Risk prediction models for gestational diabetes mellitus: a systematic review_Chinese Journal of Evidence-Based Medicine

Authors：

CHEN Shuyu , XING Nianlu ,  ZHOU Yingfeng

School of Nursing, JBI Evidence Based Nursing Cooperation Center, Fudan University, Shanghai 200030, P. R. China;

Corresponding author：

ZHOU Yingfeng, Email: zyingfeng@fudan.edu.cn

Keywords：

Gestational diabetes mellitus; Prediction model; Risk score; Systematic review

DOI：

10.7507/1672-2531.202304022

Video：

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Objective To systematically review the research status of risk prediction models for gestational diabetes mellitus (GDM). Methods The CNKI, WanFang Data, VIP, CBM, PubMed, JBI EBP, Ovid MEDLINE, Embase, Web of Science and Cochrane Library databases were electronically searched to collect relevant literature on risk prediction models for GDM from inception to October 2022. Two researchers independently screened the literature, extracted data, and assessed the risk of bias of the included studies, and then qualitative description was performed. Results A total of 19 studies were included, involving 19 risk prediction models. The evaluation results showed that, in terms of the risk of bias, 18 studies were high risk, and 1 study was unclear. In terms of applicability, 14 studies were high risk, 2 studies were low risk, and 3 studies were unclear. The area under the receiver operating characteristic curve of the included models was 0.69 to 0.88. The most common predictors included age, weight, pre-pregnancy BMI, history of diabetes, family history of diabetes, and race. Conclusion The overall performance of the risk prediction model for gestational diabetes mellitus is good, but the risk of bias of the model is high, and the clinical applicability of the model needs to be further verified.

Citation： CHEN Shuyu, XING Nianlu, ZHOU Yingfeng. Risk prediction models for gestational diabetes mellitus: a systematic review. Chinese Journal of Evidence-Based Medicine, 2023, 23(11): 1253-1258. doi: 10.7507/1672-2531.202304022 Copy

