Abstract
Background
Maternal hyperglycemia, obesity, and hypertension with gestational diabetes mellitus (GDM) are risk factors for infant complications. This study aimed to investigate maternal factors and glycemic control indicators that affect infant complications in GDM.
Methods
We conducted a retrospective cohort study including 112 mothers with GDM and their infants. Multivariate logistic regression analysis was used to investigate the variables associated with good and adverse infant outcomes. We determined the cutoff values of variables that showed a significant difference in the multivariate logistic regression analysis for predicting infant complications by performing receiver operating characteristic curve analysis.
Results
In the multivariate logistic regression analysis, prepregnancy BMI and GA in the third trimester were significantly related to good and adverse infant outcomes (adjusted odds ratios [aORs], 1.62; 95% CIs 1.17–2.25, p = 0.003 and aORs, 2.77; 95% CIs 1.15–6.64, p = 0.022, respectively). The cutoff values for prepregnancy BMI and GA in the third trimester were 25.3 kg/m2 and 13.5%, respectively.
Conclusions
The importance of weight control before pregnancy and the usefulness of GA in the third trimester to predict infant complications were suggested in this study.
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Data availability
All data generated or analyzed during this study are included in this published article. The data are not publicly available due to ethical restrictions. However, the datasets are available from the corresponding author on reasonable request.
References
Buchanan TA, Kitzmiller JL. Metabolic interactions of diabetes and pregnancy. Annu Rev Med. 1994;45:245–60.
American Diabetes Association. Glycemic targets: standards of medical care in diabetes. Diabet Care. 2020;43:66–76.
Shimizu I, Hiramatsu Y, Omori Y, Nakabayashi M, J.G.A. (Japan Glycated Albumin) Study Group. Comparison of HbA1c and glycated albumin as a control marker for newborn complications in diabetic women in a multicentre study in Japan (Japan glycated albumin study group: study 2). Ann Clin Biochem. 2018;55:639–46.
Zhang X, Wei Y, Fan L, Zhao Y, Li Y, Liu Y, et al. A multicenter all-inclusive prospective study on the relationship between glycemic control markers and maternal and neonatal outcomes in pregnant women. J Matern Fetal Neonatal Med. 2021;34:3154–61.
Kohzuma T, Tao X, Koga M. Glycated albumin as biomarker: evidence and its outcomes. J Diabetes Complications. 2021;35:108040.
Shimizu I, Kohzuma T, Koga M. A proposed glycemic control marker for the future: glycated albumin. J Lab Precis Med. 2019;4:23.
Li HP, Wang FH, Tao MF, Huang YJ, Jia WP. Association between glycemic control and birthweight with glycated albumin in Chinese women with gestational diabetes mellitus. J Diabetes Investig. 2016;7:48–55.
Yasuda S, Iuchi T, Goto A, Katanoda K, Iida S, Oikawa Y, et al. Weight control before and during pregnancy for patients with gestational diabetes mellitus. J Diabetes Investig. 2019;10:1075–82.
Khoury JC, Miodovnik M, LeMasters G, Sibai B. Pregnancy outcome and progression of diabetic nephropathy. What’s next? J Matern Fetal Neonatal Med. 2002;11:238–44.
Usami T, Yokoyama M, Ueno M, Iwama N, Sagawa N, Kawano R, et al. Comparison of pregnancy outcomes between women with early-onset and late-onset gestational diabetes in a retrospective multi-institutional study in Japan. J Diabetes Investig. 2020;11:216–22.
International Association of Diabetes and Pregnancy Study Groups Consensus Panel, Metzger BE, Gabbe SG, Persson B, Buchanan TA, Catalano PA, et al. International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes Care. 2010;33:676–82.
Watanabe K, Matsubara K, Nakamoto O, Ushijima J, Ohkuchi A, Koide K, et al. Outline of the new definition and classification of “hypertensive disorders of pregnancy (HDP)”; a revised JSSHP statement of 2005. Hypertens Res Pregnancy. 2018;6:33–7.
Kohzuma T, Yamamoto T, Uematsu Y, Shihabi ZK, Freedman BI. Basic performance of an enzymatic method for glycated albumin and reference range determination. J Diabetes Sci Technol. 2011;5:1455–62.
Kanda Y. Investigation of the freely available easy-to-use software “EZR” for medical statistics. Bone Marrow Transpl. 2013;48:452–8.
Gul R, Iqbal S, Anwar Z, Ahdi SG, Ali SH, Pirzada S. Pre-pregnancy maternal BMI as predictor of neonatal birth weight. PLoS ONE. 2020;15:e0240748.
Schaefer-Graf UM, Graf K, Kulbacka I, Kjos SL, Dudenhausen J, Vetter K, et al. Maternal lipids as strong determinants of fetal environment and growth in pregnancies with gestational diabetes mellitus. Diabetes Care. 2008;31:1858–63.
Catalano PM, Hauguel-De Mouzon S. Is it time to revisit the Pedersen hypothesis in the face of the obesity epidemic? Am J Obstet Gynecol. 2011;204:479–87.
Lepercq J, Le Ray C, Godefroy C, Pelage L, Dubois-Laforgue D, Timsit J. Determinants of a good perinatal outcome in 588 pregnancies in women with type 1 diabetes. Diabetes Metab. 2019;45:191–6.
