabetes. Endocrinol Metab Clin North Am. 2021;50(3):431\u201355.","journal-title":"Endocrinol Metab Clin North Am"},{"key":"1219_CR22","doi-asserted-by":"publisher","first-page":"992252","DOI":"10.3389\/fcvm.2022.992252","volume":"9","author":"S Xu","year":"2022","unstructured":"Xu S, Qin Z, Yuan R, Cui X, Zhang L, Bai J, et al. The hemoglobin glycation index predicts the risk of adverse cardiovascular events in coronary Heart Disease patients with type 2 Diabetes Mellitus. Front Cardiovasc Med. 2022;9:992252.","journal-title":"Front Cardiovasc Med"},{"issue":"7","key":"1219_CR23","doi-asserted-by":"publisher","first-page":"108223","DOI":"10.1016\/j.jdiacomp.2022.108223","volume":"36","author":"JM Hempe","year":"2022","unstructured":"Hempe JM, Hsia DS. Variation in the hemoglobin glycation index. J Diabetes Complications. 2022;36(7):108223.","journal-title":"J Diabetes Complications"},{"issue":"3","key":"1219_CR24","doi-asserted-by":"publisher","first-page":"690","DOI":"10.1177\/19322968211069177","volume":"17","author":"SL Cichosz","year":"2023","unstructured":"Cichosz SL, Jensen MH, Hejlesen O. Optimal data Collection Period for continuous glucose monitoring to Assess Long-Term Glycemic Control: Revisited. J Diabetes Sci Technol. 2023;17(3):690\u20135.","journal-title":"J Diabetes Sci Technol"}],"container-title":["Diabetology &amp; Metabolic Syndrome"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13098-023-01219-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13098-023-01219-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13098-023-01219-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,27]],"date-time":"2023-11-27T03:05:37Z","timestamp":1701054337000},"score":1,"resource":{"primary":{"URL":"https:\/\/dmsjournal.biomedcentral.com\/articles\/10.1186\/s13098-023-01219-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,27]]},"references-count":24,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["1219"],"URL":"https:\/\/doi.org\/10.1186\/s13098-023-01219-2","relation":{},"ISSN":["1758-5996"],"issn-type":[{"value":"1758-5996","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,27]]},"assertion":[{"value":"18 June 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 November 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 November 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Approved by the Ethical Committee of CHUSJ.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"The authors report no conflicts of interest.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"244"}}