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Article(id=1322191050861560196, tenantId=1146029695717560320, journalId=1319373162502258839, issueId=1322191025829953744, articleNumber=null, orderNo=null, doi=10.16016/j.2097-0927.202504006, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1743955200000, receivedDateStr=2025-04-07, revisedDate=1749916800000, revisedDateStr=2025-06-15, acceptedDate=null, acceptedDateStr=null, onlineDate=1793164511646, onlineDateStr=2026-10-28, pubDate=1753804800000, pubDateStr=2025-07-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793164511646, onlineIssueDateStr=2026-10-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793164511646, creator=13701087609, updateTime=1793164511646, updator=13701087609, issue=Issue{id=1322191025829953744, tenantId=1146029695717560320, journalId=1319373162502258839, year='2025', volume='47', issue='14', pageStart='1557', pageEnd='1684', issueExtLink='null', onlineDate='null', pubDate='1753804800000', pubDateStr='2025-07-30', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793164505679, creator='13701087609', updateTime=1793164547848, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322191202804420934, tenantId=1146029695717560320, journalId=1319373162502258839, issueId=1322191025829953744, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322191202804420935, tenantId=1146029695717560320, journalId=1319373162502258839, issueId=1322191025829953744, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1670, endPage=1675, ext={EN=ArticleExt(id=1322191052644139397, articleId=1322191050861560196, tenantId=1146029695717560320, journalId=1319373162502258839, language=EN, title=Predictive value and risk factors of embryo implantation site for placenta previa, columnId=1320435174995772212, journalTitle=Journal of Army Medical University, columnName=Clinical Medicine, runingTitle=null, highlight=null, articleAbstract=
Objective‍

To develop a prediction model for placenta previa in early pregnancy by analyzing embryo implantation sites and related clinical factors, in order to provide an objective basis for early risk identification.

Methods‍

A retrospective cohort study was conducted on 232 singleton pregnant women delivering in our hospital between September 2020 and March 2024. According to the final pre-delivery ultrasound findings, they were divided into placenta previa group (n=78) and a non-placenta previa group (n=154). Their ultrasound parameters [distance from lower gestational sac margin to cervical os, implantation site (lower/middle-upper uterine segment), and implantation position (anterior/posterior wall)], and clinical data [age, gravidity (categorized as <2 or ≥2 pregnancies), parity (<2 or ≥2 deliveries), and history of intrauterine procedures were collected through electronic medical records. Univariate analysis was used to screen potential predictors (P<0.1), and multivariate logistic regression analysis was employed to identify the predictors (P<0.05) for placenta previa. Then a nomogram prediction model was constructed, which was internally validated with Bootstrap (1 000 bootstrap resamples) and assessed for discrimination with area under the receiver operating characteristic curve (AUC) and for calibration with Hosmer-Lemeshow goodness-of-fit test.

Results‍

The placenta previa group showed significantly advanced age (≥35 years), lower education level (≤high school), multigravidity (≥2 pregnancies), multiparity (≥2 deliveries), more intrauterine procedures, distance of gestational sac-to-cervical os <5.5 mm, and larger proportion of lower uterine segment implantation than the non-placenta previa group (all P<0.1). But there were no statistical differences between the 2 groups in proportion of posterior wall implantation, history of cesarean section or assisted reproductive technology (ART). Multivariate logistic regression analysis confirmed lower uterine segment implantation (OR=40.40, 95%CI: 14.68~136.19, P<0.001), posterior wall implantation (OR=2.73, 95%CI:1.27~6.28, P=0.013), and intrauterine procedures (OR=3.48, 95%CI: 1.65~7.70, P=0.001) as independent risk factors. The model based on these predictors demonstrated excellent discrimination (AUC value=0.84, 95%CI: 0.79~0.90) and calibration (Hosmer-Lemeshow test Chi-square=3.455, P=0.750).

