In November 2025, a large retrospective cohort study published in the Journal of the American Medical Association (JAMA) revealed a finding of great concern to obstetricians: women of childbearing age who stopped glucagon-like peptide-1 receptor agonists (GLP-1RAs) before or in the first trimester had a significant increase in weight gain during pregnancy, and an increased risk of preterm birth, gestational diabetes, and gestational hypertension. The results of this study provide important diagnostic and treatment reference for clinicians, especially for preconception counseling for women of childbearing age with obesity or type 2 diabetes who are using this type of drug.
The use of GLP-1RAs is limited during pregnancy, and the impact of discontinuation is to be resolved GLP-1RAs are commonly used to treat obesity and type 2 diabetes, which can effectively improve glycemic control, weight loss, and improve cardiovascular outcomes, and their use in women of childbearing age has gradually increased in recent years. However, since animal experiments have shown that these drugs may cause fetal structural abnormalities, intrauterine growth restriction, and embryonic and fetal death, they are clearly listed as contraindicated drugs during pregnancy, and clinical practice recommends that women stop taking them before conception or immediately after confirming pregnancy. Previous studies have shown that discontinuation of GLP-1RAs outside of pregnancy can lead to weight regain and worsening of hyperglycemia, but there is limited and controversial data on the effects of pre-pregnancy or first trimester discontinuation on gestational weight gain and pregnancy outcomes, which has also become an important confusion faced by clinicians. Large sample matching analysis focuses on the core outcome The study included 149,790 women with singleton pregnancies who delivered at 15 facilities of the Massachusetts General Hospital Brigham Health System between June 2016 and March 2025, and used a propensity score matching method to match 448 pregnancies (exposed group) with 1344 unexposed pregnancies within 3 years before and 90 days after gestation to balance for potential confounding factors such as age, pre-pregnancy body mass index (BMI), and comorbidities. The primary outcome of the study was gestational weight gain, and secondary outcomes included key pregnancy-related indicators such as excessive gestational weight gain, fetal birth weight percentile, preterm birth, cesarean section, gestational diabetes, and gestational hypertension. When presenting the screening process of research subjects, the original text Figure 1 (derivation process of Gestational Weight Gain and Birth Weight Cohorts) can be inserted to visually show the exclusion and matching process from the initial cohort to the final analysis cohort. Pregnancy weight gain surges after drug discontinuation, and the risk of multiple adverse outcomes increases The data showed that the mean gestational weight gain in the GLP-1RA exposed group reached 13.7 kg (standard deviation 9.2 kg), which was significantly higher than that of the non-exposed group of 10.5 kg (standard deviation 8.0 kg), with a difference of 3.3 kg (95% confidence interval 2.3-4.2 kg, P<0.001). The proportion of excess gestational weight gain in the exposed group was 65%, much higher than that of the unexposed group (hazard ratio 1.32, 95% confidence interval 1.19-1.47). In terms of pregnancy outcomes, the risk of preterm birth (17% vs. 13%, hazard ratio 1.34), gestational diabetes (20% vs. 15%, hazard ratio 1.30), and gestational hypertension (46% vs. 36%, hazard ratio 1.29) were significantly higher in the exposed group than in the unexposed group, and the differences were statistically significant. It is worth noting that no significant differences were observed between the two groups in terms of fetal birth length, incidence of babies greater than or less than gestational age, and cesarean section rate, with the average birth weight percentile (58.4%) in the exposed group slightly higher than that in the unexposed group (54.8%), with a difference of 3.6% (95% confidence interval 0.2%-6.9%). Further analysis showed that 84% of women in the GLP-1RA exposure group were obese, 23% had pregestational diabetes, 21% had chronic hypertension, and most exposed people (66%) were still on record of medication within 6 months before conception, with the main reason for discontinuation of medication being planned or confirmed. Subgroup analysis showed that a similar trend of increasing gestational weight gain was observed in both recent medication (within 6 months before conception) and previous medication, whether using semaglutide or liraglutide, with semaglutide users having a higher weight gain effect, but there was overlap between the two groups. Clinical attention needs to be paid to weight management after drug discontinuation and optimize preconception counseling The results of this study are consistent with the