{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T15:48:59Z","timestamp":1781279339673,"version":"3.54.1"},"reference-count":49,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:00:00Z","timestamp":1760486400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Postpartum haemorrhage is the most common complication associated with vaginal birth and a principal cause of maternal mortality. While clinical guidelines suggest that the majority of postpartum haemorrhage cases can be averted through precise prediction and scientific management that utilise assessment tools, existing tools for predicting postpartum haemorrhage in vaginal births have demonstrated inadequacies.<\/jats:p><\/jats:sec><jats:sec><jats:title>Aim<\/jats:title><jats:p>To develop a predictive model for postpartum haemorrhage in vaginal births based on machine-learning algorithms.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We selected pregnant women who gave birth vaginally at a tertiary-level obstetrics and gynaecology hospital in Shanghai, China, from July 2023 to August 2024. Multidimensional data were collected on demographic factors of pregnant women and midwives, along with their antenatal factors (e.g., previous medical history, current medical history, laboratory indicators, and psychosocial factors) and intrapartum factors (e.g., induction techniques; the first, second, and third stages of labour; and other factors). Five predictive models were constructed using machine-learning algorithms, and these models were subsequently validated and evaluated for performance. We applied the SHapley Additive exPlanations tool to conduct an interpretative analysis of the optimal model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Findings<\/jats:title><jats:p>A total of 1,225 women who underwent vaginal births were included in our final analysis, and following univariate analysis and least absolute shrinkage and selection operator regression, 13 predictive variables were incorporated into the model. The eXtreme Gradient Boosting model exhibited the most superior performance. A midwife\u2019s years of service, degree of a woman\u2019s fear of childbirth, parity, duration of the second stage of labour, episiotomy, and companionship during labour and childbirth were identified as significant predictive factors. Moreover, the midwife\u2019s years of service and their companionship during childbirth had a moderating effect, which could effectively reduce the impact of childbirth fear and prolonged labour on the risk of postpartum haemorrhage.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The postpartum haemorrhage prediction model for vaginal births developed in this study will furnish clinical midwives with a scientific and objective tool for assessing the risk of postpartum haemorrhage, thereby supporting timely risk stratification and management in the immediate postpartum period.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fmed.2025.1670987","type":"journal-article","created":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T13:56:19Z","timestamp":1760536579000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Interpretable machine-learning-based prediction of postpartum haemorrhage in normal vaginal births in Shanghai, China"],"prefix":"10.3389","volume":"12","author":[{"given":"Xiao","family":"Yao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yirong","family":"Bao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Na","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shanshan","family":"Shan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiting","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keying","family":"Huo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rong","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Ying","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,10,15]]},"reference":[{"key":"ref1","unstructured":"WHO recommendations on the assessment of postpartum blood loss and treatment bundles for postpartum haemorrhage\n          \n          \n          Geneva\n          World Health Organization\n          \n          2023"},{"key":"ref2","year":""},{"key":"ref3","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1002\/ijgo.14116","article-title":"FIGO recommendations on the management of postpartum hemorrhage","volume":"157","author":"Escobar","year":"2022","journal-title":"Int