{"title":"1229-P： 血液糖化白蛋白或果糖胺（GA/Fruc）而非血红蛋白 A1c（A1C）有助于鉴别巨型婴儿个体--Meta 分析","authors":"SATORU KODAMA, TAKAHO YAMADA, NORIKO YAGYUDA, KAZUYA FUJIHARA, LAY MON KHIN, MASARU KITAZAWA, MASAHIKO YAMAMOTO, YASUHIRO MATSUBAYASHI, KIMINORI KATO, HIROHITO SONE","doi":"10.2337/db24-1229-p","DOIUrl":null,"url":null,"abstract":"Introduction & Objective: Poor glycemic control (GC) increases the risk of various pregnancy complications. Both A1C and GA/Fruc are convenient as they require only one measurement and do not impose fasting. However, GA/Fruc is possibly a better predictor of complications than A1C during pregnancy when GC quickly changes. This meta-analysis compared the predictive ability of pregnancy complications between A1C and GA/Fruc. Methods: We comprehensively searched for studies of prediction of maternal or neonatal adverse outcomes using both A1C and GA/Fruc and for their best cut-off values in each study presenting 2 x 2 data (i.e., true-positive, false-negative, true-negative, and false-positive cases). Results: Of 9 eligible studies, 7 predicted macrosomia and could be meta-analyzed using a hierarchical summary receiver-operating characteristic (HSROC) model. Other complications were impossible to be analyzed because of an insufficient number of data. Pooled specificity (95% confidence interval [CI]) was significantly higher (P=0.02) for GA/Fruc (0.83 [0.70-0.91]) compared with A1C (0.57 [0.35-0.77]) while pooled sensitivity (95% CI) was 0.44 (0.26-0.63) for GA/Fruc and 0.67 (0.50-0.81) for A1C (P for difference, 0.17). Conclusion: Compared with A1C, GA/Fruc is useful for specifying individuals having a macrosomic baby. Disclosure S. Kodama: None. T. Yamada: None. N. Yagyuda: None. K. Fujihara: None. L. Khin: None. M. Kitazawa: None. M. Yamamoto: None. Y. Matsubayashi: None. K. Kato: None. H. Sone: Research Support; Novo Nordisk, Astellas Pharma Inc., Kowa Company, Ltd., Kyowa Kirin Co., Ltd., Eisai Inc., Sumitomo Dainippon Pharma Co., Ltd.","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":null,"pages":null},"PeriodicalIF":6.2000,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"1229-P: Blood Glycated Albumin or Fructosamine (GA/Fruc) Rather Than Hemoglobin A1c (A1C) Is Useful for Specifying Individuals Having a Macrosomic Baby—Meta-analysis\",\"authors\":\"SATORU KODAMA, TAKAHO YAMADA, NORIKO YAGYUDA, KAZUYA FUJIHARA, LAY MON KHIN, MASARU KITAZAWA, MASAHIKO YAMAMOTO, YASUHIRO MATSUBAYASHI, KIMINORI KATO, HIROHITO SONE\",\"doi\":\"10.2337/db24-1229-p\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Introduction & Objective: Poor glycemic control (GC) increases the risk of various pregnancy complications. Both A1C and GA/Fruc are convenient as they require only one measurement and do not impose fasting. However, GA/Fruc is possibly a better predictor of complications than A1C during pregnancy when GC quickly changes. This meta-analysis compared the predictive ability of pregnancy complications between A1C and GA/Fruc. Methods: We comprehensively searched for studies of prediction of maternal or neonatal adverse outcomes using both A1C and GA/Fruc and for their best cut-off values in each study presenting 2 x 2 data (i.e., true-positive, false-negative, true-negative, and false-positive cases). Results: Of 9 eligible studies, 7 predicted macrosomia and could be meta-analyzed using a hierarchical summary receiver-operating characteristic (HSROC) model. Other complications were impossible to be analyzed because of an insufficient number of data. Pooled specificity (95% confidence interval [CI]) was significantly higher (P=0.02) for GA/Fruc (0.83 [0.70-0.91]) compared with A1C (0.57 [0.35-0.77]) while pooled sensitivity (95% CI) was 0.44 (0.26-0.63) for GA/Fruc and 0.67 (0.50-0.81) for A1C (P for difference, 0.17). Conclusion: Compared with A1C, GA/Fruc is useful for specifying individuals having a macrosomic baby. Disclosure S. Kodama: None. T. Yamada: None. N. Yagyuda: None. K. Fujihara: None. L. Khin: None. M. Kitazawa: None. M. Yamamoto: None. Y. Matsubayashi: None. K. Kato: None. H. Sone: Research Support; Novo Nordisk, Astellas Pharma Inc., Kowa Company, Ltd., Kyowa Kirin Co., Ltd., Eisai Inc., Sumitomo Dainippon Pharma Co., Ltd.