{"title":"妊娠早期胚胎发育停滞的影响因素分析及其预测模型的构建和验证","authors":"Yongjun Ji, Hong Xu, Jianing Wang, Ruiheng Zhao","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Context: </strong>The early symptoms of embryo development arrest are not typical. There is currently no model tool available to predict embryo development arrest.</p><p><strong>Objective: </strong>To explore the influencing factors of embryo development arrest in early pregnancy and build a risk prediction model.</p><p><strong>Methods: </strong>From May 2019 to March 2023, 277 patients suspected of embryonic development arrest during the first ultrasound examination in the Department of Obstetrics and Gynecology of the Ninth Affiliated Hospital of Soochow University were retrospectively selected as the study subjects. They were divided into diapause group and non-diapause group according to the second ultrasound (review after 1-2 weeks) to diagnose whether embryo development arrest. Collect two sets of data for analysis, Screen out the influencing factors of early pregnancy embryo development arrest. The logistic regression model and random forest model were constructed respectively. Evaluate the predictive performance of two statistical models.</p><p><strong>Results: </strong>Out of 277 suspected cases of embryonic developmental arrest, 88 were ultimately confirmed. Older age (OR: 2.259, P = .017), higher ultrasonic blood flow resistance index (RI) (OR: 1.728, P = .038), higher ultrasonic gestational sac diameter/embryo head hip length ratio (MSD/CRL) (OR:1.919, P = .007), lower progesterone (OR: 0.562, P = .011), and lower pregnancy-associated protein A (PAPP-A) (OR: 0.495, P = .023). The low expression of vascular endothelial growth factor (VEGF) (OR: 0.618, P = .005) was the influencing factor of embryo development arrest in early pregnancy. Building a prediction model based on the above indicators, it was found through testing that the random forest model is superior to the logistic regression model in predicting the risk of embryo development arrest.</p><p><strong>Conclusion: </strong>A random forest model based on age, ultrasound RI, progesterone, PAPP-A, ultrasound MSD/CRL ratio, and VEGF index can help clinicians identify the risk of embryonic developmental arrest.</p>","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of Influencing Factors of Embryo Development Arrest During Early Pregnancy and Construction and Validation of its Prediction Model.\",\"authors\":\"Yongjun Ji, Hong Xu, Jianing Wang, Ruiheng Zhao\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Context: </strong>The early symptoms of embryo development arrest are not typical. There is currently no model tool available to predict embryo development arrest.</p><p><strong>Objective: </strong>To explore the influencing factors of embryo development arrest in early pregnancy and build a risk prediction model.</p><p><strong>Methods: </strong>From May 2019 to March 2023, 277 patients suspected of embryonic development arrest during the first ultrasound examination in the Department of Obstetrics and Gynecology of the Ninth Affiliated Hospital of Soochow University were retrospectively selected as the study subjects. They were divided into diapause group and non-diapause group according to the second ultrasound (review after 1-2 weeks) to diagnose whether embryo development arrest. Collect two sets of data for analysis, Screen out the influencing factors of early pregnancy embryo development arrest. The logistic regression model and random forest model were constructed respectively. Evaluate the predictive performance of two statistical models.</p><p><strong>Results: </strong>Out of 277 suspected cases of embryonic developmental arrest, 88 were ultimately confirmed. Older age (OR: 2.259, P = .017), higher ultrasonic blood flow resistance index (RI) (OR: 1.728, P = .038), higher ultrasonic gestational sac diameter/embryo head hip length ratio (MSD/CRL) (OR:1.919, P = .007), lower progesterone (OR: 0.562, P = .011), and lower pregnancy-associated protein A (PAPP-A) (OR: 0.495, P = .023). The low expression of vascular endothelial growth factor (VEGF) (OR: 0.618, P = .005) was the influencing factor of embryo development arrest in early pregnancy. Building a prediction model based on the above indicators, it was found through testing that the random forest model is superior to the logistic regression model in predicting the risk of embryo development arrest.</p><p><strong>Conclusion: </strong>A random forest model based on age, ultrasound RI, progesterone, PAPP-A, ultrasound MSD/CRL ratio, and VEGF index can help clinicians identify the risk of embryonic developmental arrest.</p>\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"3","ListUrlMain":"","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Analysis of Influencing Factors of Embryo Development Arrest During Early Pregnancy and Construction and Validation of its Prediction Model.
Context: The early symptoms of embryo development arrest are not typical. There is currently no model tool available to predict embryo development arrest.
Objective: To explore the influencing factors of embryo development arrest in early pregnancy and build a risk prediction model.
Methods: From May 2019 to March 2023, 277 patients suspected of embryonic development arrest during the first ultrasound examination in the Department of Obstetrics and Gynecology of the Ninth Affiliated Hospital of Soochow University were retrospectively selected as the study subjects. They were divided into diapause group and non-diapause group according to the second ultrasound (review after 1-2 weeks) to diagnose whether embryo development arrest. Collect two sets of data for analysis, Screen out the influencing factors of early pregnancy embryo development arrest. The logistic regression model and random forest model were constructed respectively. Evaluate the predictive performance of two statistical models.
Results: Out of 277 suspected cases of embryonic developmental arrest, 88 were ultimately confirmed. Older age (OR: 2.259, P = .017), higher ultrasonic blood flow resistance index (RI) (OR: 1.728, P = .038), higher ultrasonic gestational sac diameter/embryo head hip length ratio (MSD/CRL) (OR:1.919, P = .007), lower progesterone (OR: 0.562, P = .011), and lower pregnancy-associated protein A (PAPP-A) (OR: 0.495, P = .023). The low expression of vascular endothelial growth factor (VEGF) (OR: 0.618, P = .005) was the influencing factor of embryo development arrest in early pregnancy. Building a prediction model based on the above indicators, it was found through testing that the random forest model is superior to the logistic regression model in predicting the risk of embryo development arrest.
Conclusion: A random forest model based on age, ultrasound RI, progesterone, PAPP-A, ultrasound MSD/CRL ratio, and VEGF index can help clinicians identify the risk of embryonic developmental arrest.
期刊介绍：
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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