Prediction of vaginal birth after cesarean delivery in Chinese parturients
There is an urgent need in China to better predict vaginal birth after cesarean (VBAC) to face the challenge of the second child policy. We aimed to validate a widely used VBAC prediction model (Grobman’s model) and a modified version of this model in a Chinese population. In this retrospective coho...
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description | There is an urgent need in China to better predict vaginal birth after cesarean (VBAC) to face the challenge of the second child policy. We aimed to validate a widely used VBAC prediction model (Grobman’s model) and a modified version of this model in a Chinese population. In this retrospective cohort study, 444 women with one cesarean delivery and at least one subsequent attempt for a trial of labor in Nanjing, China were included. The considered potential VBAC predictors included Grobman’s background variables and five new variables. Overall, a total of 370 women had VBAC, with a success rate of 83.3%. The new background variables “maternal height” and “estimated fetal weight” were considered as two additional predictors for VBAC. The AUC of Grobman’s model was 0.831 (95%CI = 0.775–0.886) while the AUC of our modified model with two new variables added was 0.857 (sensitivity = 72.2%, specificity = 83.8%). However, the difference between the AUC of the two models was not significant (Z = −1.69,
P
= 0.091). We confirmed that Grobman’s model was accepted in the Chinese population. A modified model that is supplemented with maternal height and estimated fetal weight needs to be further studied in the Chinese population. |
doi_str_mv | 10.1038/s41598-018-21488-6 |
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P
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P
= 0.091). We confirmed that Grobman’s model was accepted in the Chinese population. 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Song, Xuejing ; Ding, Hongjuan ; Shen, Xiaofeng ; Shen, Rong ; Hu, Ling-qun ; Long, Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c522t-ab8f4bd73dd5f614bf1f2cc0142442fb30ef77d0f2feaed69848ab3fad47c8233</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>692/499</topic><topic>692/700/478/174</topic><topic>Birth</topic><topic>Cesarean section</topic><topic>Fetuses</topic><topic>Health risk assessment</topic><topic>Humanities and Social Sciences</topic><topic>multidisciplinary</topic><topic>Prediction models</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><topic>Vagina</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wen, Juan</creatorcontrib><creatorcontrib>Song, Xuejing</creatorcontrib><creatorcontrib>Ding, Hongjuan</creatorcontrib><creatorcontrib>Shen, Xiaofeng</creatorcontrib><creatorcontrib>Shen, Rong</creatorcontrib><creatorcontrib>Hu, Ling-qun</creatorcontrib><creatorcontrib>Long, Wei</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wen, Juan</au><au>Song, Xuejing</au><au>Ding, Hongjuan</au><au>Shen, Xiaofeng</au><au>Shen, Rong</au><au>Hu, Ling-qun</au><au>Long, Wei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prediction of vaginal birth after cesarean delivery in Chinese parturients</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2018-02-15</date><risdate>2018</risdate><volume>8</volume><issue>1</issue><spage>3084</spage><epage>7</epage><pages>3084-7</pages><artnum>3084</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>There is an urgent need in China to better predict vaginal birth after cesarean (VBAC) to face the challenge of the second child policy. We aimed to validate a widely used VBAC prediction model (Grobman’s model) and a modified version of this model in a Chinese population. In this retrospective cohort study, 444 women with one cesarean delivery and at least one subsequent attempt for a trial of labor in Nanjing, China were included. The considered potential VBAC predictors included Grobman’s background variables and five new variables. Overall, a total of 370 women had VBAC, with a success rate of 83.3%. The new background variables “maternal height” and “estimated fetal weight” were considered as two additional predictors for VBAC. The AUC of Grobman’s model was 0.831 (95%CI = 0.775–0.886) while the AUC of our modified model with two new variables added was 0.857 (sensitivity = 72.2%, specificity = 83.8%). However, the difference between the AUC of the two models was not significant (Z = −1.69,
P
= 0.091). We confirmed that Grobman’s model was accepted in the Chinese population. A modified model that is supplemented with maternal height and estimated fetal weight needs to be further studied in the Chinese population.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>29449665</pmid><doi>10.1038/s41598-018-21488-6</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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subjects | 692/499 692/700/478/174 Birth Cesarean section Fetuses Health risk assessment Humanities and Social Sciences multidisciplinary Prediction models Science Science (multidisciplinary) Vagina |
title | Prediction of vaginal birth after cesarean delivery in Chinese parturients |
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