| 基于阴道微生态相关指标构建复发性流产风险预测模型 |
| 投稿时间：2025-01-28 修订日期：2025-03-28 点此下载全文 |
| 引用本文：余晓娟,董赟芳,胡万芹.基于阴道微生态相关指标构建复发性流产风险预测模型[J].医学研究杂志,2025,54(8):68-73 |
| DOI：
10.11969/j.issn.1673-548X.2025.08.012 |
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| 基金项目:国家自然科学基金资助项目(82020694) |
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| 中文摘要:目的 探讨复发性流产(recurrent spontaneous abortion,RSA)患者妊娠发生不良结局的影响因素,构建列线图风险预测模型,并进行验证。方法 选取2021年3月～2024年3月昆明医科大学第二附属医院收治的219例RSA患者,根据妊娠结局分为妊娠结局不良组(n=129)与妊娠结局良好组(n=90),收集病例资料。结果 两组在白细胞酯酶(leukocyte esterase,LE)阳性/阴性、过氧化氢(hydrogen peroxide,H2O2)阳性/阴性、细菌性阴道炎(bacterial vaginosis,BV)、分娩孕周方面比较,差异均有统计学意义(P<0.05)。多因素Logistic回归分析结果显示,LE阳性(OR=10.677)、H2O2阴性(OR=3.796)、BV感染(OR=4.827)是RSA患者不良妊娠结局的危险因素,而分娩孕周增加(OR=0.294)是保护因素。基于此构建的列线图预测模型曲线下面积(area under of curve,AUC)为0.913。验证结果显示,该模型区分度、拟合优度、校准度及临床决策净收益均较高。结论阴道微生态失衡及阴道酶学改变与RSA患者的不良妊娠结局有相关性,基于LE、H2O2、BV、分娩孕周构建的列线图预测模型可方便、有效地评估RSA患者不良妊娠结局的发生率,为早期识别高风险患者,预防RSA的发生和发展提供依据。 |
| 中文关键词:复发性流产 妊娠结局 阴道微生态 影响因素 列线图 |
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| Construction of A Risk Prediction Model for Recurrent Spontaneous Abortion Based on the Relevant Indicators of Vaginal Microecology. |
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| Abstract:Objective To investigate the influencing factors of adverse pregnancy outcomes in patients with recurrent spontaneous abortion (RSA), construct and validate the Nomogram risk prediction model. Methods A total of 219 patients with RSA admitted to the Second Affiliated Hospital of Kunming Medical University from March 2021 to March 2024 were selected and divided into the poor pregnancy outcome group (n=129) and the good pregnancy outcome group (n=90) according to the pregnancy outcome. The case data was collected. Results There were statistically significant differences in the leukocyte esterase (LE) positive/negative, hydrogen peroxide (H2O2) positive/negative, bacterial vaginosis (BV), and gestational week of delivery between two groups (P<0.05). The results of multivariate Logistic regression analysis showed that LE positivity (OR=10.677), H2O2 negativity (OR=3.796), and BV infection (OR=4.827) were the risk factors for adverse pregnancy outcomes in RSA patients, whereas an increase in the gestational week of delivery (OR=0.294) was a protective factor. The area under the curve (AUC) of the Nomogram prediction model constructed based on this was 0.913. The validation results showed that the model had high discrimination, goodness of fit, calibration and net benefit for clinical decision-making. Conclusion Vaginal microecological imbalance and vaginal enzymatic alterations are correlate with adverse pregnancy outcomes in patients with RSA. The Nomogram prediction model constructed on the basis of LE, H2O2, BV and gestational week of delivery can conveniently and efficiently assess the probability of adverse pregnancy outcomes in patients with RSA, and provide a basis for the early identification of high-risk patients and the prevention of the occurrence and development of RSA. |
| keywords:Recurrent spontaneous abortion Pregnancy outcomes Vaginal microecology Influencing factors Nomogram |
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