Conclusion‍

Lower uterine segment/posterior wall implantation and intrauterine procedures are independent risk factors for placenta previa. Our nomogram model based on these factors shows good predictive efficiency, and can provide reference for early recognition of pregnant woman with high-risk placenta previa.

, authors=Na KUANG, Wenjiao HE, Xi XIONG, Zhengqiong CHEN, authorsList=Na KUANG, Wenjiao HE, Xi XIONG, Zhengqiong CHEN, authorCompany=null, correspAuthors=Zhengqiong CHEN, authorNote=null, correspAuthorsNote=null, copyrightStatement=© 2025 Journal of Army Medical University, copyrightOwner=Editorial Office of Journal of Army Medical University, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322191054141505934, articleId=1322191050861560196, tenantId=1146029695717560320, journalId=1319373162502258839, language=CN, title=胚胎着床位置对前置胎盘的预测价值及相关影响因素分析, columnId=1322185541475488183, journalTitle=陆军军医大学学报, columnName=临床医学, runingTitle=null, highlight=null, articleAbstract=
目的

通过分析胚胎着床位置及相关临床因素，建立早孕期前置胎盘预测模型，为临床早期识别高风险人群提供客观依据。

方法

采用回顾性队列研究设计，纳入2020年9月至2024年3月于陆军军医大学第二附属医院分娩的232例单胎妊娠孕妇。根据分娩前末次超声检查结果分为前置胎盘组（n=78）和非前置胎盘组（n=154）。通过电子病历系统收集：①超声参数：孕囊下缘至宫颈内口距离、胚胎着床上下位置（下段/中上段）、胚胎着床前后位置（后壁/前壁）；②临床资料：年龄、孕次、产次、宫腔操作史等。采用单因素分析（P<0.1）筛选潜在预测因素，通过多因素Logistic回归（P<0.05）确定独立危险因素，并基于回归结果构建列线图预测模型。通过Bootstrap法（1 000次重采样）进行内部验证，采用受试者工作特征曲线下面积（AUC）和Hosmer-Lemeshow检验评估模型性能。

结果

通过单因素分析显示，前置胎盘组在高龄（≥35岁）、低学历（高中及以下）、多孕次（≥2次）、多产次（≥2次）、宫腔操作史、孕囊下缘距宫颈内口<5.5 mm及胚胎着床下段的比例高于非前置胎盘组（P<0.1）；而胚胎着床后壁、剖宫产史和ART组间差异无统计学意义（P>0.1）。多因素Logistic回归分析进一步证实，胚胎着床于下段（OR=40.40，95%CI：14.68~136.19，P<0.001）、着床于后壁（OR=2.73，95%CI：1.27~6.28，P=0.013）和宫腔操作史（OR=3.48，95%CI：1.65~7.70，P=0.001）是前置胎盘的独立危险因素。基于这些因素构建的预测模型具有较高的区分度（AUC=0.84，95%CI：0.79~0.90）和良好的校准度（Hosmer-Lemeshow检验，χ²=3.455，P=0.750）。

结论

胚胎着床于下段、着床于后壁和宫腔操作史是前置胎盘的独立危险因素。基于这些因素构建的列线图模型具有良好的预测效能，可为临床早期识别前置胎盘高风险孕妇提供参考。

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陈正琼，E-mail：
CHEN Zhengqiong，E-mail：
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Ultrasound Obstet Gynecol，2020，56（5）：725-731., articleTitle=Follow-up ultrasound in second-trimester low-positioned anterior and posterior placentae：prospective cohort study, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1322191054384775567, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, xref=1, ext=[AuthorCompanyExt(id=1322191054397358480, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, companyId=1322191054384775567, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1Department of Obstetrics and Gynecology，Second Affiliated Hospital，Army Medical University （Third Military Medical University），Chongqing，China), AuthorCompanyExt(id=1322191054409941393, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, companyId=1322191054384775567, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1陆军军医大学（第三军医大学）第二附属医院妇产科，重庆)])], figs=[ArticleFig(id=1322191057601806766, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, language=EN, label=null, caption=null, figureFileSmall=W2jEkXXNEr6b0DP8XBiKwg==, figureFileBig=Y54JdNPTmIw7SighHzp8Cw==, tableContent=null), ArticleFig(id=1322191057673109935, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, language=CN, label=图1, caption=同一孕妇妊娠6周的经阴道超声特征

