{"title":"预测胰岛素治疗糖尿病妇女新生儿不良结局的风险:现在是制定妊娠特异性血糖风险指数 (GRI) 的时候了吗?","authors":"Fabrizia Citro, Cristina Bianchi, Tommaso Belcari, Federico Galleano, Caterina Venturi, Lorella Battini, Piero Marchetti, Alessandra Bertolotto, Michele Aragona","doi":"10.1177/19322968241289957","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The Glycemia Risk Index (GRI) describes the quality of glycemic control, emphasizing extreme hypoglycemia and hyperglycemia more than less extreme values. However, a pregnancy-specific GRI (pGRI), tailored to the tighter target glucose range required during pregnancy, has not been established.</p><p><strong>Methods: </strong>We retrospectively evaluated clinical, metabolic, and Continuous Glucose Monitoring (CGM) data across pregnancy in women with insulin-treated diabetes, managed between September 2021 and March 2024 at the University Hospital of Pisa. First and second levels of hyperglycemia (TAR1: 140-180 mg/dL, TAR2: >180 mg/dL) and hypoglycemia (TBR1: 63-54 mg/dL, TBR2: <54 mg/dL) were used to calculate the pGRI at each trimester. Logistic regression analysis investigated the association between pGRI and risk of at least one adverse neonatal outcome (among preterm delivery, macrosomia, large for gestational age, small for gestational age, neonatal hypoglycemia, neonatal jaundice, and neonatal intensive care unit admission).</p><p><strong>Results: </strong>Of 45 pregnant women, 25 (56%) experienced at least one adverse neonatal outcome. In the third trimester, women with adverse outcomes had significantly higher total TAR (26 [12-32]% vs 10 [4-23]%, <i>P</i> = .018) and lower TIR (71 [64-83]% vs 88 [75-92]%, <i>P</i> = .007). Specifically, the difference was notable in TAR2 (6 [2-15]% vs 1 [0-4]%, <i>P</i> = .004), whereas TAR1 was comparable between the 2 groups. Accordingly, third trimester pGRI was higher in women with adverse neonatal outcomes (38 [18-49]% vs 18 [10-31]%, <i>P</i> = .013) and, at logistic regression, slightly but significantly increased the risk of adverse neonatal outcomes (1.044 [1.004-1.086], <i>P</i> = .024).</p><p><strong>Conclusions: </strong>Pregnant women with insulin-treated diabetes reporting adverse neonatal outcomes spent more time in hyperglycemia, particularly in extreme hyperglycemia. Therefore, the level of hyperglycemia should always be assessed during pregnancy. The pGRI, emphasizing extreme hyperglycemia, may be a novel comprehensive tool for assessing the risk of adverse neonatal outcomes.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241289957"},"PeriodicalIF":4.1000,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571631/pdf/","citationCount":"0","resultStr":"{\"title\":\"Predicting the Risk of Adverse Neonatal Outcomes in Women With Insulin-Treated Diabetes: Is It Time for a Pregnancy-Specific Glycemic Risk Index (GRI)?\",\"authors\":\"Fabrizia Citro, Cristina Bianchi, Tommaso Belcari, Federico Galleano, Caterina Venturi, Lorella Battini, Piero Marchetti, Alessandra Bertolotto, Michele Aragona\",\"doi\":\"10.1177/19322968241289957\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The Glycemia Risk Index (GRI) describes the quality of glycemic control, emphasizing extreme hypoglycemia and hyperglycemia more than less extreme values. However, a pregnancy-specific GRI (pGRI), tailored to the tighter target glucose range required during pregnancy, has not been established.</p><p><strong>Methods: </strong>We retrospectively evaluated clinical, metabolic, and Continuous Glucose Monitoring (CGM) data across pregnancy in women with insulin-treated diabetes, managed between September 2021 and March 2024 at the University Hospital of Pisa. First and second levels of hyperglycemia (TAR1: 140-180 mg/dL, TAR2: >180 mg/dL) and hypoglycemia (TBR1: 63-54 mg/dL, TBR2: <54 mg/dL) were used to calculate the pGRI at each trimester. Logistic regression analysis investigated the association between pGRI and risk of at least one adverse neonatal outcome (among preterm delivery, macrosomia, large for gestational age, small for gestational age, neonatal hypoglycemia, neonatal jaundice, and neonatal intensive care unit admission).</p><p><strong>Results: </strong>Of 45 pregnant women, 25 (56%) experienced at least one adverse neonatal outcome. In the third trimester, women with adverse outcomes had significantly higher total TAR (26 [12-32]% vs 10 [4-23]%, <i>P</i> = .018) and lower TIR (71 [64-83]% vs 88 [75-92]%, <i>P</i> = .007). Specifically, the difference was notable in TAR2 (6 [2-15]% vs 1 [0-4]%, <i>P</i> = .004), whereas TAR1 was comparable between the 2 groups. Accordingly, third trimester pGRI was higher in women with adverse neonatal outcomes (38 [18-49]% vs 18 [10-31]%, <i>P</i> = .013) and, at logistic regression, slightly but significantly increased the risk of adverse neonatal outcomes (1.044 [1.004-1.086], <i>P</i> = .024).