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中华妇幼临床医学杂志(电子版) ›› 2020, Vol. 16 ›› Issue (05) : 574 -583. doi: 10.3877/cma.j.issn.1673-5250.2020.05.011

所属专题： 文献；

论著

妊娠期糖尿病高龄孕妇并发子痫前期的相关因素分析
陈秋和1, 单丹2, 陈倩1, 胡雅毅2,†()   
  1. 1. 四川大学华西第二医院妇产科、出生缺陷与相关妇儿疾病教育部重点实验室，成都　610041；四川大学华西临床医学院，成都　610041
    2. 四川大学华西第二医院妇产科、出生缺陷与相关妇儿疾病教育部重点实验室，成都　610041
  • 收稿日期:2020-03-04 修回日期:2020-09-07 出版日期:2020-10-01
  • 通信作者: 胡雅毅

Correlation analysis between advanced pregnant women with gestational diabetes mellitus and different types of preeclampsia

Qiuhe Chen1, Dan Shan2, Qian Chen1, Yayi Hu2,†()   

  1. 1. Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China; West China School of Medicine, Sichuan University, Chengdu 610041, Sichuan Province, China
    2. Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
  • Received:2020-03-04 Revised:2020-09-07 Published:2020-10-01
  • Corresponding author: Yayi Hu
  • Supported by:
    Applied Basic Research Project of Science and Technology Department of Sichuan Province(2019YJ0086); Chengdu Technological Innovation Research and Development Project(2019-YF05-00448-SNL); Clinical Research Fund of West China Second University Hospital, Sichuan University(KL024)
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引用本文：

陈秋和, 单丹, 陈倩, 胡雅毅. 妊娠期糖尿病高龄孕妇并发子痫前期的相关因素分析[J]. 中华妇幼临床医学杂志(电子版), 2020, 16(05): 574-583.

Qiuhe Chen, Dan Shan, Qian Chen, Yayi Hu. Correlation analysis between advanced pregnant women with gestational diabetes mellitus and different types of preeclampsia[J]. Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition), 2020, 16(05): 574-583.

目的

探讨妊娠期糖尿病(GDM)单胎妊娠高龄孕妇并发3种类型子痫前期(PE)(PE、早发型PE及重度PE)的相关因素。

方法

选择2018年1至12月在四川大学华西第二医院就诊的600例单胎妊娠高龄(≥35～39岁)孕妇纳入高龄组，年龄为(36.4±1.2)岁，其中GDM孕妇为200例，非GDM孕妇为400例。再按照与高龄组GDM与非GDM孕妇1∶1选取同期在本院就诊的600例单胎妊娠超高龄(≥ 40岁)孕妇纳入超高龄组，年龄为(40.9±1.2)岁，其中GDM孕妇为200例，非GDM孕妇为400例。本研究设定的可能影响孕妇发生PE的相关因素包括GDM、是否初产妇、人体质量指数(BMI)、文化程度、居住地及辅助生殖技术(ART)史，探讨这6种因素影响单胎妊娠高龄孕妇并发3种类型PE(PE、早发型PE及重度PE)的风险。采用t检验对年龄等进行组间比较，采用χ2检验对各组受试者中并发3种类型PE所占比例进行分析。对于2组孕妇并发3种类型PE影响因素的多因素非条件logistic回归模型进行分析。本研究遵循的程序符合2013年修订的《世界医学协会赫尔辛基宣言》要求。