A：子宫矢状切面显示由底蜕膜与叶状绒毛膜构成的早期胎盘结构（胚胎着床位置），定位显示着床于宫腔上1/3段前壁；B：子宫横切面（局部放大）显示底蜕膜-叶状绒毛膜界面；C：彩色多普勒显示早期胎盘滋养血管束（即血流富集区）；D：三维容积重建：立体展示底蜕膜、叶状绒毛膜与宫腔的空间关系

, figureFileSmall=W2jEkXXNEr6b0DP8XBiKwg==, figureFileBig=Y54JdNPTmIw7SighHzp8Cw==, tableContent=null), ArticleFig(id=1322191057899602352, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, language=EN, label=null, caption=null, figureFileSmall=HQiBawoAhAeSNZlyMNEuZg==, figureFileBig=EZJrIjOEfGD0UkCWM5l6Nw==, tableContent=null), ArticleFig(id=1322191057954128305, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, language=CN, label=图2, caption=前置胎盘风险列线图, figureFileSmall=HQiBawoAhAeSNZlyMNEuZg==, figureFileBig=EZJrIjOEfGD0UkCWM5l6Nw==, tableContent=null), ArticleFig(id=1322191058025431474, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, language=EN, label=null, caption=null, figureFileSmall=00KvlASFrVeur48fGuMB0A==, figureFileBig=IXm/+1ngr8fAPODur0pToQ==, tableContent=null), ArticleFig(id=1322191058100928947, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, language=CN, label=图3, caption=列线图预测效果的ROC曲线, figureFileSmall=00KvlASFrVeur48fGuMB0A==, figureFileBig=IXm/+1ngr8fAPODur0pToQ==, tableContent=null), ArticleFig(id=1322191058168037812, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, language=EN, label=null, caption=null, figureFileSmall=dXh9c/nZZjoMOtbXdmzs4w==, figureFileBig=iY1GZ7kcrien/vmciLtE1g==, tableContent=null), ArticleFig(id=1322191058247729589, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, language=CN, label=图4, caption=列线图校准曲线, figureFileSmall=dXh9c/nZZjoMOtbXdmzs4w==, figureFileBig=iY1GZ7kcrien/vmciLtE1g==, tableContent=null), ArticleFig(id=1322191058319032758, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
项目非前置胎盘组（n=154）前置胎盘组（n=78）χ²P
ART149/154（96.75）71/78（91.03）3.4630.112
剖宫产史64/154（41.56）25/78（32.05）1.9790.159
年龄≥35岁29/154（18.83）24/78（30.77）4.1860.041
产次≥2次101/154（65.58）60/78（76.92）3.1340.077
孕次≥2次85/154（55.19）62/78（79.49）13.162<0.001
学历（高中及以下）107/154（69.48）40/78（51.28）7.3860.007
宫腔操作史70/154（45.45）63/78（80.77）26.395<0.001
胚胎着床后壁79/154（51.30）41/78（52.56）0.0330.855
胚胎着床下段5/154（3.25）42/78（53.85）82.059<0.001
孕囊下缘至宫颈内口距离<5.5 mm8/154（5.19）40/78（51.28）67.020<0.001
), ArticleFig(id=1322191058390335927, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, language=CN, label=表1, caption=

