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早期妊娠自然流产风险的临床预测模型的建立与内部验证。

Development and internal validation of a clinical prediction model for spontaneous abortion risk in early pregnancy.

机构信息

Imaging Diagnosis Department, Jinan Second Maternal and Child Health Hospital, Jinan City, Shandong Province, China.

Psychological Clinic, Jinan Second Maternal and Child Health Hospital, Jinan City, Shandong Province, China.

出版信息

Clinics (Sao Paulo). 2023 Dec 15;79:100318. doi: 10.1016/j.clinsp.2023.100318. eCollection 2024.

DOI:10.1016/j.clinsp.2023.100318
PMID:38103265
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10770515/
Abstract

OBJECTIVE

This study aimed to develop and internally validate a prediction model for estimating the risk of spontaneous abortion in early pregnancy.

METHODS

This prospective cohort study included 9,895 pregnant women who received prenatal care at a maternal health facility in China from January 2021 to December 2022. Data on demographics, medical history, lifestyle factors, and mental health were collected. A multivariable logistic regression analysis was performed to develop the prediction model with spontaneous abortion as the outcome. The model was internally validated using bootstrapping techniques, and its discrimination and calibration were assessed.

RESULTS

The spontaneous abortion rate was 5.95% (589/9,895) 1. The final prediction model included nine variables: maternal age, history of embryonic arrest, thyroid dysfunction, polycystic ovary syndrome, assisted reproduction, exposure to pollution, recent home renovation, depression score, and stress score 1. The model showed good discrimination with a C-statistic of 0.88 (95% CI 0.87‒0.90) 1, and its calibration was adequate based on the Hosmer-Lemeshow test (p = 0.27).

CONCLUSIONS

The prediction model demonstrated good performance in estimating spontaneous abortion risk in early pregnancy based on demographic, clinical, and psychosocial factors. Further external validation is recommended before clinical application.

摘要

目的

本研究旨在开发并内部验证一种预测模型,以估计早期妊娠自然流产的风险。

方法

本前瞻性队列研究纳入了 2021 年 1 月至 2022 年 12 月在中国一家妇幼保健机构接受产前保健的 9895 名孕妇。收集了人口统计学、病史、生活方式因素和心理健康数据。采用多变量逻辑回归分析建立以自然流产为结局的预测模型。采用自举技术对模型进行内部验证,并评估其判别能力和校准度。

结果

自然流产率为 5.95%(589/9895)。最终的预测模型包括 9 个变量:母亲年龄、胚胎停育史、甲状腺功能障碍、多囊卵巢综合征、辅助生殖、暴露于污染、近期家庭装修、抑郁评分和压力评分。模型具有良好的判别能力,C 统计量为 0.88(95%CI 0.87-0.90),Hosmer-Lemeshow 检验表明校准适度(p=0.27)。

结论

该预测模型基于人口统计学、临床和社会心理因素,在估计早期妊娠自然流产风险方面表现出良好的性能。建议在临床应用前进行进一步的外部验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd69/10770515/358853303ceb/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd69/10770515/a33caf81872b/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd69/10770515/358853303ceb/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd69/10770515/a33caf81872b/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd69/10770515/358853303ceb/gr2.jpg

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