结果

①高龄组和超高龄组中，GDM孕妇发生PE、早发型PE、重度PE所占比例均高于非GDM孕妇，其中高龄组GDM孕妇与非GDM孕妇并发PE者所占比例比较，差异有统计学意义(P<0.05)。超高龄组GDM孕妇与非GDM孕妇并发早发型PE、重度PE所占比例比较，差异亦有统计学意义(P<0.05)。②多因素非条件logistic回归分析结果显示，GDM是导致高龄组孕妇发生PE(OR＝2.232, 95%CI：1.080～4.613，P＝0.030)的危险因素。GDM是导致超高龄组孕妇发生早发型PE(OR＝3.456，95%CI：1.238～9.650，P＝0.018)和重度PE(OR＝2.236，95%CI：1.057～4.729，P＝0.035)的危险因素。③控制混杂因素后，多因素非条件logistic回归分析结果显示，在高龄组中，GDM孕妇发生PE风险是非GDM孕妇的1.934倍(OR＝1.934，95%CI：1.029～4.115，P＝0.047)；BMI≥24 kg/m2是导致高龄组GDM孕妇发生PE(OR＝2.931，95%CI：1.332～6.449, P＝0.008)，早发型PE(OR＝2.977, 95%CI：1.105～8.019，P＝0.031)和重度PE(OR＝2.638，95%CI：1.093～6.365，P＝0.031)的危险因素；居住地在乡村是导致其发生PE(OR＝2.831，95%CI：1.042～7.686，P＝0.041)和重度PE(OR＝3.232，95%CI：1.088～9.603，P＝0.035)的危险因素；文化程度高是高龄孕妇发生PE(OR＝0.231，95%CI：0.071～0.749，P＝0.015)和重度PE(OR＝0.179，95%CI：0.048～0.673，P＝0.011)的保护因素。在超高龄组中，GDM孕妇发生早发型PE、重度PE的风险，分别为非GDM孕妇的3.187倍(OR＝3.187，95%CI：1.109～9.153，P＝0.031)与2.3倍(OR＝2.351，95%CI：1.043～5.302, P＝0.039)；BMI≥24 kg/m2是导致其发生PE(OR＝2.654，95%CI：1.417～4.971，P＝0.002)和重度PE(OR＝3.418，95%CI：1.515～7.710，P＝0.003)的危险因素；居住地在郊县是导致其发生PE(OR＝2.374，95%CI：1.089～5.171，P＝0.030)和重度PE(OR＝5.303，95%CI：2.074～13.565，P<0.001)的危险因素；文化程度高是超高龄孕妇发生PE(OR＝0.347，95%CI：0.135～0.892，P＝0.028)和重度PE(OR＝0.164，95%CI：0.047～0.574，P＝0.005)的保护因素。

结论

GDM高龄孕妇的PE发病风险较非GDM高龄孕妇显著增高，GDM超高龄孕妇的早发型PE和重度PE发病风险较非GDM超高龄孕妇显著增加。BMI≥24 kg/m2、文化程度低、居住地在郊县和乡村，均是导致高龄及超高龄孕妇3种类型PE发生的危险因素。

关键词: 糖尿病, 妊娠, 先兆子痫, 人体质量指数, Logistic模型, 危险因素, 单胎妊娠, 孕妇
Objective

To investigate the correlation between advanced gestational diabetes mellitus (GDM) and different types of preeclampsia (PE), and to improve the clinical management of advanced GDM pregnant women.

Methods

From January to December 2018, 600 elderly pregnant women[(36.4±1.2) years old]admitted to West China Second University Hospital, Sichuan University were included into elderly group, including 200 GDM and 400 non-GDM pregnant women. According to 1∶1 ratio, 600 ultra-elderly pregnant women (200 GDM and 400 non-GDM pregnant women) who visited the same hospital during the same period were enrolled into ultra-elderly group, with the age of (40.9±1.2) years old. Independent-samples t test was used to compare the age between two groups, and the proportion of different types of PE was analyzed by chi-square test. Univariate and multivariate logistic regression models were used to analyze the relationship between GDM elderly pregnant women and different types of PE. This study was in line with the requirements of World Medical Association Declaration of Helsinki revised in 2013.