</p><p><strong>Conclusions: </strong>Pregnant women with insulin-treated diabetes reporting adverse neonatal outcomes spent more time in hyperglycemia, particularly in extreme hyperglycemia. Therefore, the level of hyperglycemia should always be assessed during pregnancy. The pGRI, emphasizing extreme hyperglycemia, may be a novel comprehensive tool for assessing the risk of adverse neonatal outcomes.</p>\",\"PeriodicalId\":15475,\"journal\":{\"name\":\"Journal of Diabetes Science and Technology\",\"volume\":\" \",\"pages\":\"19322968241289957\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2024-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571631/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Diabetes Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/19322968241289957\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Diabetes Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/19322968241289957","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
摘要
背景:血糖风险指数(GRI)描述了血糖控制的质量,与不太极端的血糖值相比,它更强调极端低血糖和高血糖。然而,针对妊娠期更严格的目标血糖范围而定制的妊娠特异性血糖风险指数(pGRI)尚未建立:我们回顾性地评估了 2021 年 9 月至 2024 年 3 月期间在比萨大学医院接受治疗的胰岛素治疗糖尿病妇女在整个孕期的临床、代谢和连续血糖监测(CGM)数据。结果:在 45 名孕妇中,25 人(56%)至少出现过一次新生儿不良结局。在第三孕期,出现不良结果的孕妇的总 TAR 明显更高(26 [12-32]% vs 10 [4-23]%,P = .018),TIR 明显更低(71 [64-83]% vs 88 [75-92]%,P = .007)。具体而言,TAR2(6 [2-15]% vs 1 [0-4]%,P = .004)差异显著,而 TAR1 在两组之间不相上下。因此,在新生儿不良预后的妇女中,第三孕期 pGRI 较高(38 [18-49]% vs 18 [10-31]%,P = .013),并且在逻辑回归中,pGRI 会轻微但显著地增加新生儿不良预后的风险(1.044 [1.004-1.086],P = .024):结论:接受胰岛素治疗的糖尿病孕妇出现不良新生儿结局的时间较长,尤其是极度高血糖。因此,在妊娠期间应始终对高血糖水平进行评估。强调极度高血糖的 pGRI 可能是评估新生儿不良结局风险的一种新型综合工具。
Predicting the Risk of Adverse Neonatal Outcomes in Women With Insulin-Treated Diabetes: Is It Time for a Pregnancy-Specific Glycemic Risk Index (GRI)?
Background: The Glycemia Risk Index (GRI) describes the quality of glycemic control, emphasizing extreme hypoglycemia and hyperglycemia more than less extreme values. However, a pregnancy-specific GRI (pGRI), tailored to the tighter target glucose range required during pregnancy, has not been established.
Methods: We retrospectively evaluated clinical, metabolic, and Continuous Glucose Monitoring (CGM) data across pregnancy in women with insulin-treated diabetes, managed between September 2021 and March 2024 at the University Hospital of Pisa. First and second levels of hyperglycemia (TAR1: 140-180 mg/dL, TAR2: >180 mg/dL) and hypoglycemia (TBR1: 63-54 mg/dL, TBR2: <54 mg/dL) were used to calculate the pGRI at each trimester. Logistic regression analysis investigated the association between pGRI and risk of at least one adverse neonatal outcome (among preterm delivery, macrosomia, large for gestational age, small for gestational age, neonatal hypoglycemia, neonatal jaundice, and neonatal intensive care unit admission).
Results: Of 45 pregnant women, 25 (56%) experienced at least one adverse neonatal outcome. In the third trimester, women with adverse outcomes had significantly higher total TAR (26 [12-32]% vs 10 [4-23]%, P = .018) and lower TIR (71 [64-83]% vs 88 [75-92]%, P = .007). Specifically, the difference was notable in TAR2 (6 [2-15]% vs 1 [0-4]%, P = .004), whereas TAR1 was comparable between the 2 groups. Accordingly, third trimester pGRI was higher in women with adverse neonatal outcomes (38 [18-49]% vs 18 [10-31]%, P = .013) and, at logistic regression, slightly but significantly increased the risk of adverse neonatal outcomes (1.044 [1.004-1.086], P = .024).
Conclusions: Pregnant women with insulin-treated diabetes reporting adverse neonatal outcomes spent more time in hyperglycemia, particularly in extreme hyperglycemia. Therefore, the level of hyperglycemia should always be assessed during pregnancy. The pGRI, emphasizing extreme hyperglycemia, may be a novel comprehensive tool for assessing the risk of adverse neonatal outcomes.
期刊介绍:
The Journal of Diabetes Science and Technology (JDST) is a bi-monthly, peer-reviewed scientific journal published by the Diabetes Technology Society. JDST covers scientific and clinical aspects of diabetes technology including glucose monitoring, insulin and metabolic peptide delivery, the artificial pancreas, digital health, precision medicine, social media, cybersecurity, software for modeling, physiologic monitoring, technology for managing obesity, and diagnostic tests of glycation. The journal also covers the development and use of mobile applications and wireless communication, as well as bioengineered tools such as MEMS, new biomaterials, and nanotechnology to develop new sensors. Articles in JDST cover both basic research and clinical applications of technologies being developed to help people with diabetes.