1.	中华医学会妇产科学分会产科学组, 中华医学会围产医学分会妊娠合并糖尿病协作组. 妊娠合并糖尿病诊治指南(2014). 中华妇产科杂志, 2014, 49(8): 561-569.
2.	Wang H, Li N, Chivese T, et al. IDF diabetes atlas: estimation of global and regional gestational diabetes mellitus prevalence for 2021 by international association of diabetes in pregnancy study group's criteria. Diabetes Res Clin Pract, 2022, 183: 109050.
3.	Guariguata L, Linnenkamp U, Beagley J, et al. Global estimates of the prevalence of hyperglycaemia in pregnancy. Diabetes Res Clin Pract, 2014, 103(2): 176-185.
4.	Metzger BE, Lowe LP. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med, 2008, 358(19): 1991-2002.
5.	Scholtens DM, Kuang A, Lowe LP, et al. Hyperglycemia and adverse pregnancy outcome follow-up study (HAPO FUS): maternal glycemia and childhood glucose metabolism. Diabetes Care, 2019, 42(3): 381-392.
6.	韩炜, 唐成和. 母亲妊娠期糖尿病对胎儿结局影响的研究进展. 中华实用儿科临床杂志, 2022, 37(14): 1117-1120.
7.	赵亚玲. 妊娠期糖尿病对子代的远期影响研究. 昆明: 昆明医科大学, 2013.
8.	李占魁, 白瑞苗. 妊娠期高血糖暴露对子代神经发育结局的影响. 中国儿童保健杂志, 2022, 30(10): 1045-1048.
9.	倪娟, 林远贵, 吴兰, 等. 妊娠期糖尿病对肺发育的影响. 中国呼吸与危重监护杂志, 2015, 14(2): 190-193.
10.	徐枭喻, 王梅新, 汪惠才. 糖尿病前期人群筛查方法与风险预测模型的研究进展. 护理研究, 2017, 31(35): 4468-4471.
11.	董婧, 马良坤, 马乐, 等. 妊娠期糖尿病风险预测模型研究进展. 中华健康管理学杂志, 2021, 15(2): 200-204.
12.	廖文圣, 邵彦翔, 孙光曦, 等. 预后预测模型在临床非转移肾细胞癌中的应用价值. 四川大学学报(医学版), 2019, 50(5): 720-724.
13.	陈香萍, 张奕, 庄一渝, 等. PROBAST: 诊断或预后多因素预测模型研究偏倚风险的评估工具. 中国循证医学杂志, 2020, 20(6): 737-744.
14.	马帅. 基于一项队列研究探索妊娠期糖尿病的危险因素并构建风险模型. 北京: 中国医学科学院北京协和医学院, 2019.
15.	陈梦凡, 钱婷婷, 周梦林, 等. 基于人口学及临床特征的妊娠期糖尿病预测模型的研究. 实用妇产科杂志, 2019, 35(2): 117-122.
16.	李金金, 杨梦云, 蒋敏华. 妊娠期糖尿病孕妇早期筛查模型的建立及应用价值. 中国妇幼保健, 2021, 36(1): 69-73.
17.	van Leeuwen M, Opmeer BC, Zweers EJ, et al. Estimating the risk of gestational diabetes mellitus: a clinical prediction model based on patient characteristics and medical history. BJOG, 2010, 117(1): 69-75.
18.	Tran TS, Do MA, Morris JM, et al. Early prediction of gestational diabetes mellitus in Vietnam: clinical impact of currently recommended diagnostic criteria. Diabetes Care, 2013, (36): 618-624.
19.	Teede HJ, Harrison CL, Teh WT, et al. Gestational diabetes: development of an early risk prediction tool to facilitate opportunities for prevention. Aust N Z J Obstet Gynaecol, 2011, 51(6): 499-504.
20.	Syngelaki A, Pastides A, Kotecha R, et al. First-trimester screening for gestational diabetes mellitus based on maternal characteristics and history. Fetal Diagn Ther, 2015, 38(1): 14-21.
21.	Sweeting A, Park F, Hyett J. The first trimester: prediction and prevention of the great obstetrical syndromes. Best Pract Res Clin Obstet Gynaecol, 2015, 29(2): 183-193.
22.	Shirazian N, Emdadi R, Mahboubi M, et al. Screening for gestational diabetes: usefulness of clinical risk factors. Arch Gynecol Obstet, 2009, 280(6): 933-937.
23.	Schoenaker DAJM, Vergouwe Y, Soedamah-Muthu SS, et al. Preconception risk of gestational diabetes: development of a prediction model in nulliparous Australian women. Diabetes Res Clin Pract, 2018, 146: 48-57.
24.	Savvidou M, Nelson SM, Makgoba M, et al. First-trimester prediction of gestational diabetes mellitus: examining the potential of combining maternal characteristics and laboratory measures. Diabetes, 2010, 59(12): 3017-3022.