前置胎盘组与非前置胎盘组二分类变量比较 ［例（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
项目非前置胎盘组（n=154）前置胎盘组（n=78）χ²P
ART149/154（96.75）71/78（91.03）3.4630.112
剖宫产史64/154（41.56）25/78（32.05）1.9790.159
年龄≥35岁29/154（18.83）24/78（30.77）4.1860.041
产次≥2次101/154（65.58）60/78（76.92）3.1340.077
孕次≥2次85/154（55.19）62/78（79.49）13.162<0.001
学历（高中及以下）107/154（69.48）40/78（51.28）7.3860.007
宫腔操作史70/154（45.45）63/78（80.77）26.395<0.001
胚胎着床后壁79/154（51.30）41/78（52.56）0.0330.855
胚胎着床下段5/154（3.25）42/78（53.85）82.059<0.001
孕囊下缘至宫颈内口距离<5.5 mm8/154（5.19）40/78（51.28）67.020<0.001
), ArticleFig(id=1322191058465833400, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
变量βSEPOR95%CI
宫腔操作史1.250.390.0013.481.65~7.70
胚胎着床下段3.700.56<0.00140.4014.68~136.19
胚胎着床后壁1.000.400.0132.731.27~6.28
), ArticleFig(id=1322191058549719481, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322191050861560196, language=CN, label=表2, caption=

前置胎盘的多因素Logistic回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量βSEPOR95%CI
宫腔操作史1.250.390.0013.481.65~7.70
胚胎着床下段3.700.56<0.00140.4014.68~136.19
胚胎着床后壁1.000.400.0132.731.27~6.28
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胚胎着床位置对前置胎盘的预测价值及相关影响因素分析
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况娜 , 何文娇 , 熊希 , 陈正琼
陆军军医大学学报 | 临床医学 2025,47(14): 1670-1675
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陆军军医大学学报 |临床医学 2025 , 47 (14) : 1670 -1675
胚胎着床位置对前置胎盘的预测价值及相关影响因素分析
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况娜, 何文娇, 熊希, 陈正琼
作者信息
  • 1陆军军医大学（第三军医大学）第二附属医院妇产科，重庆
通讯作者:
陈正琼，E-mail：
CHEN Zhengqiong，E-mail：
Predictive value and risk factors of embryo implantation site for placenta previa
Na KUANG, Wenjiao HE, Xi XIONG, Zhengqiong CHEN
Affiliations
  • 1Department of Obstetrics and Gynecology，Second Affiliated Hospital，Army Medical University （Third Military Medical University），Chongqing，China
出版时间: 2025-07-30 doi: 10.16016/j.2097-0927.202504006
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摘要
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目的

通过分析胚胎着床位置及相关临床因素，建立早孕期前置胎盘预测模型，为临床早期识别高风险人群提供客观依据。

方法

采用回顾性队列研究设计，纳入2020年9月至2024年3月于陆军军医大学第二附属医院分娩的232例单胎妊娠孕妇。根据分娩前末次超声检查结果分为前置胎盘组（n=78）和非前置胎盘组（n=154）。通过电子病历系统收集：①超声参数：孕囊下缘至宫颈内口距离、胚胎着床上下位置（下段/中上段）、胚胎着床前后位置（后壁/前壁）；②临床资料：年龄、孕次、产次、宫腔操作史等。采用单因素分析（P<0.1）筛选潜在预测因素，通过多因素Logistic回归（P<0.05）确定独立危险因素，并基于回归结果构建列线图预测模型。通过Bootstrap法（1 000次重采样）进行内部验证，采用受试者工作特征曲线下面积（AUC）和Hosmer-Lemeshow检验评估模型性能。

结果

通过单因素分析显示，前置胎盘组在高龄（≥35岁）、低学历（高中及以下）、多孕次（≥2次）、多产次（≥2次）、宫腔操作史、孕囊下缘距宫颈内口<5.5 mm及胚胎着床下段的比例高于非前置胎盘组（P<0.1）；而胚胎着床后壁、剖宫产史和ART组间差异无统计学意义（P>0.1）。多因素Logistic回归分析进一步证实，胚胎着床于下段（OR=40.40，95%CI：14.68~136.19，P<0.001）、着床于后壁（OR=2.73，95%CI：1.27~6.28，P=0.013）和宫腔操作史（OR=3.48，95%CI：1.65~7.70，P=0.001）是前置胎盘的独立危险因素。基于这些因素构建的预测模型具有较高的区分度（AUC=0.84，95%CI：0.79~0.90）和良好的校准度（Hosmer-Lemeshow检验，χ²=3.455，P=0.750）。

