Lillian H Goodman, Amanda A Allshouse, Ann M Bruno, Torri D Metz
{"title":"验证剖宫产后阴道分娩预测模型,不考虑曾有两次剖宫产经历者的种族和民族因素。","authors":"Lillian H Goodman, Amanda A Allshouse, Ann M Bruno, Torri D Metz","doi":"10.1097/AOG.0000000000005633","DOIUrl":null,"url":null,"abstract":"<p><p>Previous models for prediction of vaginal birth after cesarean (VBAC) relied on race and ethnicity, raising concern for bias. In response, the Maternal-Fetal Medicine Units Network (MFMU) created a new prediction model without race and ethnicity for individuals with one prior cesarean delivery. We performed a secondary analysis of the MFMU Cesarean Registry database to evaluate whether the MFMU VBAC prediction model without race and ethnicity could accurately predict VBAC for individuals with two prior cesarean deliveries. Overall, 353 individuals were included and 252 (71%) had VBAC. An area under the curve for the receiver operating curve of 0.74 (95% CI, 0.69-0.80) was reported for the predicted probabilities for VBAC, indicating that the model can be used for prediction of VBAC in this population.</p>","PeriodicalId":19483,"journal":{"name":"Obstetrics and gynecology","volume":null,"pages":null},"PeriodicalIF":5.7000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11257801/pdf/","citationCount":"0","resultStr":"{\"title\":\"Validation of a Vaginal Birth After Cesarean Delivery Prediction Model Without Race and Ethnicity in Individuals With Two Prior Cesarean Deliveries.\",\"authors\":\"Lillian H Goodman, Amanda A Allshouse, Ann M Bruno, Torri D Metz\",\"doi\":\"10.1097/AOG.0000000000005633\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Previous models for prediction of vaginal birth after cesarean (VBAC) relied on race and ethnicity, raising concern for bias. In response, the Maternal-Fetal Medicine Units Network (MFMU) created a new prediction model without race and ethnicity for individuals with one prior cesarean delivery. We performed a secondary analysis of the MFMU Cesarean Registry database to evaluate whether the MFMU VBAC prediction model without race and ethnicity could accurately predict VBAC for individuals with two prior cesarean deliveries. Overall, 353 individuals were included and 252 (71%) had VBAC. An area under the curve for the receiver operating curve of 0.74 (95% CI, 0.69-0.80) was reported for the predicted probabilities for VBAC, indicating that the model can be used for prediction of VBAC in this population.</p>\",\"PeriodicalId\":19483,\"journal\":{\"name\":\"Obstetrics and gynecology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11257801/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Obstetrics and gynecology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/AOG.0000000000005633\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/6/6 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"OBSTETRICS & GYNECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Obstetrics and gynecology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/AOG.0000000000005633","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/6 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"OBSTETRICS & GYNECOLOGY","Score":null,"Total":0}
Validation of a Vaginal Birth After Cesarean Delivery Prediction Model Without Race and Ethnicity in Individuals With Two Prior Cesarean Deliveries.
Previous models for prediction of vaginal birth after cesarean (VBAC) relied on race and ethnicity, raising concern for bias. In response, the Maternal-Fetal Medicine Units Network (MFMU) created a new prediction model without race and ethnicity for individuals with one prior cesarean delivery. We performed a secondary analysis of the MFMU Cesarean Registry database to evaluate whether the MFMU VBAC prediction model without race and ethnicity could accurately predict VBAC for individuals with two prior cesarean deliveries. Overall, 353 individuals were included and 252 (71%) had VBAC. An area under the curve for the receiver operating curve of 0.74 (95% CI, 0.69-0.80) was reported for the predicted probabilities for VBAC, indicating that the model can be used for prediction of VBAC in this population.
期刊介绍:
"Obstetrics & Gynecology," affectionately known as "The Green Journal," is the official publication of the American College of Obstetricians and Gynecologists (ACOG). Since its inception in 1953, the journal has been dedicated to advancing the clinical practice of obstetrics and gynecology, as well as related fields. The journal's mission is to promote excellence in these areas by publishing a diverse range of articles that cover translational and clinical topics.
"Obstetrics & Gynecology" provides a platform for the dissemination of evidence-based research, clinical guidelines, and expert opinions that are essential for the continuous improvement of women's health care. The journal's content is designed to inform and educate obstetricians, gynecologists, and other healthcare professionals, ensuring that they stay abreast of the latest developments and best practices in their field.