Results

①The proportions of PE, early-onset PE and severe PE in GDM pregnant women were higher than those in non-GDM pregnant women in both elderly group and ultra-elderly group.Among them, the proportion of GDM pregnant women complicated with PE in the elderly group was higher than that of non-GDM pregnant women, with statistically significant (P<0.05). The proportion of early-onset PE and severe PE in GDM pregnant women in the ultra-elderly group were higher than those of non-GDM pregnant women, with statistically significant (P<0.05). ② Univariate logistic regression analysis showed that GDM was a risk factor for PE of elderly group (OR=2.232, 95%CI: 1.080-4.613, P=0.030). As for ultra-elderly age group, GDM was a risk factor for early-onset PE (OR=3.456, 95%CI: 1.238-9.650, P=0.018) and severe PE (OR=2.236, 95%CI: 1.057-4.729, P=0.035). ③After controlling for confounding factors, multivariate unconditional logistic regression analysis showed that the risk of PE in GDM pregnant women was 1.934 times than that in non-GDM pregnant women (OR=1.934, 95%CI: 1.029-4.115, P=0.047). In addition, BMI≥24 kg/m2 was a risk factor for PE(OR=2.931, 95%CI: 1.332-6.449, P=0.008), early-onset PE(OR=2.977, 95%CI: 1.105-8.019, P=0.031) and severe PE (OR=2.638, 95%CI: 1.093-6.365, P=0.031). Living in rural areas was a risk factor for PE (OR=2.831, 95%CI: 1.042-7.686, P=0.041) and severe PE (OR=3.232, 95%CI: 1.088-9.603, P=0.035). High education level was a protective factor for PE (OR=0.231, 95%CI: 0.071-0.749, P=0.015) and severe PE (OR=0.179, 95%CI: 0.048-0.673, P=0.011). In ultra-elderly group, the risk of early-onset PE and severe PE of pregnant women with GDM increased by 3.187 times (OR=3.187, 95%CI: 1.109-9.153, P=0.031) and 2.351 times (OR=2.351, 95%CI: 1.043-5.302, P=0.039), respectively, compared with those without GDM. In addition, BMI≥24 kg/m2 was a risk factor for PE(OR=2.654, 95%CI: 1.417-4.971, P=0.002) and severe PE (OR=3.418, 95%CI: 1.515-7.710, P=0.003). Living in suburban counties was a risk factor for PE (OR=2.374, 95%CI: 1.089-5.171, P=0.030) and severe PE (OR=5.303, 95%CI: 2.074-13.565, P<0.001). High education level was a protective factor for PE (OR=0.347, 95%CI: 0.135-0.892, P=0.028) and severe PE (OR=0.164, 95%CI: 0.047-0.574, P=0.005).

Conclusions

Elderly GDM pregnant women increase the risk of PE, while ultra-elderly GDM increases the risk of early onset and severe preeclampsia. Overweight and obesity, low education level and living in rural areas of suburban counties are different risk factors of preeclampsia.