conclusions of previous studies on weight regain after discontinuation of GLP-1RA outside pregnancy, suggesting that women who use this type of drug before pregnancy may gain excess weight during pregnancy due to rapid weight gain after discontinuation, thereby increasing the risk of adverse pregnancy outcomes. Although GLP-1RAs may provide benefits for weight control and improved blood sugar before pregnancy, the rebound effect after discontinuation may negate some of the benefits. This finding provides an important reference for clinicians: for women of childbearing age who are using GLP-1RAs, they need to be fully informed of the risk of increased weight gain and related adverse outcomes during pregnancy consultation after discontinuation of the drug, and develop a targeted weight management plan; For women who are trying to conceive with obesity or diabetes, it is necessary to weigh the short-term benefits of GLP-1RA treatment against the potential risks after discontinuation, and explore better strategies for pre-pregnancy weight and blood glucose management. The study also pointed out its own limitations, including the failure to collect actual drug use, the lack of BMI data before preconception medication, and the limited representation of the study population, and more prospective studies are needed to further validate these findings in the future and explore effective interventions to reduce the risk of adverse pregnancy after drug discontinuation. However, the results of the current study are based on large-sample electronic health records and rigorous propensity score matching analysis, and the results are highly reliable, providing key evidence-based medical evidence for clinical practice. [References] 1. American Diabetes Association. 8.Pharmacologic approaches to glycemic treatment. Diabetes Care. 2017; 40(suppl 1):S64-S74. doi:10.2337/dc17-S011 2. Driscoll AK, Gregory ECW. Increases in prepregnancy obesity: United States, 2016-2019.NCHS Data Brief.2020; (392):1-8. 3. Gorsch LP, Wen T, Lonier JY, et al. Trends in delivery hospitalizations with pregestational and gestational diabetes mellitus and associated outcomes: 2000-2019. Am J Obstet Gynecol. 2023; 229(1):63.e1-63.e14. doi:10.1016/j.ajog.2022.12.006 4. American College of Obstetricians and Gynecologists’ Committee on Practice Bulletins–Obstetrics. ACOG practice bulletin no.201: pregestational diabetes mellitus. Obstet Gynecol.2018; 132(6):e228-e248. doi:10.1097/AOG. 0000000000002960 5. US Food and Drug Administration. Ozempic (semaglutide) highlights of prescribing information. Accessed August 6, 2025.https://www.accessdata. fda.gov/drugsatfda_docs/label/2025/209637s025lbl.pdf 6. US Food and Drug Administration. Mounjaro(tirzepatide) highlights of prescribing information. Accessed August 6, 2025.https://www.accessdata.fda.gov/drugsatfda_docs/label/2025/215866s031lbl.pdf 7. US Food and Drug Administration. Byetta(exenatide) highlights of prescribing information. Accessed August 6, 2025. https://www.accessdata.fda.gov/drugsatfda_docs/label/2025/021773s050lbl.pdf 8. US Food and Drug Administration. Victoza(liraglutide) highlights of prescribing information. Accessed August 6, 2025.https://www.accessdata.fda.gov/drugsatfda_docs/label/2025/022341s044lbl.pdf 9. US Food and Drug Administration. Trulicity(dulaglutide) highlights of prescribing information. Accessed August 6, 2025.https://www.accessdata.fda.gov/drugsatfda_docs/label/2025/125469s063lbl.pdf 10. Obesity in pregnancy: ACOG practice bulletin,number 230. Obstet Gynecol. 2021; 137(6):e128-e144.doi:10.1097/AOG.0000000000004395 11. Cesta CE, Rotem R, Bateman BT, et al. Safety of GLP-1 receptor agonists and other second-line antidiabetics in early pregnancy. JAMA Intern Med.2024; 184(2):144-152. 12. Dao K, Shechtman S, Weber-Schoendorfer C,et al. Use of GLP1 receptor agonists in early pregnancy and reproductive safety: a multicentre,observational, prospective cohort study based on the databases of six Teratology Information Services. BMJ Open. 2024; 14(4):e083550. doi:10.1136/bmjopen-2023-083550 13. Imbroane MR, LeMoine F, Nau CT. Preconception glucagon-like peptide-1 receptor agonist use associated with decreased risk of adverse obstetrical outcomes. Am J Obstet Gynecol.2025; 233(2):116.e1-116.e7.doi:10.1016/j.ajog.2025.01.019 14. Hanif M, Hays AG, Nagarajan JS, Sah SP,Weinstock RS, Taub CC. Efficacy and safety of glucagon-like peptide-1 receptor agonist use during the first trimester in pregnant women with type 2 diabetes. Am J Cardiol. 2025; 246:10-13. doi:10.1016/j.amjcard.2025.03.013 15. Pondugula N, Culhane JF, Lundsberg LS,Partridge C, Merriam AA. Gestational weight gain and hypertensive disorders of pregnancy with prepregnancy and early pregnancy glucagon-like peptide-1 receptor agonist exposure. Obstet Gynecol. Published online July 3, 2025. doi:10.1097/AOG.0000000000005995 16. Wilding JPH, Batterham RL, Davies M, et al; STEP 1 Study Group. Weight regain and cardiometabolic effects after withdrawal of semaglutide: the STEP 1 trial extension. Diabetes Obes Metab. 