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症状性双胎妊娠中自我报告的疼痛评分预测早产:一项回顾性研究。

Self-reported pain scores as a predictor of preterm birth in symptomatic twin pregnancy: a retrospective study.

机构信息

Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, South Korea.

Center for Precision Medicine, Seoul National University Hospital, Seoul, South Korea.

出版信息

BMC Pregnancy Childbirth. 2021 Jul 1;21(1):472. doi: 10.1186/s12884-021-03931-1.

Abstract

BACKGROUND

To evaluate the self-reported pain scores as a predictor of preterm birth (PTB) in symptomatic twin pregnancy and to develop a nomogram for the prediction model.

METHODS

We conducted a retrospective study of 148 cases of symptomatic twin pregnancies before 34 weeks of gestation visited at Seoul national university hospital from 2013 to 2018. With other clinical factors, self-reported pain score was evaluated by the numerical rating scale (NRS) pain scores for pain intensity. By multivariate analyses and logistic regression, we developed a prediction model for PTB within 7 days. Using the Cox proportional hazards model, the curves were plotted to show the predictability of the PTB according to NRS pain score, while adjusting the other covariates.

RESULTS

Twenty-three patients (15.5 %) delivered preterm within 7 days. By a logistic regression analysis, higher NRS pain score (OR 1.558, 95 % CI 1.093-2.221, P < 0.05), shorter cervical length (OR 3.164, 95 % CI 1.262-7.936, P < 0.05) and positive fibronectin results (OR 8.799, 95 % CI 1.101-70.330, P < 0.05) affect PTB within 7 days. Using the variables, the area under the receiver operating characteristic curve (AUROC) of the prediction model was 0.917. In addition, we developed a nomogram for the prediction of PTB within 7 days.

CONCLUSIONS

Self-reported pain scores combined with cervical length and fetal fibronectin are useful in predicting impending PTB in symptomatic twin pregnancy.

摘要

背景

评估有症状的双胎妊娠中自我报告的疼痛评分作为早产(PTB)的预测指标,并为预测模型开发列线图。

方法

我们对 2013 年至 2018 年在首尔国立大学医院就诊的 148 例有症状的双胎妊娠在 34 周前进行了回顾性研究。除其他临床因素外,自我报告的疼痛评分通过数字评分量表(NRS)的疼痛强度评分进行评估。通过多变量分析和逻辑回归,我们为 7 天内的 PTB 建立了预测模型。使用 Cox 比例风险模型,绘制曲线以显示 NRS 疼痛评分对 PTB 的预测能力,同时调整其他协变量。

结果

23 例(15.5%)在 7 天内早产。通过逻辑回归分析,较高的 NRS 疼痛评分(OR 1.558,95%CI 1.093-2.221,P<0.05)、较短的宫颈长度(OR 3.164,95%CI 1.262-7.936,P<0.05)和阳性纤维连接蛋白结果(OR 8.799,95%CI 1.101-70.330,P<0.05)影响 7 天内的 PTB。使用这些变量,预测模型的受试者工作特征曲线下面积(AUROC)为 0.917。此外,我们为预测 7 天内的 PTB 开发了一个列线图。

结论

自我报告的疼痛评分结合宫颈长度和胎儿纤维连接蛋白可用于预测有症状的双胎妊娠中即将发生的 PTB。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4e7b/8246682/59a4c585a3a1/12884_2021_3931_Fig1_HTML.jpg

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