K.M. Rasmussen, A.L. Yaktine, 2009 Institute of Medicine. (US) and National Research Council (US). Committee to reexamine IOM pregnancy weight guidelines. Weight gain during pregnancy: reexamining the guidelines. National Academies Press, Washington (DC). US.
Mendes N, Alves M, Andrade R, Ribeiro RT, Papoila AL, Serrano F. Association between glycated albumin, fructosamine, and HbA1c with neonatal outcomes in a prospective cohort of women with gestational diabetes mellitus. Int J Gynaecol Obstet. 2019;146:326–32.
Hughes RC, Rowan J, Florkowski CM. Is there a role for HbA1c in pregnancy? Curr Diab Rep. 2016;16:5.
Hashimoto K, Osugi T, Noguchi S, Morimoto Y, Wasada K, Imai S, et al. A1C but not serum glycated albumin is elevated because of iron deficiency in late pregnancy in diabetic women. Diabetes Care. 2010;33:509–11.
Koga M. Glycated albumin; clinical usefulness. Clin Chim Acta. 2014;433:96–104.
Koga M, Hirata T, Kasayama S, Ishizaka Y, Yamakado M. Body mass index negatively regulates glycated albumin through insulin secretion in patients with type 2 diabetes mellitus. Clin Chim Acta. 2015;438:19–23.
Huh JH, Kim KJ, Lee BW, Kim DW, Kang ES, Cha BS, et al. The relationship between BMI and glycated albumin to glycated hemoglobin (GA/A1c) ratio according to glucose tolerance status. PLoS ONE. 2014;9:e89478.
Sonagra AD, Biradar SM, Murthy DKJ. Normal pregnancy- a state of insulin resistance. J Clin Diagn Res. 2014;8:01–3.
Sameshima H, Kamitomo M, Kajiya S, Kai M, Furukawa S, Ikenoue S. Early glycemic control reduces large-for-gestational-age infants in 250 Japanese gestational diabetes pregnancies. Am J Perinatol. 2000;17:371–6.
Hay WW. Care of the infant of the diabetic mother. Curr Diab Rep. 2012;12:4–15.
Hiramatsu Y, Shimizu I, Omori Y, Nakabayashi M. Determination of reference intervals of glycated albumin and hemoglobin A1c in healthy pregnant Japanese women and analysis of their time courses and influencing factors during pregnancy. Endocr J. 2012;59:145–51.
Yu F, Lv L, Liang Z, Wang Y, Wen J, Lin X, et al. Continuous glucose monitoring effects on maternal glycemic control and pregnancy outcomes in patients with gestational diabetes mellitus: a prospective cohort study. J Clin Endocrinol Metab. 2014;99:4674–82.
Suwa T, Ohta A, Matsui T, Koganei R, Kato H, Kawata T, et al. Relationship between clinical markers of glycemia and glucose excursion evaluated by continuous glucose monitoring (CGM). Endocr J. 2010;57:135–40.
Hayashi K, Matsuda Y, Kawamichi Y, Shiozaki A, Saito S. Smoking during pregnancy increases risks of various obstetric complications: a case-cohort study of the Japan Perinatal Registry Network database. J Epidemiol. 2011;21:61–6.
Olson CM, Strawderman MS. Modifiable behavioral factors in a biopsychosocial model predict inadequate and excessive gestational weight gain. J Am Diet Assoc. 2003;103:48–54.
Zhou Q, Shi DB, Lv LY. The establishment of biological reference intervals of nontraditional glycemic markers in a Chinese population. J Clin Lab Anal. 2017;31:e22097.
Selvin E, Warren B, He X, Sacks DB, Saenger AK. Establishment of community-based reference intervals for fructosamine, glycated albumin, and 1,5-anhydroglucitol. Clin Chem. 2018;64:843–50.
Acknowledgements
The authors are grateful to the staff of our facility for their support. We thank American Journal Experts (AJE) for English language editing.
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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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DS Conceptualization, Investigation, Methodology, Formal analysis, Writing-Original draft, Writing–Review & Editing. EM Investigation, Methodology, Formal analysis, Writing–Review & Editing. MM Investigation, Data curation, Formal analysis. HS Conceptualization, Methodology, Writing–Review & Editing. TK Conceptualization, Supervision, Writing–Review & Editing. KI Writing–Review & Editing, Project administration.
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This study was performed in accordance with the principles of the Declaration of Helsinki and was approved by the ethics board of Saitama Medical Center Jichi Medical University (approval no. S20-070, Aug 27. 2020). An opt-out consent form was published on the website of Saitama Medical Center Jichi Medical University. This study was exempted from the requirement for written informed consent because of its retrospective design and the fact that participants chose to participate in the study by not opting out on the Saitama Medical Center Jichi Medical University webpage, which implied their tacit consent to participate in this study. None of the participants opted out of this study.
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Sugawara, D., Makita, E., Matsuura, M. et al. Prepregnancy body mass index and glycated albumin in the third trimester may predict infant complications in gestational diabetes mellitus: a retrospective cohort study. Diabetol Int 14, 280–287 (2023). https://doi.org/10.1007/s13340-023-00631-3
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DOI: https://doi.org/10.1007/s13340-023-00631-3