\",\"PeriodicalId\":11376,\"journal\":{\"name\":\"Diabetes\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2024-07-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Diabetes\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2337/db24-1229-p\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2337/db24-1229-p","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
1229-P: Blood Glycated Albumin or Fructosamine (GA/Fruc) Rather Than Hemoglobin A1c (A1C) Is Useful for Specifying Individuals Having a Macrosomic Baby—Meta-analysis
Introduction & Objective: Poor glycemic control (GC) increases the risk of various pregnancy complications. Both A1C and GA/Fruc are convenient as they require only one measurement and do not impose fasting. However, GA/Fruc is possibly a better predictor of complications than A1C during pregnancy when GC quickly changes. This meta-analysis compared the predictive ability of pregnancy complications between A1C and GA/Fruc. Methods: We comprehensively searched for studies of prediction of maternal or neonatal adverse outcomes using both A1C and GA/Fruc and for their best cut-off values in each study presenting 2 x 2 data (i.e., true-positive, false-negative, true-negative, and false-positive cases). Results: Of 9 eligible studies, 7 predicted macrosomia and could be meta-analyzed using a hierarchical summary receiver-operating characteristic (HSROC) model. Other complications were impossible to be analyzed because of an insufficient number of data. Pooled specificity (95% confidence interval [CI]) was significantly higher (P=0.02) for GA/Fruc (0.83 [0.70-0.91]) compared with A1C (0.57 [0.35-0.77]) while pooled sensitivity (95% CI) was 0.44 (0.26-0.63) for GA/Fruc and 0.67 (0.50-0.81) for A1C (P for difference, 0.17). Conclusion: Compared with A1C, GA/Fruc is useful for specifying individuals having a macrosomic baby. Disclosure S. Kodama: None. T. Yamada: None. N. Yagyuda: None. K. Fujihara: None. L. Khin: None. M. Kitazawa: None. M. Yamamoto: None. Y. Matsubayashi: None. K. Kato: None. H. Sone: Research Support; Novo Nordisk, Astellas Pharma Inc., Kowa Company, Ltd., Kyowa Kirin Co., Ltd., Eisai Inc., Sumitomo Dainippon Pharma Co., Ltd.
期刊介绍：
Diabetes is a scientific journal that publishes original research exploring the physiological and pathophysiological aspects of diabetes mellitus. We encourage submissions of manuscripts pertaining to laboratory, animal, or human research, covering a wide range of topics. Our primary focus is on investigative reports investigating various aspects such as the development and progression of diabetes, along with its associated complications. We also welcome studies delving into normal and pathological pancreatic islet function and intermediary metabolism, as well as exploring the mechanisms of drug and hormone action from a pharmacological perspective. Additionally, we encourage submissions that delve into the biochemical and molecular aspects of both normal and abnormal biological processes.
However, it is important to note that we do not publish studies relating to diabetes education or the application of accepted therapeutic and diagnostic approaches to patients with diabetes mellitus. Our aim is to provide a platform for research that contributes to advancing our understanding of the underlying mechanisms and processes of diabetes.
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