结论

胚胎着床于下段、着床于后壁和宫腔操作史是前置胎盘的独立危险因素。基于这些因素构建的列线图模型具有良好的预测效能，可为临床早期识别前置胎盘高风险孕妇提供参考。

胚胎着床  /  前置胎盘  /  危险因素  /  预测模型
Objective‍

To develop a prediction model for placenta previa in early pregnancy by analyzing embryo implantation sites and related clinical factors, in order to provide an objective basis for early risk identification.

Methods‍

A retrospective cohort study was conducted on 232 singleton pregnant women delivering in our hospital between September 2020 and March 2024. According to the final pre-delivery ultrasound findings, they were divided into placenta previa group (n=78) and a non-placenta previa group (n=154). Their ultrasound parameters [distance from lower gestational sac margin to cervical os, implantation site (lower/middle-upper uterine segment), and implantation position (anterior/posterior wall)], and clinical data [age, gravidity (categorized as <2 or ≥2 pregnancies), parity (<2 or ≥2 deliveries), and history of intrauterine procedures were collected through electronic medical records. Univariate analysis was used to screen potential predictors (P<0.1), and multivariate logistic regression analysis was employed to identify the predictors (P<0.05) for placenta previa. Then a nomogram prediction model was constructed, which was internally validated with Bootstrap (1 000 bootstrap resamples) and assessed for discrimination with area under the receiver operating characteristic curve (AUC) and for calibration with Hosmer-Lemeshow goodness-of-fit test.

Results‍

The placenta previa group showed significantly advanced age (≥35 years), lower education level (≤high school), multigravidity (≥2 pregnancies), multiparity (≥2 deliveries), more intrauterine procedures, distance of gestational sac-to-cervical os <5.5 mm, and larger proportion of lower uterine segment implantation than the non-placenta previa group (all P<0.1). But there were no statistical differences between the 2 groups in proportion of posterior wall implantation, history of cesarean section or assisted reproductive technology (ART). Multivariate logistic regression analysis confirmed lower uterine segment implantation (OR=40.40, 95%CI: 14.68~136.19, P<0.001), posterior wall implantation (OR=2.73, 95%CI:1.27~6.28, P=0.013), and intrauterine procedures (OR=3.48, 95%CI: 1.65~7.70, P=0.001) as independent risk factors. The model based on these predictors demonstrated excellent discrimination (AUC value=0.84, 95%CI: 0.79~0.90) and calibration (Hosmer-Lemeshow test Chi-square=3.455, P=0.750).

Conclusion‍

Lower uterine segment/posterior wall implantation and intrauterine procedures are independent risk factors for placenta previa. Our nomogram model based on these factors shows good predictive efficiency, and can provide reference for early recognition of pregnant woman with high-risk placenta previa.