Key words: Diabetes, gestation, Pre-eclampsia, Body mass index, Logistic models, Risk factors, Sigleton pregnancy, Pregnant women
表1 高龄组和超高龄组孕妇的3种类型PE所占比例比较[例数(%)]
组别 例数 PE 早发型PE 重度PE 组别 例数 PE 早发型PE 重度PE
高龄组         超高龄组        
  GDM孕妇 200 16(8.0) 8(4.0) 12(6.0)   GDM孕妇 200 22(11.0) 10(5.0) 15(7.5)
  非GDM孕妇 400 15(3.8) 10(2.5) 13(3.2)   非GDM孕妇 400 28(7.0) 6(1.5) 14(3.5)
χ2值   4.915 1.031 2.525 χ2值   2.793 6.293 4.638
P值   0.027 0.310 0.112 P值   0.095 0.012 0.031
表2 GDM导致高龄组孕妇3种类型PE发生的单因素logistic回归分析
PE类型 B SE Wald值 P值 OR值 OR值95%CI
PE 0.803 0.370 4.698 0.030 2.232 1.080～4.613
早发型PE 0.486 0.482 1.013 0.314 1.625 0.631～4.183
重度PE 0.642 0.410 2.451 0.117 1.900 0.851～4.245
表3 GDM导致超高龄组孕妇3种类型PE发生的单因素logistic回归分析
PE类型 B SE Wald值 P值 OR值 OR值95%CI
PE 0.496 0.299 2.749 0.097 0.609 0.339～1.095
早发型PE 1.240 0.524 5.603 0.018 3.456 1.238～9.650
重度PE 0.804 0.382 4.430 0.035 2.236 1.057～4.729
表4 不同类型PE影响因素的多因素非条件logistic回归分析的变量含义及赋值情况
自变量/因变量 变量名 赋值
是否为PE y1 y1＝0表示非PE，y1＝1表示PE
是否为早发型PE y2 y2＝0表示非早发型PE，y2＝1表示早发型PE
是否为重度PE y3 y3＝0表示非重度PE，y3＝1表示重度PE
是否为GDM x1 x1＝0表示非GDM，x1＝1表示GDM
是否为初产妇 x2 x2＝1表示初产妇，x2＝2表示经产妇
BMI x3 x3＝0表示BMI<24 kg/m2，x3＝1表示BMI≥24 kg/m2
文化程度 x4 x4＝1表示学历为小学及以下，x4＝2表示学历为中学，x4＝3表示学历为大学及以上
居住地 x5 x5＝1表示居住地在城市，x5＝2表示居住地在郊县，x5＝3表示居住地在乡村
是否有ART史 x6 x6＝0表示无ART史，x6＝1表示有ART史
表5 高龄组孕妇PE影响因素的多因素非条件logistic分析
影响因素 B SE Wald值 P值 OR值 OR值95%CI
常数项 -2.474 0.604 16.790 <0.001 0.084 —
GDM 0.660 0.385 2.932 0.047 1.934 1.029～4.115
初产妇 -0.350 0.442 0.628 0.428 0.705 0.294～1.675
BMI≥24 kg/m2 1.075 0.402 7.140 0.008 2.931 1.332～6.449
文化程度            
  小学及以下 — — 6.163 0.046 — —
  中学 -0.771 0.560 1.897 0.168 0.463 0.154～1.385
  大学及以上 -1.466 0.600 5.961 0.015 0.231 0.071～0.749
居住地            
  城市 — — 6.041 0.049 — —
  郊县 -0.830 0.761 1.190 0.275 0.436 0.098～1.937
  乡村 1.040 0.510 4.168 0.041 2.831 1.042～7.686
ART史 -0.091 0.582 0.024 0.876 0.913 0.292～2.859
表6 高龄组孕妇早发型PE影响因素的多因素非条件logistic分析
影响因素 B SE Wald值 P值 OR值 OR值95%CI
常数项 -2.872 0.785 13.393 <0.001 0.057 —
GDM 0.332 0.494 0.452 0.501 1.393 0.530～3.666
初产妇 -0.644 0.568 1.285 0.257 0.525 0.173～1.599
BMI≥24 kg/m2 1.091 0.506 4.657 0.031 2.977 1.105～8.019
文化程度            
  小学及以下 — — 1.677 0.432 — —
  中学 -0.759 0.750 1.025 0.311 0.468 0.108～2.035
  大学及以上 -0.984 0.762 1.669 0.196 0.374 0.084～1.663
居住地            
  城市 — — 0.283 0.868 — —
  郊县 —0.200 0.777 0.067 0.796 0.818 0.178～3.753
  乡村 0.337 0.786 0.184 0.668 1.401 0.300～6.540
ART史 -0.391 0.787 0.247 0.619 0.676 0.145～3.162
表7 高龄组孕妇重度PE影响因素的多因素非条件logistic分析
影响因素 B SE Wald值 P值 OR值 OR值95%CI
常数项 -2.331 0.655 12.646 <0.001 0.097 —
GDM 0.469 0.427 1.211 0.271 1.599 0.693～3.689
初产妇 -0.733 0.514 2.028 0.154 0.481 0.175～1.317
BMI≥24 kg/m2 0.970 0.449 4.658 0.031 2.638 1.093～6.365
文化程度            
  小学及以下 — — 6.526 0.038 — —
  中学 -0.991 0.617 2.578 0.108 0.371 0.111～1.244
  大学及以上 -1.720 0.676 6.480 0.011 0.179 0.048～0.673
居住地            