J Gynaecol Obstet"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"401","DOI":"10.3760\/cma.j.cn112141-20230223-00084","article-title":"Guidelines for the prevention and management of postpartum haemorrhage (2023)","volume":"58","year":"2023","journal-title":"Chin J Obstet Gynecol"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"e119","DOI":"10.1213\/ANE.0000000000004424","article-title":"Trends in postpartum hemorrhage in the United States from 2010 to 2014","volume":"130","author":"Reale","year":"2020","journal-title":"Anesth Analg"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1186\/1471-2393-12-108","article-title":"Trends in postpartum hemorrhage from 2000 to 2009: a population-based study","volume":"12","author":"Mehrabadi","year":"2012","journal-title":"BMC Pregnancy Childbirth"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"535","DOI":"10.3109\/00016349.2010.484044","article-title":"Cesarean vs vaginal delivery: an institutional experience","volume":"56","author":"Sharma","year":"2018","journal-title":"Acta Obstet Gynecol Scand"},{"key":"ref8","first-page":"13","article-title":"Survey on the incidence of complications of vaginal delivery in China from 2016 to 2020","volume":"38","author":"Shi","year":"2022","journal-title":"J Pract Obstet Gynaecol"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"e106","DOI":"10.1111\/1471-0528.14178","article-title":"Prevention and management of postpartum haemorrhage: green-top guideline no.52","volume":"124","year":"2017","journal-title":"Bjog"},{"key":"ref10","year":""},{"key":"ref11","first-page":"179","article-title":"Prediction and prevention of postpartum hemorrhage","author":"Jiang","year":"1994","journal-title":"Chin J Pract Gynecol Obstet"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"1308","DOI":"10.1097\/AOG.0000000000003574","article-title":"Evaluation of risk-assessment tools for severe postpartum hemorrhage in women undergoing cesarean delivery","volume":"134","author":"Kawakita","year":"2019","journal-title":"Obstet Gynecol"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"1005","DOI":"10.1111\/trf.17320","article-title":"Comparison of three antepartum risk assessment tools to predict significant postpartum hemorrhage in livebirths","volume":"63","author":"Movva","year":"2023","journal-title":"Transfusion"},{"key":"ref14","first-page":"13","article-title":"Meta-analysis of the predictive effect of postpartum hemorrhage early warning scoring form on postpartum hemorrhage","volume":"34","author":"Liu","year":"2017","journal-title":"J Nurs Chin Peoples Liberation Army"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"22620","DOI":"10.1038\/s41598-021-02198-y","article-title":"Machine learning approach for the prediction of postpartum hemorrhage in vaginal birth","volume":"11","author":"Akazawa","year":"2021","journal-title":"Sci Rep"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"1015","DOI":"10.1007\/s00404-021-06377-0","article-title":"Machine learning-based prediction of postpartum hemorrhage after vaginal delivery: combining bleeding high risk factors and uterine contraction curve","volume":"306","author":"Liu","year":"2022","journal-title":"Arch Gynecol Obstet"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"54","DOI":"10.3390\/biology12010054","article-title":"Development and validation of a predictive tool for postpartum hemorrhage after vaginal delivery: a prospective cohort study","volume":"12","author":"Bihan","year":"2022","journal-title":"Biology"},{"key":"ref18","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1002\/ijgo.13797","article-title":"Development and validation of a predictive model for severe postpartum hemorrhage in women undergoing vaginal delivery: a retrospective cohort study","volume":"157","author":"Liu","year":"2022","journal-title":"Int J Gynaecol Obstet"},{"key":"ref19","first-page":"876","article-title":"Establishment and validation of risk prediction model for postpartum hemorrhage for pregnant women \u226535 years of age in natural delivery","volume":"29","author":"Yang","year":"2023","journal-title":"Altern Ther Health Med"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1186\/s12884-024-06982-2","article-title":"Differences in maternal and perinatal outcomes between Dutch and non-western women in a midwife-led