embryo implantation  /  placenta previa  /  risk factors  /  prediction model
况娜, 何文娇, 熊希, 陈正琼. 胚胎着床位置对前置胎盘的预测价值及相关影响因素分析. 陆军军医大学学报, 2025 , 47 (14) : 1670 -1675 . DOI: 10.16016/j.2097-0927.202504006
Na KUANG, Wenjiao HE, Xi XIONG, Zhengqiong CHEN. Predictive value and risk factors of embryo implantation site for placenta previa[J]. Journal of Army Medical University, 2025 , 47 (14) : 1670 -1675 . DOI: 10.16016/j.2097-0927.202504006
正文
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前置胎盘是指妊娠28周后胎盘位置低于胎先露部，其下缘达到或覆盖宫颈内口［1］。随着我国生育政策调整（全面二孩、三孩政策实施），前置胎盘发病率呈显著上升趋势，现已成为妊娠晚期出血和医源性早产的重要原因，严重威胁母婴安全［2］。流行病学调查显示，我国前置胎盘发病率存在明显地域差异，1965-2015年全国总体发病率为1.24%，其中西南地区发病率最高（达2.01%）［3］。目前其发病机制尚未完全阐明，现有研究认为主要与子宫内膜损伤［4］及胚胎着床位置异常［5］等因素相关。因此，建立早期预测体系对临床干预具有重要价值。
在产科超声领域，早孕期胚胎着床位置的评估已成为预测胎盘发育异常的重要研究方向。现有研究主要通过测量孕囊下缘与宫颈内口或剖宫产瘢痕的距离来评估着床位置［6-7］，该方法在孕囊较小时期预测价值较高，但随着孕囊增大其准确性逐渐降低。近年研究发现，妊娠5~6周的胚胎/卵黄囊位置与中期胎盘位置具有良好一致性［8］。金雪鸿等［9］学者基于超声检测技术，通过多维度指标分析发现，血流富集区、孕囊囊壁增厚区、卵黄囊位置及胚芽位置4项超声指标对早孕期（<10周）胎盘定位的预测符合率分别达90.29%、89.02%、73.01%和70.15%，且多参数联合评估可显著提升预测准确性，这为早期胎盘定位提供了更可靠的评估方法。然而，当前研究方法仍存在局限性：一方面，对孕囊着床方位（前壁/后壁）的差异性影响研究不足；另一方面，尚缺乏整合超声指标与临床危险因素的预测模型。基于此，本研究旨在通过超声观察胚胎着床位置和早孕期临床特征，尽早识别前置胎盘高风险人群，构建前置胎盘的预测模型，为临床提供理论参考。
1　资料与方法
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1.1　研究对象
选取2020年9月至2024年3月从妊娠5~8周起全程于陆军军医大学第二附属医院产检，并于妊娠28周后在该院分娩的孕妇为研究对象。其中发展为前置胎盘者共有78例，设为病例组；另纳入其中非前置胎盘154例设为对照组。纳入标准：①年龄25~45岁；②超声影像及临床资料完整。排除标准：①母体子宫畸形（单角子宫、双子宫、纵隔子宫）；②双胎妊娠或多胎妊娠。样本量计算基于RILEY等［10］提出的预测模型标准，使用R软件（version 4.2.1）的pmsampsize包完成，根据预试验数据（事件发生率33.6%，78/232）、模型预期解释力（Cox-Snell R²=0.307）及3个预测变量，计算得出所需最小样本量为232例（其中阳性事件≥78例）。本研究获得陆军军医大学第二附属医院伦理委员会批准（2025-研第094-01）。
1.2　研究方向
1.2.1　超声检查规范
本研究采用Voluson E10和Philips EPIQ7超声诊断仪进行检查，配置腔内超声探头（频率4~9 MHz）和腹部超声探头（频率3.5 MHz）。检查时，受检者取仰卧截石位，经阴道超声探头置于后穹隆，通过矢状面、横切面等多切面观察胚胎着床位置，并测量孕囊下缘至宫颈内口的距离。胚胎着床位置的判定标准如下：妊娠5~6周通过卵黄囊或胚芽位置确定，妊娠7~8周通过孕囊囊壁增厚区及血流富集区综合判断。胚胎着床的上下位置沿宫腔底部至宫颈内口分为上、中、下三等份［5］，着床的前后位置分为前壁和后壁（图1）。孕囊下缘至宫颈内口距离的测量在子宫矢状切面上进行。预实验确定最佳截断值为5.5 mm，据此分为≥5.5 mm和<5.5 mm两组。所有超声检查由3名经验丰富的妇产科超声医师独立完成，以确保数据准确性。