  城市 — — 5.495 0.064 — —
  郊县 —0.535 0.769 0.485 0.486 0.586 0.130～3.642
  乡村 1.173 0.556 4.457 0.035 3.232 1.088～9.603
ART史 0.092 0.591 0.024 0.877 1.096 0.344～3.490
表8 超高龄组孕妇PE影响因素的多因素非条件logistic分析
影响因素 B SE Wald值 P值 OR值 OR值95%CI
常数项 -2.825 0.505 31.315 <0.001 0.059 —
GDM 0.458 0.312 2.165 0.141 1.582 0.859～2.913
初产妇 0.637 0.363 3.083 0.079 1.891 0.929～3.852
BMI≥24 kg/m2 0.976 0.320 9.297 0.002 2.654 1.417～4.971
文化程度            
  小学及以下 — — 4.931 0.085 — —
  中学 -0.552 0.434 1.618 0.203 0.576 0.246～1.348
  大学及以上 -1.059 0.482 4.832 0.028 0.347 0.135～0.892
居住地            
  城市 — — 5.178 0.075 — —
  郊县 0.864 0.397 4.733 0.030 2.374 1.089～5.171
  乡村 0.501 0.411 1.489 0.222 1.651 0.738～3.692
ART史 0.476 0.427 1.244 0.265 1.609 0.697～3.712
表9 超高龄组孕妇早发型PE影响因素的多因素非条件logistic分析
影响因素 B SE Wald值 P值 OR值 OR值95%CI
常数项 -3.867 0.822 22.115 <0.001 0.021 —
GDM 1.159 0.538 4.635 0.031 3.187 1.109～9.153
初产妇 -0.297 0.605 0.241 0.624 0.743 0.227～2.432
BMI≥24 kg/m2 0.892 0.554 2.588 0.108 2.439 0.823～7.230
文化程度            
  小学及以下 — — 3.290 0.193 — —
  中学 -0.465 0.694 0.449 0.503 0.628 0.161～2.448
  大学及以上 -1.665 0.942 3.128 0.077 0.189 0.030～1.198
居住地            
  城市 — — 2.887 0.236 — —
  郊县 1.005 0.638 2.485 0.115 2.732 0.783～9.533
  乡村 0.752 0.714 1.110 0.292 2.121 0.542～8.594
ART史 -0.180 0.707 0.065 0.800 0.836 0.209～3.343
表10 超高龄组孕妇重度PE影响因素的多因素非条件logistic分析
影响因素 B SE Wald值 P值 OR值 OR值95%CI
常数项 -3.693 0.657 31.596 <0.001 0.025 —
GDM 0.855 0.415 4.248 0.039 2.351 1.043～5.302
初产妇 0.759 0.475 2.550 0.110 2.136 0.841～5.424
BMI≥24 kg/m2 1.229 0.415 8.769 0.003 3.418 1.515～7.710
文化程度            
  小学及以下 — — 8.022 0.018 — —
  中学 -0.791 0.515 2.355 0.125 0.454 0.165～1.245
  大学及以上 -1.806 0.638 8.008 0.005 0.164 0.047～0.574
居住地            
  城市 — — 12.478 0.002 — —
  郊县 1.668 0.479 12.124 <0.001 5.303 2.074～13.565
  乡村 0.991 0.526 3.548 0.060 2.693 0.961～7.550
ART史 -0.326 0.695 0.220 0.639 0.722 0.185～2.818
[1]
苏杭，刘之英，赖怡，等. 高龄孕妇产前诊断结果及其首选无创产前筛查局限性的大样本分析[J/CD]. 中华妇幼临床医学杂志(电子版)，2018，14 (6): 718-723. DOI: 10.3877/cma.j.issn.1673-5250.2018.06.015.
[2]
Shan D, Qiu PY, Wu YX, et al. Pregnancy outcomes in women of advanced maternal age: a retrospective Cohort study from China[J]. Sci Rep, 2018, 8(1): 12239. DOI: 10.1038/s41598-018-29889-3.
[3]
漆洪波，刘洪莉，黄湛. 40岁以上高龄孕妇的孕期保健[J/CD]. 妇产与遗传(电子版), 2015, 5(1): 19-22. DOI: 10.3868/j.issn.2095-1558.2015.01.005.
[4]
羊超，曾泽英，唐书勤. 合并妊娠糖尿病的高龄孕产妇并发妊娠高血压疾病危险因素分析[J/CD]. 中国医学前沿杂志(电子版), 2019, 11(1): 147-150. DOI: 10.12037/YXQY.2019.01-26.
[5]
韩肖燕，杨惠霞，杨桦. 妊娠期糖尿病孕妇晚孕期血脂浓度检测的临床意义[J/CD]. 中华妇幼临床医学杂志(电子版)，2019，15 (1): 14-18. DOI: 10.3877/cma.j.issn.1673-5250.2019.01.003
[6]
杨孜，张为远. 《妊娠期高血压疾病诊治指南(2020)》解读[J]. 中华妇产科杂志，2020, 55(6): 425-432. DOI: 10.3760/cma.j.cn112141-20200302-00159.
[7]
