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.	中華醫學會婦產科學分會產科學組, 中華醫學會圍產醫學分會妊娠合并糖尿病協作組. 妊娠合并糖尿病診治指南(2014). 中華婦產科雜志, 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.	韓煒, 唐成和. 母親妊娠期糖尿病對胎兒結局影響的研究進展. 中華實用兒科臨床雜志, 2022, 37(14): 1117-1120.
7.	趙亞玲. 妊娠期糖尿病對子代的遠期影響研究. 昆明: 昆明醫科大學, 2013.
8.	李占魁, 白瑞苗. 妊娠期高血糖暴露對子代神經發育結局的影響. 中國兒童保健雜志, 2022, 30(10): 1045-1048.
9.	倪娟, 林遠貴, 吳蘭, 等. 妊娠期糖尿病對肺發育的影響. 中國呼吸與危重監護雜志, 2015, 14(2): 190-193.
10.	徐梟喻, 王梅新, 汪惠才. 糖尿病前期人群篩查方法與風險預測模型的研究進展. 護理研究, 2017, 31(35): 4468-4471.
11.	董婧, 馬良坤, 馬樂, 等. 妊娠期糖尿病風險預測模型研究進展. 中華健康管理學雜志, 2021, 15(2): 200-204.
12.	廖文圣, 邵彥翔, 孫光曦, 等. 預后預測模型在臨床非轉移腎細胞癌中的應用價值. 四川大學學報(醫學版), 2019, 50(5): 720-724.
13.	陳香萍, 張奕, 莊一渝, 等. PROBAST: 診斷或預后多因素預測模型研究偏倚風險的評估工具. 中國循證醫學雜志, 2020, 20(6): 737-744.
14.	馬帥. 基于一項隊列研究探索妊娠期糖尿病的危險因素并構建風險模型. 北京: 中國醫學科學院北京協和醫學院, 2019.
15.	陳夢凡, 錢婷婷, 周夢林, 等. 基于人口學及臨床特征的妊娠期糖尿病預測模型的研究. 實用婦產科雜志, 2019, 35(2): 117-122.
16.	李金金, 楊夢云, 蔣敏華. 妊娠期糖尿病孕婦早期篩查模型的建立及應用價值. 中國婦幼保健, 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, 王艷紅, 趙亞楠, 等. 產后出血風險預測模型的系統評價. 中國循證醫學雜志, 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.	崔儉儉, 陳海天, 王冬昱, 等. 有妊娠期糖尿病史者再次妊娠發生糖代謝異常的危險因素. 中華圍產醫學雜志, 2021, (5): 335-343.
40.	王志宏, 閆海洋, 劉傳麗. 預測妊娠期糖尿病風險模型的外部驗證: 基于荷蘭人群的前瞻性多中心隊列研究. 循證醫學, 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. 中華醫學會婦產科學分會產科學組, 中華醫學會圍產醫學分會妊娠合并糖尿病協作組. 妊娠合并糖尿病診治指南(2014). 中華婦產科雜志, 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. 韓煒, 唐成和. 母親妊娠期糖尿病對胎兒結局影響的研究進展. 中華實用兒科臨床雜志, 2022, 37(14): 1117-1120.
7. 趙亞玲. 妊娠期糖尿病對子代的遠期影響研究. 昆明: 昆明醫科大學, 2013.
8. 李占魁, 白瑞苗. 妊娠期高血糖暴露對子代神經發育結局的影響. 中國兒童保健雜志, 2022, 30(10): 1045-1048.
9. 倪娟, 林遠貴, 吳蘭, 等. 妊娠期糖尿病對肺發育的影響. 中國呼吸與危重監護雜志, 2015, 14(2): 190-193.
10. 徐梟喻, 王梅新, 汪惠才. 糖尿病前期人群篩查方法與風險預測模型的研究進展. 護理研究, 2017, 31(35): 4468-4471.
11. 董婧, 馬良坤, 馬樂, 等. 妊娠期糖尿病風險預測模型研究進展. 中華健康管理學雜志, 2021, 15(2): 200-204.
12. 廖文圣, 邵彥翔, 孫光曦, 等. 預后預測模型在臨床非轉移腎細胞癌中的應用價值. 四川大學學報(醫學版), 2019, 50(5): 720-724.
13. 陳香萍, 張奕, 莊一渝, 等. PROBAST: 診斷或預后多因素預測模型研究偏倚風險的評估工具. 中國循證醫學雜志, 2020, 20(6): 737-744.
14. 馬帥. 基于一項隊列研究探索妊娠期糖尿病的危險因素并構建風險模型. 北京: 中國醫學科學院北京協和醫學院, 2019.
15. 陳夢凡, 錢婷婷, 周夢林, 等. 基于人口學及臨床特征的妊娠期糖尿病預測模型的研究. 實用婦產科雜志, 2019, 35(2): 117-122.
16. 李金金, 楊夢云, 蔣敏華. 妊娠期糖尿病孕婦早期篩查模型的建立及應用價值. 中國婦幼保健, 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, 王艷紅, 趙亞楠, 等. 產后出血風險預測模型的系統評價. 中國循證醫學雜志, 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. 崔儉儉, 陳海天, 王冬昱, 等. 有妊娠期糖尿病史者再次妊娠發生糖代謝異常的危險因素. 中華圍產醫學雜志, 2021, (5): 335-343.
40. 王志宏, 閆海洋, 劉傳麗. 預測妊娠期糖尿病風險模型的外部驗證: 基于荷蘭人群的前瞻性多中心隊列研究. 循證醫學, 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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