1.2.2　胎盘相关疾病诊断标准
前置胎盘的诊断依据分娩前末次超声检查结果，检查时孕妇取平卧位并保持膀胱适度充盈，常规采用经腹灰阶超声检查，对可疑病例联合应用经阴道超声及彩色多普勒超声评估。图像采集由一名经验丰富的超声医师完成，并由另一名医师每日复核。胎盘植入性疾病（placenta accreta spectrum disorders，PAS）的诊断分为产前评估和产后确诊［11］。产前评估主要通过超声检查，重点观察胎盘植入征象，对于超声无法明确植入深度或评估后壁植入、宫旁组织受累的病例，补充MRI检查。产后确诊以手术记录和病理结果为金标准，病理诊断分为粘连型（placenta creta，PC，绒毛侵入浅肌层）、植入型（placenta increta，PI，绒毛侵入深肌层）和穿透型（placenta percreta，PP，绒毛穿透浆膜层或侵犯邻近器官）［12］。若病理结果与手术-临床诊断不一致，以病理结果为准。
1.2.3　临床资料收集
包括孕妇年龄、学历、孕次、产次、剖宫产史、宫腔操作史（如人工流产、宫腔粘连松解术、息肉或黏膜下肌瘤切除术、诊断性刮宫术）以及辅助生殖技术（assisted reproductive technology，ART）。所有数据通过电子化采集，并由双人核对录入，确保数据的完整性和准确性。
1.3　统计学分析
采用SPSS 26.0和R软件（R version 4.2.1）进行统计分析。计数资料以例（%）表示，组间比较采用χ²检验。通过单因素分析（P<0.1）筛选潜在预测因素后，纳入多因素Logistic回归分析（P<0.05）确定前置胎盘的独立危险因素，并基于回归结果构建列线图预测模型。采用Bootstrap法（1 000次重采样）进行内部验证，通过校准曲线和Hosmer-Lemeshow检验评估模型校准度，通过受试者工作特征曲线（ROC曲线）分析模型的区分能力，计算曲线下面积（AUC）及其95%置信区间。所有检验均为双侧，P<0.05为差异有统计学意义。
2　结果
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2.1　前置胎盘组与非前置胎盘组的一般资料及组间比较
本研究期间，从妊娠5~8周起全程我院产检并分娩的孕妇共5 360例，发展成前置胎盘者78例，且前置胎盘中合并胎盘植入性疾病者共51例。单因素分析（检验水准α=0.1）显示，前置胎盘组在高龄（≥35岁）、低学历（高中及以下）、多孕次（≥2次）、多产次（≥2次）、宫腔操作史、孕囊下缘距宫颈内口<5.5 mm及胚胎着床下段的比例显著高于非前置胎盘组（P<0.1）；而胚胎着床后壁、剖宫产史和ART的组间差异无统计学意义（P>0.1），见表1。
2.2　前置胎盘危险因素的Logistic回归分析
采用多因素Logistic回归分析（前向似然比法）探讨前置胎盘的危险因素，将单因素分析中P<0.1的变量（年龄、学历、产次、孕次、宫腔操作史、孕囊下缘至宫颈内口距离、胚胎着床上下位置）纳入模型，同时基于临床重要性保留了单因素分析无统计学差异的胚胎着床前后位置指标［13］。最终分析显示：胚胎着床下段（与中上段相比：OR=40.40，95%CI：14.68~136.19，P<0.001）、宫腔操作史（OR=3.48，95%CI：1.65~7.70，P<0.001）及胚胎着床后壁（与前壁相比：OR=2.73，95%CI：1.27~6.28，P=0.013）是前置胎盘的独立危险因素，其余变量无统计学差异（P>0.05，表2）。
2.3　前置胎盘列线图模型的构建与验证
基于回归结果采用R软件（version 4.2.1）及rms程序包构建前置胎盘风险预测列线图模型（图2），该模型通过计算各危险因素对应评分总和并在风险轴上定位来预测个体发病风险。内部验证显示模型具有良好判别能力（C-index=0.84，95%CI：0.79~0.90，图3）和校准度（Bootstrap法1 000次重采样验证显示校准曲线与理想曲线贴合良好，Hosmer-Lemeshow检验P=0.750）（图4），表明预测风险与实际风险具有良好一致性。
3　讨论