25.	Phaloprakarn C, Tangjitgamol S, Manusirivithaya S. A risk score for selective screening for gestational diabetes mellitus. Eur J Obstet Gynecol Reprod Biol, 2009, 145(1): 71-75.
26.	Naylor CD, Sermer M, Chen E, et al. Selective screening for gestational diabetes mellitus. Toronto Trihospital Gestational Diabetes Project Investigators. N Engl J Med, 1997, 337(22): 1591-1596.
27.	Nanda S, Savvidou M, Syngelaki A, et al. Prediction of gestational diabetes mellitus by maternal factors and biomarkers at 11 to 13 weeks. Prenat Diagn, 2011, 31(2): 135-141.
28.	Gabbay-Benziv R, Doyle LE, Blitzer M, et al. First trimester prediction of maternal glycemic status. J Perinat Med, 2015, 43(3): 283-289.
29.	Eleftheriades M, Papastefanou I, Lambrinoudaki I, et al. Elevated placental growth factor concentrations at 11-14 weeks of gestation to predict gestational diabetes mellitus. Metabolism, 2014, 63(11): 1419-1425.
30.	Donovan BM, Breheny PJ, Robinson JG, et al. Development and validation of a clinical model for preconception and early pregnancy risk prediction of gestational diabetes mellitus in nulliparous women. PLoS One, 2019, 14(4): e0215173.
31.	Caliskan E, Kayikcioglu F, Oztürk N, et al. A population-based risk factor scoring will decrease unnecessary testing for the diagnosis of gestational diabetes mellitus. Acta Obstet Gynecol Scand, 2004, 83(6): 524-530.
32.	Benhalima K, Van Crombrugge P, Moyson C, et al. Estimating the risk of gestational diabetes mellitus based on the 2013 WHO criteria: a prediction model based on clinical and biochemical variables in early pregnancy. Acta Diabetol, 2020, 57(6): 661-671.
33.	郭淑杰, 王艳红, 赵亚楠, 等. 产后出血风险预测模型的系统评价. 中国循证医学杂志, 2022, 22(11): 1287-1300.
34.	Leng J, Shao P, Zhang C, et al. Prevalence of gestational diabetes mellitus and its risk factors in Chinese pregnant women: a prospective population-based study in Tianjin, China. PLoS One, 2015, 10(3): e0121029.
35.	Kim SY, Sappenfield W, Sharma AJ, et al. Racial/ethnic differences in the prevalence of gestational diabetes mellitus and maternal overweight and obesity, by nativity, Florida, 2004-2007. Obesity (Silver Spring), 2013, 21(1): E33-E40.
36.	Moosazadeh M, Asemi Z, Lankarani KB, et al. Family history of diabetes and the risk of gestational diabetes mellitus in Iran: a systematic review and meta-analysis. Diabetes Metab Syndr, 2017, 11 (Suppl 1): S99-S104.
37.	Bellamy L, Casas JP, Hingorani AD, et al. Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. Lancet, 2009, 373(9677): 1773-1779.
38.	Kragelund Nielsen K, Andersen GS, Damm P, et al. Migration, gestational diabetes, and adverse pregnancy outcomes: a nationwide study of singleton deliveries in Denmark. J Clin Endocrinol Metab, 2021, 106(12): e5075-e5087.
39.	崔俭俭, 陈海天, 王冬昱, 等. 有妊娠期糖尿病史者再次妊娠发生糖代谢异常的危险因素. 中华围产医学杂志, 2021, (5): 335-343.
40.	王志宏, 闫海洋, 刘传丽. 预测妊娠期糖尿病风险模型的外部验证: 基于荷兰人群的前瞻性多中心队列研究. 循证医学, 2018, 18(6): 341-343.
41.	Collins GS, Reitsma JB, Altman DG, et al. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. The TRIPOD Group. Circulation, 2015, 131(2): 211-219.

