Construction of a prediction model for preterm birth risk
WANG Qiong1, CHEN Danqing2, WEI Yili1, QIAN Fangfang1
1. Zhejiang University School of Medicine, Hangzhou, Zhejiang 310000, China; 2. Obstetrics and Gynecology Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310000, China
Abstract：Objective To construct a prediction model for preterm birth risk among pregnant women, so as to provide the reference for screening high-risk population and preventing preterm birth. Methods Pregnant women who received antenatal examination and delivered at the Women's Hospital, School of Medicine, Zhejiang University from January 1 to December 31, 2019 were selected as the study subjects, among them, 80% were included in the modeling group, and 20% were included in the validation group. Demographic and clinical information were collected. A multivariable logistic regression model was used to analyze the predictive factors of preterm birth risk in the modeling group, and a preterm birth risk prediction model was established based on the OR values of predictive factors. The model was validated with the data from the validation group. The Youden index was used to determine the critical score for predicting preterm birth risk. The prediction performance of the model was evaluated using the receiver operating characteristic (ROC) curve. Results A total of 15 197 pregnant women were surveyed, including 12 131 pregnant women in the observation group and 3 066 pregnant women in the validation group. There was no statistically significant difference in age, education level and gravidity between the two groups of pregnant women (all P<0.05). Multivariable logistic regression analysis identified the number of pregnancies, education level, place of residence, hypertension, diabetes, history of preterm birth, twin-pregnancy, placenta praevia, and gestational hypertension as risk prediction factors for preterm birth risk among pregnant women. The risk score system for preterm birth was established as follows: >2 pregnancies (2 points), high school education or below (4 points), college degree or above (-4 points), rural residence (5 points), hypertension (7 points), diabetes (11 points), history of preterm birth (11 points), twin-pregnancy (28 points), placenta previa (19 points), and gestational hypertension (12 points). The total score of the preterm birth risk scoring system ranged from -4 to 99 points. When the critical score was 8 points, the Youden index was the highest at 0.480, with an area under the ROC curve of 0.749 (95%CI: 0.732-0.767), a sensitivity of 0.610, and a specificity of 0.886, indicating good prediction performance of the model. Conclusion The preterm birth risk prediction model established in this study based on demographic and clinical characteristics of pregnant women can effectively predict the risk of preterm birth among pregnant women.
[1] CHAWANPAIBOON S,VOGEL J P,MOLLER A B,et al.Global,regional,and national estimates of levels of preterm birth in 2014:a systematic review and modelling analysis[J].Lancet Glob Health,2019,7(1):37-46. [2] JONES A J,EKE U A,EKE A C.Prediction and prevention of preterm birth in pregnant women living with HIV on antiretroviral therapy[J].Expert Rev Anti Infect Ther,2022,20(6):837-848. [3] 陈桂儿,周金英.单胎妊娠自发性早产的影响因素研究[J].预防医学,2024,36(3):251-254. [4] OSKOVI KAPLAN Z A,OZGU-ERDINC A S.Prediction of preterm birth:maternal characteristics,ultrasound markers,and biomarkers:an updated overview[J/OL].J Pregnancy,2018[2024-06-23].http://doi.org/10.1155/2018/8367571. [5] SWEET D G,CARNIELLI V P,GREISEN G,et al.European Consensus Guidelines on the Management of Respiratory Distress Syndrome:2022 update[J].Neonatology,2023,120(1):3-23. [6] 蓝仙梅,罗霞,郑晓红,等.丽水市单胎活产儿早产的影响因素分析[J].预防医学,2021,33(3):313-316. [7] SCHAAF J M,RAVELLI A C,MOL B W,et al.Development of a prognostic model for predicting spontaneous singleton preterm birth[J].Eur J Obstet Gynecol Reprod Biol,2012,164(2):150-155. [8] 于永中,李天麟.GB 3869—83 中华人民共和国国家标准体力劳动强度分级[J].化工劳动保护,1999,20(5/6):15-16. [9] OFTEDAL A M,BUSTERUD K,IRGENS L M,et al.Socio-economic risk factors for preterm birth in Norway 1999-2009[J].Scand J Public Health,2016,44(6):587-92. [10] MARGERISON C E,LUO Z H,LI Y,Economic conditions during pregnancy and preterm birth:a maternal fixed-effects analysis[J].Paediatr Perinat Epidemiol,2019,33(2):154-161. [11] 王飞雪,丁悦虹,许凌.浙江省孕前优生健康检查结果分析[J].预防医学,2019,31(7):742-743,747. [12] WEI Y M,XU Q,YANG H X,et al.Preconception diabetes mellitus and adverse pregnancy outcomes in over 6.4 million women:a population-based cohort study in China[J].PLoS Med,2019,16(10):1-15. [13] ALLEN A J,SNOWDEN J M,LAU B,et al.Type-2 diabetes mellitus:does prenatal care affect outcomes?[J].J Matern Fetal Neonatal Med,2018,31(1):93-97. [14] MENZIES R,LI A L K,MURPHY K E,et al.Risk of singleton preterm birth after prior twin preterm birth:a cohort study[J].J Matern Fetal Neonatal Med,2020,33(21):3602-3607. [15] FUCHS F,SENAT M V.Multiple gestations and preterm birth[J].Semin Fetal Neonatal Med,2016,21(2):113-120. [16] TAKAI I U,SAYYADI B M,GALADANCI H S.Antepartum hemorrhage:a retrospective analysis from a Northern Nigerian teaching hospital[J].Int J Appl Basic Med Res,2016,7(2):112-116. [17] PREMKUMAR A,HENRY D E,MOGHADASSI M,et al.The interaction between maternal race/ethnicity and chronic hypertension on preterm birth[J/OL].Am J Obstet Gynecol,2016,215[2024-06-23].https://doi.org/10.1016/j.ajog.2016.08.019. [18] DAVIES E L,BELL J S,BHATTACHARYA S.Preeclampsia and preterm delivery:a population-based case-control study[J].Hypertens Pregnancy,2016,35(4):510-519. [19] YANG Y Y,LE RAY I,ZHU J,et al.Preeclampsia prevalence,risk factors,and pregnancy outcomes in Sweden and China[J/OL].JAMA Netw Open,2021,4(5)[2024-06-23].https://doi.org/10.1001/jamanetworkopen.2021.8401. [20] CELIK E,TO M,GAJEWSKA K,et al.Cervical length and obstetric history predict spontaneous preterm birth: development and validation of a model to provide individualized risk assessment[J].Ultrasound Obstet Gynecol,2008,31(5):549-554.