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本研究基于超声参数与临床危险因素的综合评估，揭示了宫腔下段着床、后壁着床以及宫腔操作史是前置胎盘的独立危险因素。这一结果与既往研究中关于宫腔操作损伤内膜导致胎盘异常种植［4，14］的机制一致，同时提出了着床位置高低及后壁着床在前置胎盘发生中的独立预测价值，为临床早期识别高危人群提供了新的视角。
宫腔下段着床作为前置胎盘最突出的危险因素（OR=40.40，95%CI：14.68~136.19），其风险预测的关键在于早期胚胎着床位置的精准判断［15］。临床研究表明，以下超声参数可用于胚胎着床位置的判断：在妊娠5~6周，底蜕膜的可视化（厚度于6~7周达峰）及卵黄囊/胚芽位置可提供初始定位［16］；至7~8周，孕囊增厚区域与血流富集区则成为更明显的判断指标［9］。这种多时段、多参数的评估方法具有高度准确性，一项前瞻性研究显示其与中期胎盘位置判断完全一致［8］。基于此方法，本研究发现胚胎着床位置与宫颈内口的关系直接决定风险程度，这可能与宫颈区域的特殊生理环境有关：丰富的血供既延缓了胎盘边缘的生理性退化，又限制了其向宫底方向的自然移位，从而导致胎盘持续附着在子宫下段［17］。
后壁着床同样显著增加前置胎盘风险（OR=2.73，95%CI：1.27~6.28），其机制源于子宫后壁的解剖学特性：肌层较薄且扩张受限，限制了胎盘的生理性迁移能力。相比之下，前壁胎盘可随子宫下段形成向血供更丰富的宫底移行，而后壁胎盘易滞留于原位，这一结论与JANSEN等［18］的前瞻性研究结果一致，进一步支持着床位置对胎盘迁移的动态影响。
宫腔操作史（如人工流产、黏膜下肌瘤切除术等）使前置胎盘风险升高3.48倍（95%CI：1.65~7.70）。其机制可能为操作导致子宫内膜基底层损伤，破坏蜕膜化过程，促使胚胎选择血供相对充足的宫颈区或瘢痕邻近区域着床［4，14］。值得注意的是，LI等［6］的研究表明，剖宫产瘢痕妇女中孕囊下缘与瘢痕距离越近，前置胎盘风险越高，但本研究进一步揭示，即使无瘢痕存在，宫腔操作本身也可通过内膜损伤增加前置胎盘发生风险。
这些危险因素的发现具有重要的临床启示。将胚胎着床位置评估纳入早孕期筛查，有助于早期识别前置胎盘的高危人群，实现疾病的早发现、早干预；针对同时具备下段着床、后壁着床以及宫腔操作史等多个高危因素的孕妇，建立个性化的预警机制，制定严密的孕期管理方案，能够有效降低前置胎盘相关并发症的发生风险；从长远来看，优化宫腔操作技术，最大程度减少对子宫内膜的损伤，是降低前置胎盘发病率的重要预防措施。
本研究创新性地通过早孕期经阴道超声直接评估胚胎着床位置（宫腔下段/中上段、后壁/前壁），并结合宫腔操作史构建了可视化列线图预测模型，为前置胎盘的早期风险评估提供了新的量化工具。然而，作为一项单中心回顾性研究，本研究存在选择偏倚的可能性，且样本量有限，模型的外部效度尚需验证。未来研究应通过多中心前瞻性队列进一步验证模型的普适性，同时可探索整合血清学标志物等更多预测指标，并开发智能化评估系统以提高预测效能和临床适用性。

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2025年第47卷第14期
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doi: 10.16016/j.2097-0927.202504006
  • 接收时间：2025-04-07
  • 首发时间：2026-10-28
  • 出版时间：2025-07-30
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  • 收稿日期：2025-04-07
  • 修回日期：2025-06-15
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    1陆军军医大学（第三军医大学）第二附属医院妇产科，重庆

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Number of
species		 占总种数比例
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total species (%)		 属
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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