2022; 24(8):1553-1564. doi:10.1111/dom.14725 17. Rubino D, Abrahamsson N, Davies M, et al; STEP 4 Investigators. Effect of continued weekly subcutaneous semaglutide vs placebo on weight loss maintenance in adults with overweight or obesity: the STEP 4 randomized clinical trial. JAMA. 2021; 325(14):1414-1425. doi:10.1001/jama.2021.3224 18. Vesco KK, Sharma AJ, Dietz PM, et al. Newborn size among obese women with weight gain outside the 2009 Institute of Medicine recommendation. Obstet Gynecol. 2011; 117(4):812-818. doi:10.1097/ AOG.0b013e3182113ae4 19. Champion ML, Harper LM. Gestational weight gain: update on outcomes and interventions. Curr Diab Rep. 2020; 20(3):11. doi:10.1007/s11892-020-1296-1 20. Dude AM, Kominiarek MA, Haas DM, et al. Weight gain in early, mid, and late pregnancy and hypertensive disorders of pregnancy. Pregnancy Hypertens. 2020; 20:50-55. doi:10.1016/j.preghy. 2020.03.001 21. Langford A, Joshu C, Chang JJ, Myles T, Leet T.Does gestational weight gain affect the risk of adverse maternal and infant outcomes in overweight women? Matern Child Health J. 2011; 15(7):860-865. doi:10.1007/s10995-008-0318-4 22. Voerman E, Santos S, Patro Golab B, et al. Maternal body mass index, gestational weight gain, and the risk of overweight and obesity across childhood: an individual participant data meta-analysis. PLoS Med.2019; 16(2):e1002744.doi:10.1371/journal.pmed.1002744 23. von Elm E, Altman DG, Egger M, Pocock SJ,Gøtzsche PC, Vandenbroucke JP; STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med. 2007; 147(8):573-577. doi:10.7326/0003-4819-147-8-200710160-00010 24. Nalichowski R, Keogh D, Chueh HC, Murphy SN. Calculating the benefits of a research patient data repository. AMIA Annu Symp Proc. 2006; 2006:1044. 25. Committee opinion no. 700: methods for estimating the due date. Obstet Gynecol. 2017; 129(5):e150-e154. doi:10.1097/AOG.0000000000002046 26. Rasmussen KM, Yaktine AL, eds; 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; 2009. Accessed November 29, 2023. https://www.ncbi.nlm.nih.gov/books/NBK32813/ 27. Aris IM, Kleinman KP, Belfort MB, Kaimal A, Oken E. A 2017 US reference for singleton birth weight percentiles using obstetric estimates of gestation. Pediatrics. 2019; 144(1):e20190076. doi:10.1542/peds.2019-0076 28. ACOG practice bulletin no. 190: gestational diabetes mellitus. Obstet Gynecol. 2018; 131(2):e49-e64. doi:10.1097/AOG.0000000000002501 29. Gestational hypertension and preeclampsia: ACOG practice bulletin, number 222. Obstet Gynecol. 2020; 135(6):e237-e260. doi:10.1097/AOG.0000000000003891 30. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983; 70(1):41-55. doi:10.1093/biomet/70.1.41 31. Ho DE, Imai K, King G, Stuart EA. Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Polit Anal. 2007; 15(3):199-236. doi:10.1093/pan/mpl013 32. Eberly LA, Yang L, Essien UR, et al. Racial,ethnic, and socioeconomic inequities in glucagon-like peptide-1 receptor agonist use among patients with diabetes in the US. JAMA Health Forum. 2021; 2(12):e214182. doi:10.1001/jamahealthforum.2021.4182 33. Liang KY, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika. 1986; 73(1):13-22. doi:10.1093/biomet/73.1.13 34. Williamson E, Morley R, Lucas A, Carpenter J.Propensity scores: from naive enthusiasm to intuitive understanding. Stat Methods Med Res.2012; 21(3):273-293. doi:10.1177/0962280210394483 35. White IR, Royston P, Wood AM. Multiple imputation using chained equations: issues and guidance for practice. Stat Med. 2011; 30(4):377-399.doi:10.1002/sim.4067 36. Pishgar F, Greifer N, Leyrat C, Stuart E.MatchThem: matching and weighting after multiple imputation. R J. 2021; 13(2):228. doi:10.32614/RJ-2021-073 37. van Buuren S, Groothuis-Oudshoorn K.mice: Multivariate imputation by chained equations in R.J Stat Softw. 2011; 45(3):1-67. doi:10.18637/jss.v045.i03 38. Lumley T. Analysis of complex survey samples. J Stat Softw. 2004; 9(8):1-19. doi:10.18637/jss.v009.i08 39. Waters TP, Huston-Presley L, Catalano PM. Neonatal body composition according to the revised Institute of Medicine recommendations for maternal weight gain. J Clin Endocrinol Metab. 2012; 97(10):3648-3654. doi:10.1210/jc.2012-1781 40. Hivert MF, Rifas-Shiman SL, Gillman MW,Oken E. Greater early and mid-pregnancy gestational weight gains are associated with excess adiposity in mid-childhood. Obesity (Silver Spring).2016; 24(7):1546-1553. doi:10.1002/oby.21511 41. Wells BJ, Chagin KM, Nowacki AS, Kattan MW. Strategies for handling missing data in electronic health record derived data. EGEMS (Wash DC).2013; 1(3):1035. doi:10.13063/2327-9214.1035 42. Greifer N, Stuart EA. Choosing the causal estimand for propensity score analysis of observational studies. arXiv. Preprint posted online June 19, 2021. doi:10.48550/arXiv.2106.10577 43. Osterman MJK, Hamilton BE, Martin JA,Driscoll AK, Valenzuela CP. Births: final data for 2022. Natl Vital Stat Rep. 2024; 73(2):1-56.
责编：Lucy