{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T21:32:49Z","timestamp":1786570369219,"version":"build-2736575974"},"reference-count":34,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2023,7,12]],"date-time":"2023-07-12T00:00:00Z","timestamp":1689120000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Diabetes Metabolism Res"],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Glucose management indicator (GMI) is a core metric derived from continuous glucose monitoring (CGM) and is widely used to evaluate glucose control in patients with diabetes. No study has explored the pregnancy\u2010specific GMI. This study aimed to derive a best\u2010fitting model to calculate GMI from mean blood glucose (MBG) obtained from CGM among pregnant women with type 1 diabetes mellitus (T1DM).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 272 CGM data and corresponding laboratory HbA1c from 98 pregnant women with T1DM in the CARNATION study were analysed in this study. Continuous glucose monitoring data were collected to calculate MBG, time\u2010in\u2010range (TIR), and glycaemic variability parameters. The relationships between the MBG and HbA1c during pregnancy and postpartum were explored. Mix\u2010effect regression analysis with polynomial terms and cross\u2010validation method was conducted to investigate the best\u2010fitting model to calculate GMI from MBG obtained by CGM.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The pregnant women had a mean age of 28.9\u00a0\u00b1\u00a03.8\u00a0years, with a diabetes duration of 8.8\u00a0\u00b1\u00a06.2\u00a0years and a mean body mass index (BMI) of 21.1\u00a0\u00b1\u00a02.5\u00a0kg\/m\n                      <jats:sup>2<\/jats:sup>\n                      . The HbA1c levels were 6.1\u00a0\u00b1\u00a01.0% and 6.4\u00a0\u00b1\u00a01.0% during pregnancy and at postpartum (\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0=\u00a00.024). The MBG levels were lower during pregnancy than those at postpartum (6.5\u00a0\u00b1\u00a01.1\u00a0mmol\/L vs. 7.1\u00a0\u00b1\u00a01.5\u00a0mmol\/L,\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0=\u00a00.008). After adjusting the confounders of haemoglobin (Hb), BMI, trimesters, disease duration, mean amplitude of glycaemic excursions and CV%, we developed a pregnancy\u2010specific GMI\u2010MBG equation: GMI for pregnancy (%)\u00a0=\u00a00.84\u20130.28* [Trimester] + 0.08 * [ BMI in kg\/m\n                      <jats:sup>2<\/jats:sup>\n                      ] + 0.01 * [Hb in g\/mL] + 0.50 * [MBG in mmol\/L].\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We derived a pregnancy\u2010specific GMI equation, which should be recommended for antenatal clinical care.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Clinical trial registry number<\/jats:title>\n                    <jats:p>ChiCTR1900025955.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/dmrr.3689","type":"journal-article","created":{"date-parts":[[2023,7,12]],"date-time":"2023-07-12T05:04:00Z","timestamp":1689138240000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A pregnancy\u2010specific Glucose management indicator derived from continuous glucose monitoring in pregnant women with type 1 diabetes"],"prefix":"10.1002","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9889-5812","authenticated-orcid":false,"given":"Ping","family":"Ling","sequence":"first","affiliation":[{"name":"Department of Endocrinology and Metabolism The Third Affiliated Hospital of Sun Yat\u2010sen University Guangdong Provincial Key Laboratory of Diabetology Sun Yat\u2010Sen University  Guangzhou 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Endocrinology Institute of Endocrine and Metabolic Disease The First Affiliated Hospital of USTC Division of Life Sciences and Medicine Clinical Research Hospital of Chinese Academy of Sciences (Hefei) University of Science and Technology of China  Hefei China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8503-0310","authenticated-orcid":false,"given":"Sihui","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Endocrinology Institute of Endocrine and Metabolic Disease The First Affiliated Hospital of USTC Division of Life Sciences and Medicine Clinical Research Hospital of Chinese Academy of Sciences (Hefei) University of Science and Technology of China  Hefei China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7596-5670","authenticated-orcid":false,"given":"Xubin","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Endocrinology and 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