Poon LC, Shennan A, Hyett JA, et al. Erratum to " The International Federation of Gynecology and Obstetrics (FIGO) initiative on pre-eclampsia: a pragmatic guide for first-trimester screening and prevention" [Int J Gynecol Obstet 145 Suppl. 1 (2019) 1-33][J]. Int J Gynaecol Obstet, 2019, 146(3): 390-391. DOI: 10.1002/ijgo.12892.
[8]
American Diabetes Association. (2) Classification and diagnosis of diabetes[J]. Diabetes Care, 2015, 38(Suppl): S8-S16. DOI: 10.2337/dc15-S005.
[9]
Zhou BF, Cooperative Meta-Analysis Group of the Working Group on Obesity in China. Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults--study on optimal cut-off points of body mass index and waist circumference in Chinese adults[J]. Biomed Environ Sci, 2002，15(1): 83-96.
[10]
杜文琼，赵枫，郭玲玲，等. 子痫前期风险评估模型建立与验证[J]. 中华疾病控制杂志，2019, 23(8): 981-986. DOI: 10.16462/j.cnki.zhjbkz.2019.08.019.
[11]
王珊，张燕，钟文明，等. 子痫前期发病的相关高危因素调查分析[J]. 中国妇幼保健，2017, 32(1): 125-127. DOI: 10.7620/zgfybj.j.issn.1001-4411.2017.01.44.
[12]
Staff AC. The two-stage placental model of preeclampsia: an update[J]. J Reprod Immunol, 2019, 134-135: 1-10. DOI: 10.1016/j.jri.2019.07.004.
[13]
史伟，彭笑笑，马秀华. 妊娠期糖尿病合并子痫前期的临床特点及对妊娠结局的影响[J]. 中国医刊，2018, 53(9): 1006-1008. DOI: 10.3969/j.issn.1008-1070.2018.09.016.
[14]
Liu L, Zhang X, Rong C, et al. Distinct DNA methylomes of human placentas between pre-eclampsia and gestational diabetes mellitus[J]. Cell Physiol Biochem, 2014, 34(6): 1877-1889. DOI: 10.1159/000366386.
[15]
Weissgerber TL, Mudd LM. Preeclampsia and diabetes[J]. Curr Diab Rep, 2015, 15(3): 9. DOI: 10.1007/s11892-015-0579-4.
[16]
Phaloprakarn C, Tangjitgamol S. Risk assessment for preeclampsia in women with gestational diabetes mellitus[J]. J Perinat Med, 2009, 37(6): 617-621. DOI: 10.1515/JPM.2009.108.
[17]
Poorolajal J, Jenabi E．The association between body mass index and preeclampsia: a Meta-analysis[J]. J Matern Fetal Neonatal Med, 2016, 29(22): 3670-3676.DOI: 10.3109/14767058.2016.1140738.
[18]
Syngelaki A, Nicolaides KH, Balani J, et al. Metformin versus placebo in obese pregnant women without diabetes mellitus[J]. N Engl J Med, 2016, 374(5): 434-443. DOI: 10.1056/NEJMoa1509819.
[19]
Romero R, Erez O, Hüttemann M, et al. Metformin, the aspirin of the 21st century: its role in gestational diabetes mellitus, prevention of preeclampsia and cancer, and the promotion of longevity[J]. Am J Obstet Gyneol, 2017, 217(3): 282-302. DOI: 10.1016/j.ajog.2017.06.003.
[20]
Brownfoot FC, Hastie R, Hannan NJ, et al. Metformin as a prevention and treatment for preeclampsia: effects on soluble fms-like tyrosine kinase 1 and soluble endoglin secretion and endothelial dysfunction[J]. Am J Obstet Gynecol, 2016, 214(3): 356.e1-e356.e15. DOI: 10.1016/j.ajog.2015.12.019.
[21]
Comittee on Obsttric Practice Society for Maternal-Fetal medicine. ACOG Committee Opinion No.743. Low-dose aspirin use during pregnancy[J]. Obstet Gynecol, 2018, 132(1): e44-e52. DOI: 10.1097/AOG.0000000000002708
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