Volume 22 Issue 4
Apr.  2024
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KONG Wencui, ZHANG Yaojia, LIU Mingsong. Analysis on the construction of early missed abortion prediction model based on ultrasonic characteristics[J]. Chinese Journal of General Practice, 2024, 22(4): 651-655. doi: 10.16766/j.cnki.issn.1674-4152.003472
Citation: KONG Wencui, ZHANG Yaojia, LIU Mingsong. Analysis on the construction of early missed abortion prediction model based on ultrasonic characteristics[J]. Chinese Journal of General Practice, 2024, 22(4): 651-655. doi: 10.16766/j.cnki.issn.1674-4152.003472

Analysis on the construction of early missed abortion prediction model based on ultrasonic characteristics

doi: 10.16766/j.cnki.issn.1674-4152.003472
Funds:

 2023KY1183

  • Received Date: 2023-10-18
    Available Online: 2024-05-29
  •   Objective  Ultrasound features can be used to predict early missed abortion, but there is no research to explain the value of transvaginal ultrasound features in predicting early missed abortion in different gestational weeks, so this study established a prediction model of early missed abortion based on ultrasound features and analyzed its prediction efficiency.  Methods  A total of 251 pregnant women diagnosed as intrauterine singleton pregnancy by transvaginal ultrasound from January 2021 to February 2022 in Huzhou Maternal and Child Health Hospital were included as the research objects. The gestational sac (GS), yolk sac (YS) diameter, crown-rump length (CRL) and fetal heart rate (HR) were detected by the ultrasound until the 10th week of pregnancy. Two hundred and fifty-one patients were followed up and recorded the incidence of missed abortion in 11-12 weeks and the levels of GS, YS, CRL and HR. Logistic regression data package in SPSS 22.0 software was used to screen the influencing factors of early missed abortion, and a logistic regression prediction model was constructed to draw ROC curve to analyze the prediction efficiency.  Results  Pregnant women were divided into abortion group (43 cases) and continued pregnancy group (208 cases) according to whether the patients had early missed abortion. The results of multivariate logistic regression showed that testosterone (OR=0.452), estradiol (OR=1.422) and progesterone (OR=1.442) were all predictors of early missed abortion (P < 0.05). The prediction model based on clinical features predicted the area under the curve of early missed abortion was 0.815, the prediction model of 6-week ultrasound characteristics was 0.801, the prediction model of 7-week ultrasound characteristics was 0.926, the prediction model of 8-week ultrasound characteristics was 0.906, the prediction model of 9-week ultrasound characteristics was 0.883 and the prediction model of 10-week ultrasound characteristics was 0.924. According to Delong analysis, the area under the curve of the ultrasonic feature prediction model at the 7th and 10th weeks of pregnancy is higher than that of the prediction model based on clinical features (P < 0.05).  Conclusion  The prediction model based on ultrasound characteristics of 6-10 weeks can be used to predict missed abortion in 11-12 weeks of pregnancy, but the prediction value of the prediction model based on ultrasound characteristics of 7-week and 10-week of pregnancy are higher than that based on clinical characteristics, and the prediction value of other pregnancy ultrasound characteristics prediction models is equivalent to that based on clinical characteristics, among which YS is the strongest ultrasound characteristic index to predict early missed abortion.

     

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