1. 中华医学会妇产科学分会产科学组, 中华医学会围产医学分会妊娠合并糖尿病协作组. 妊娠合并糖尿病诊治指南(2014). 中华妇产科杂志, 2014, 49(8): 561-569.
2. Wang H, Li N, Chivese T, et al. IDF diabetes atlas: estimation of global and regional gestational diabetes mellitus prevalence for 2021 by international association of diabetes in pregnancy study group's criteria. Diabetes Res Clin Pract, 2022, 183: 109050.
3. Guariguata L, Linnenkamp U, Beagley J, et al. Global estimates of the prevalence of hyperglycaemia in pregnancy. Diabetes Res Clin Pract, 2014, 103(2): 176-185.
4. Metzger BE, Lowe LP. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med, 2008, 358(19): 1991-2002.
5. Scholtens DM, Kuang A, Lowe LP, et al. Hyperglycemia and adverse pregnancy outcome follow-up study (HAPO FUS): maternal glycemia and childhood glucose metabolism. Diabetes Care, 2019, 42(3): 381-392.
6. 韩炜, 唐成和. 母亲妊娠期糖尿病对胎儿结局影响的研究进展. 中华实用儿科临床杂志, 2022, 37(14): 1117-1120.
7. 赵亚玲. 妊娠期糖尿病对子代的远期影响研究. 昆明: 昆明医科大学, 2013.
8. 李占魁, 白瑞苗. 妊娠期高血糖暴露对子代神经发育结局的影响. 中国儿童保健杂志, 2022, 30(10): 1045-1048.
9. 倪娟, 林远贵, 吴兰, 等. 妊娠期糖尿病对肺发育的影响. 中国呼吸与危重监护杂志, 2015, 14(2): 190-193.
10. 徐枭喻, 王梅新, 汪惠才. 糖尿病前期人群筛查方法与风险预测模型的研究进展. 护理研究, 2017, 31(35): 4468-4471.
11. 董婧, 马良坤, 马乐, 等. 妊娠期糖尿病风险预测模型研究进展. 中华健康管理学杂志, 2021, 15(2): 200-204.
12. 廖文圣, 邵彦翔, 孙光曦, 等. 预后预测模型在临床非转移肾细胞癌中的应用价值. 四川大学学报(医学版), 2019, 50(5): 720-724.
13. 陈香萍, 张奕, 庄一渝, 等. PROBAST: 诊断或预后多因素预测模型研究偏倚风险的评估工具. 中国循证医学杂志, 2020, 20(6): 737-744.
14. 马帅. 基于一项队列研究探索妊娠期糖尿病的危险因素并构建风险模型. 北京: 中国医学科学院北京协和医学院, 2019.
15. 陈梦凡, 钱婷婷, 周梦林, 等. 基于人口学及临床特征的妊娠期糖尿病预测模型的研究. 实用妇产科杂志, 2019, 35(2): 117-122.
16. 李金金, 杨梦云, 蒋敏华. 妊娠期糖尿病孕妇早期筛查模型的建立及应用价值. 中国妇幼保健, 2021, 36(1): 69-73.
17. van Leeuwen M, Opmeer BC, Zweers EJ, et al. Estimating the risk of gestational diabetes mellitus: a clinical prediction model based on patient characteristics and medical history. BJOG, 2010, 117(1): 69-75.
18. Tran TS, Do MA, Morris JM, et al. Early prediction of gestational diabetes mellitus in Vietnam: clinical impact of currently recommended diagnostic criteria. Diabetes Care, 2013, (36): 618-624.
19. Teede HJ, Harrison CL, Teh WT, et al. Gestational diabetes: development of an early risk prediction tool to facilitate opportunities for prevention. Aust N Z J Obstet Gynaecol, 2011, 51(6): 499-504.
20. Syngelaki A, Pastides A, Kotecha R, et al. First-trimester screening for gestational diabetes mellitus based on maternal characteristics and history. Fetal Diagn Ther, 2015, 38(1): 14-21.
21. Sweeting A, Park F, Hyett J. The first trimester: prediction and prevention of the great obstetrical syndromes. Best Pract Res Clin Obstet Gynaecol, 2015, 29(2): 183-193.
22. Shirazian N, Emdadi R, Mahboubi M, et al. Screening for gestational diabetes: usefulness of clinical risk factors. Arch Gynecol Obstet, 2009, 280(6): 933-937.
23. Schoenaker DAJM, Vergouwe Y, Soedamah-Muthu SS, et al. Preconception risk of gestational diabetes: development of a prediction model in nulliparous Australian women. Diabetes Res Clin Pract, 2018, 146: 48-57.
24. Savvidou M, Nelson SM, Makgoba M, et al. First-trimester prediction of gestational diabetes mellitus: examining the potential of combining maternal characteristics and laboratory measures. Diabetes, 2010, 59(12): 3017-3022.
