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单胎妊娠低出生体重风险预测模型,该模型源自双绒毛膜双胎妊娠。

A prediction model of low birthweight risk in singleton pregnancies reduced from dichorionic twin pregnancies.

作者信息

Tang Minyue, Li Qingfang, Wang Guiquan, Xu Jiayu, Sun Saijun, Zhu Yimin

机构信息

Department of Reproductive Endocrinology, School of Medicine, Women's HospitalZhejiang UniversityShangcheng District, 1 Xueshi Road, Hangzhou, 310006, China.

Key Laboratory of Women's Reproductive Health of Zhejiang Province, School of Medicine, Women's Hospital, Zhejiang University, Hangzhou, China.

出版信息

Reprod Biol Endocrinol. 2025 Jun 5;23(1):86. doi: 10.1186/s12958-025-01419-7.

Abstract

BACKGROUND

The incidence of twin pregnancies has risen in recent decades, which is mainly attributable to assisted reproduction technology. Fetal reduction (FR) can significantly reduce the risk of low birthweight (LBW) in twins; however, the LBW risk is higher in singletons reduced from twins than that in primary singletons. Factors including maternal factors and FR timing may affect the LBW risk after FR, but there are no relevant prediction models reported to date. Our main study objective was to develop a nomogram to predict LBW risk in singleton pregnancies reduced from dichorionic (DC) twins.

METHODS

We retrospectively reviewed and analysed data from women with DC twin pregnancies who underwent FR at Women's Hospital School of Medicine, Zhejiang University between July 2005 and August 2021. Least absolute shrinkage and selection operator (LASSO) regression was used to identify relevant variables associated with LBW. A nomogram was constructed and receiver operating characteristic curve, calibration curves, and decision clinical analysis were used for model performance assessment and visualization. The model was evaluated using cohorts produced by 500 resampling bootstrap analysis to test its stability.

RESULTS

A total of 471 patients were enrolled in the analysis. Finally, seven independent predictive factors for LBW were identified and integrated to construct the nomogram, including maternal height, nulliparous, conception method, reasons for FR, gestational age at FR, gestational diabetes, and pregnancy hypertensive disease. The area under the receiver operating characteristic curve of our prediction model was 0.793, which was validated in internal confirmation (0.762) using bootstrap analysis. The nomogram had well-fitted calibration curves. Decision curve analysis demonstrated that the nomogram was clinically useful.

CONCLUSION

We first developed a reliable predictive nomogram for the risk of LBW in DC twin pregnancies reduced to singleton pregnancies, providing a useful guide for clinicians and patients in making appropriate decisions regarding FR.

摘要

背景

近几十年来双胎妊娠的发生率有所上升,这主要归因于辅助生殖技术。减胎术(FR)可显著降低双胎低出生体重(LBW)风险;然而,双胎减为单胎后的低出生体重风险高于初产单胎。包括母体因素和减胎术时机在内的因素可能会影响减胎术后的低出生体重风险,但迄今为止尚无相关预测模型报道。我们的主要研究目标是开发一种列线图,以预测双绒毛膜(DC)双胎减为单胎妊娠后的低出生体重风险。

方法

我们回顾性分析了2005年7月至2021年8月在浙江大学医学院附属妇产科医院接受减胎术的双绒毛膜双胎妊娠女性的数据。采用最小绝对收缩和选择算子(LASSO)回归来识别与低出生体重相关的变量。构建列线图,并使用受试者操作特征曲线、校准曲线和决策临床分析进行模型性能评估和可视化。使用500次重采样自举分析产生的队列对模型进行评估,以测试其稳定性。

结果

共有471例患者纳入分析。最终,确定了7个低出生体重的独立预测因素并整合以构建列线图,包括母亲身高、未生育、受孕方式、减胎原因、减胎时的孕周、妊娠期糖尿病和妊娠高血压疾病。我们预测模型的受试者操作特征曲线下面积为0.793,在使用自举分析的内部验证(0.762)中得到验证。列线图具有拟合良好的校准曲线。决策曲线分析表明该列线图具有临床实用性。

结论

我们首次开发了一种可靠的预测列线图,用于预测双绒毛膜双胎减为单胎妊娠后的低出生体重风险,为临床医生和患者在减胎术的适当决策方面提供了有用的指导。

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