care setting: a retrospective cohort study","volume":"24","author":"Ali","year":"2024","journal-title":"BMC Pregnancy Childbirth"},{"key":"ref21","first-page":"70","article-title":"The impact of anxiety and depression in parturient women on the labour process, labour outcomes, postpartum haemorrhage and lactation","volume":"30","author":"Guo","year":"2022","journal-title":"Clin Res"},{"key":"ref22","doi-asserted-by":"publisher","first-page":"e2221","DOI":"10.1002\/nop2.2221","article-title":"Roles and challenges encountered by midwives in the management of postpartum haemorrhage following normal vaginal delivery: a scoping review","volume":"11","author":"Yao","year":"2024","journal-title":"Nurs Open"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"675","DOI":"10.1016\/j.beth.2020.05.002","article-title":"Supervised machine learning: a brief primer","volume":"51","author":"Jiang","year":"2020","journal-title":"Behav Ther"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1167\/tvst.9.2.14","article-title":"Introduction to machine learning, neural networks, and deep learning","volume":"9","author":"Choi","year":"2020","journal-title":"Transl Vis Sci Technol"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"e078378","DOI":"10.1136\/bmj-2023-078378","article-title":"TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods","volume":"385","author":"Collins","year":"2024","journal-title":"BMJ"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s10140-024-02310-5","article-title":"The incidence of vascular injuries in patients with negative cervical computed tomography (CT) following blunt trauma","author":"Aslan","year":"2025","journal-title":"Emerg Radiol"},{"key":"ref27","doi-asserted-by":"publisher","first-page":"m441","DOI":"10.1136\/bmj.m441","article-title":"Calculating the sample size required for developing a clinical prediction model","volume":"368","author":"Riley","year":"2020","journal-title":"BMJ"},{"key":"ref28","doi-asserted-by":"publisher","first-page":"1092","DOI":"10.1001\/archinte.166.10.1092","article-title":"A brief measure for assessing generalized anxiety disorder: the GAD-7","volume":"166","author":"Spitzer","year":"2006","journal-title":"Arch In-tern Med"},{"key":"ref29","first-page":"245","article-title":"The impact of anxiety in early and late pregnancy on the mode of delivery in parturient women","volume":"56","author":"Qian","year":"2021","journal-title":"Chin J Nurs"},{"key":"ref30","doi-asserted-by":"publisher","first-page":"782","DOI":"10.1192\/bjp.150.6.782","article-title":"Detection of postnatal depression. Development of the 10-item Edinburgh postnatal depression scale","volume":"150","author":"Cox","year":"1987","journal-title":"Br J Psychiatry"},{"key":"ref31","doi-asserted-by":"publisher","first-page":"453","DOI":"10.13390\/j.issn.1672-1861.2018.05.025","article-title":"Analysis of the cut-off value of the Edinburgh postnatal depression scale for prenatal depression screening in women in late pregnancy","volume":"19","author":"Fu","year":"2018","journal-title":"Chin J Clin Obstet Gynecol"},{"key":"ref32","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1111\/j.1365-2648.2010.05479.x","article-title":"Childbirth self-efficacy inventory and childbirth attitudes questionnaire: psychometric properties of Thai language versions","volume":"67","author":"Tanglakmankhong","year":"2011","journal-title":"J Adv Nurs"},{"key":"ref33","first-page":"81","article-title":"Chinese version of the childbirth fear scale and its reliability and validity","volume":"31","author":"Wei","year":"2016","journal-title":"J Nurs"},{"key":"ref34","doi-asserted-by":"publisher","first-page":"114286","DOI":"10.1016\/j.envres.2022.114286","article-title":"XGBoost model as an efficient machine learning approach for PFAS removal: effects of material characteristics and operation conditions","volume":"215","author":"Karbassiyazdi","year":"2022","journal-title":"Environ Res"},{"key":"ref35","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1002\/(SICI)1097-0258(19970228)16:4<>3.0.CO;2\u20133","article-title":"The LASSO method for variable selection in the cox model","volume":"16","author":"Tibshirani","year":"1997","journal-title":"Stat Med"},{"key":"ref36","doi-asserted-by":"publisher","first-page":"1293","DOI":"10.1016\/j.jogc.2022.10.002","article-title":"Guideline No. 431: postpartum hemorrhage and hemorrhagic shock","volume":"44","author":"Basso","year":"2022","journal-title":"J Obstet Gynaecol Can"},{"key":"ref37","doi-asserted-by":"publisher","first-page":"4633","DOI":"10.3390\/ijerph18094633","article-title":"Risk factors for postpartum hemorrhage in a Thai\u2013Myanmar border community hospital: a nested case-control study","volume":"18","author":"Thepampan","year":"2021","journal-title":"Int J Environ Res Public Health"},{"key":"ref38","doi-asserted-by":"publisher","first-page":"1096501","DOI":"10.3389\/fmed.2023.1096501","article-title":"Primary postpartum hemorrhage and associated factors among delivering women in Gedeo zone, southern Ethiopia","volume":"10","author":"Zenebe","year":"2023","journal-title":"Front Med"},{"key":"ref39","doi-asserted-by":"publisher","first-page":"304","DOI":"10.4314\/ahs.v21i1.39","article-title":"Factors that influence management of postpartum hemorrhage among midwives in a rural setting in Kenya","volume":"21","author":"Muthoni","year":"2021","journal-title":"Afr Health Sci"},{"key":"ref40","doi-asserted-by":"publisher","first-page":"1180","DOI":"10.1002\/nop2.304","article-title":"Fear of childbirth from the perspective of midwives working in hospitals in Norway: a qualitative study","volume":"6","author":"Tobiasson","year":"2019","journal-title":"Nurs Open"},{"key":"ref41","doi-asserted-by":"publisher","first-page":"1908","DOI":"10.4314\/ahs.v20i4.49","article-title":"Knowledge and barriers on correct use of modified guidelines for active management of third stage of labour: a cross sectional survey of nurse-midwives at three referral hospitals in Dar es Salaam, Tanzania","volume":"20","author":"Ramadhani","year":"2020","journal-title":"Afr Health Sci"},{"key":"ref42","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1186\/s12884-022-04804-x","article-title":"Midwives' experiences of reducing maternal morbidity and mortality from postpartum haemorrhage (PPH) in eastern Nigeria","volume":"22","author":"Kalu","year":"2022","journal-title":"BMC Pregnancy Childbirth"},{"key":"ref43","doi-asserted-by":"publisher","first-page":"e464","DOI":"10.1016\/j.wombi.2021.11.005","article-title":"Women's experiences of the second stage of labour","volume":"35","author":"H\u00e4ggsg\u00e5rd","year":"2022","journal-title":"Women Birth"},{"key":"ref44","first-page":"525","article-title":"Management of spontaneous vaginal delivery","volume":"109","author":"McKenna","year":"2024","journal-title":"Am Fam Physician"},{"key":"ref45","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1016\/j.midw.2017.12.013","article-title":"The midwifery services framework: the process of implementation","volume":"58","author":"Nove","year":"2018","journal-title":"Midwifery"},{"key":"ref46","volume-title":"The impact of childbirth fear on pregnancy outcomes","author":"Zhang","year":"2023"},{"key":"ref47","doi-asserted-by":"publisher","first-page":"S740","DOI":"10.1016\/j.ajog.2023.04.011","article-title":"The physiology and pharmacology of oxytocin in labor and in the peripartum period","volume":"230","author":"Uvn\u00e4s-Moberg","year":"2024","journal-title":"Am J Obstet Gynecol"},{"key":"ref48","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1016\/j.ejogrb.2020.11.041","article-title":"Blood type and postpartum hemorrhage by mode of delivery: a retrospective cohort study","volume":"256","author":"Burd","year":"2021","journal-title":"Eur J Obstet Gynecol Reprod Biol"},{"key":"ref49","doi-asserted-by":"publisher","first-page":"6458","DOI":"10.4103\/jfmpc.jfmpc_222_22","article-title":"Clinical spectrum and outcome of pregnancy with liver diseases - a prospective study","volume":"11","author":"Bahadur","year":"2022","journal-title":"J Family Med Prim Care"}],"container-title":["Frontiers in Medicine"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2025.1670987\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T13:56:23Z","timestamp":1760536583000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2025.1670987\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,15]]},"references-count":49,"alternative-id":["10.3389\/fmed.2025.1670987"],"URL":"https:\/\/doi.org\/10.3389\/fmed.2025.1670987","relation":{},"ISSN":["2296-858X"],"issn-type":[{"value":"2296-858X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,15]]},"article-number":"1670987"}}