25. Phaloprakarn C, Tangjitgamol S, Manusirivithaya S. A risk score for selective screening for gestational diabetes mellitus. Eur J Obstet Gynecol Reprod Biol, 2009, 145(1): 71-75.
26. Naylor CD, Sermer M, Chen E, et al. Selective screening for gestational diabetes mellitus. Toronto Trihospital Gestational Diabetes Project Investigators. N Engl J Med, 1997, 337(22): 1591-1596.
27. Nanda S, Savvidou M, Syngelaki A, et al. Prediction of gestational diabetes mellitus by maternal factors and biomarkers at 11 to 13 weeks. Prenat Diagn, 2011, 31(2): 135-141.
28. Gabbay-Benziv R, Doyle LE, Blitzer M, et al. First trimester prediction of maternal glycemic status. J Perinat Med, 2015, 43(3): 283-289.
29. Eleftheriades M, Papastefanou I, Lambrinoudaki I, et al. Elevated placental growth factor concentrations at 11-14 weeks of gestation to predict gestational diabetes mellitus. Metabolism, 2014, 63(11): 1419-1425.
30. Donovan BM, Breheny PJ, Robinson JG, et al. Development and validation of a clinical model for preconception and early pregnancy risk prediction of gestational diabetes mellitus in nulliparous women. PLoS One, 2019, 14(4): e0215173.
31. Caliskan E, Kayikcioglu F, Oztürk N, et al. A population-based risk factor scoring will decrease unnecessary testing for the diagnosis of gestational diabetes mellitus. Acta Obstet Gynecol Scand, 2004, 83(6): 524-530.
32. Benhalima K, Van Crombrugge P, Moyson C, et al. Estimating the risk of gestational diabetes mellitus based on the 2013 WHO criteria: a prediction model based on clinical and biochemical variables in early pregnancy. Acta Diabetol, 2020, 57(6): 661-671.
33. 郭淑杰, 王艳红, 赵亚楠, 等. 产后出血风险预测模型的系统评价. 中国循证医学杂志, 2022, 22(11): 1287-1300.
34. Leng J, Shao P, Zhang C, et al. Prevalence of gestational diabetes mellitus and its risk factors in Chinese pregnant women: a prospective population-based study in Tianjin, China. PLoS One, 2015, 10(3): e0121029.
35. Kim SY, Sappenfield W, Sharma AJ, et al. Racial/ethnic differences in the prevalence of gestational diabetes mellitus and maternal overweight and obesity, by nativity, Florida, 2004-2007. Obesity (Silver Spring), 2013, 21(1): E33-E40.
36. Moosazadeh M, Asemi Z, Lankarani KB, et al. Family history of diabetes and the risk of gestational diabetes mellitus in Iran: a systematic review and meta-analysis. Diabetes Metab Syndr, 2017, 11 (Suppl 1): S99-S104.
37. Bellamy L, Casas JP, Hingorani AD, et al. Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. Lancet, 2009, 373(9677): 1773-1779.
38. Kragelund Nielsen K, Andersen GS, Damm P, et al. Migration, gestational diabetes, and adverse pregnancy outcomes: a nationwide study of singleton deliveries in Denmark. J Clin Endocrinol Metab, 2021, 106(12): e5075-e5087.
39. 崔俭俭, 陈海天, 王冬昱, 等. 有妊娠期糖尿病史者再次妊娠发生糖代谢异常的危险因素. 中华围产医学杂志, 2021, (5): 335-343.
40. 王志宏, 闫海洋, 刘传丽. 预测妊娠期糖尿病风险模型的外部验证: 基于荷兰人群的前瞻性多中心队列研究. 循证医学, 2018, 18(6): 341-343.
41. Collins GS, Reitsma JB, Altman DG, et al. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. The TRIPOD Group. Circulation, 2015, 131(2): 211-219.

Chinese Journal of Evidence-Based Medicine

Risk prediction models for gestational diabetes mellitus: a systematic review

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