Qin Zhengwen, Qiu Yamin, Lin Jie, Yang Yi, Hao Li, He Lina
Department of Obstetrics and Gynecology, Zigong Maternal and Child Health Hospital, Zigong City, Sichuan Province, People's Republic of China.
Department of Reproductive Health and Infertility, Zigong Maternal and Child Health Hospital, No.49, Wong Tong Road, Longjing Street, Daan District, Zigong City, 643000, Sichuan Province, People's Republic of China.
Sci Rep. 2025 Jun 4;15(1):19637. doi: 10.1038/s41598-025-02990-0.
To identify the factors affecting adverse reproductive outcomes in TPOAb-positive patients and to establish a predictive model based on these factors to assess the risk of adverse reproductive outcomes in patients. A retrospective cohort study was conducted, including 326 TPOAb-positive female patients who visited the reproductive medicine clinic of our hospital from January 2020 to December 2022. Patients were divided into groups with adverse reproductive outcomes and without adverse reproductive outcomes based on clinical outcomes. Data analysis was performed using SPSS software version 26.0 and R software, and independent risk factors for adverse reproductive outcomes were identified through univariate and multivariate logistic regression analysis, followed by the construction of a nomogram predictive model. The predictive performance of the model was assessed using the ROC curve. Additionally, a subgroup analysis was conducted within the adverse reproductive outcomes group. Logistic regression analyses were performed for the three subgroups: recurrent miscarriage, repeated implantation failure, and no usable embryos, to explore specific risk factors for each subgroup and compare the performance of predictive models for each subgroup. Univariate analysis showed that age, AMH levels, TPOAb concentration, TSH levels, and endometriosis are significant factors affecting adverse reproductive outcomes (P < 0.05). Multivariate logistic regression analysis further confirmed these factors as independent risk factors for adverse reproductive outcomes. The established nomogram predictive model showed good predictive performance in both the training set (AUC = 0.901) and the validation set (AUC = 0.858). Subgroup analysis showed that TSH levels, TPOAb concentration, age, AMH levels, and endometriosis were common risk factors for the three groups, but their weights differed. The nomogram model demonstrated the best predictive performance in the RIF group (AUC = 0.926), while its predictive performance was relatively lower in the RPL group (AUC = 0.869). This study successfully established a nomogram predictive model for adverse reproductive outcomes in TPOAb-positive patients. Through subgroup analysis, we identified the specific risk factors and predictive performance for subgroups of recurrent miscarriage, repeated implantation failure, and unavailable embryos, providing a reference for precise clinical assessment and intervention.
为了确定影响TPOAb阳性患者不良生殖结局的因素，并基于这些因素建立预测模型以评估患者不良生殖结局的风险。进行了一项回顾性队列研究，纳入了2020年1月至2022年12月期间到我院生殖医学门诊就诊的326例TPOAb阳性女性患者。根据临床结局将患者分为有不良生殖结局组和无不良生殖结局组。使用SPSS 26.0软件和R软件进行数据分析，通过单因素和多因素逻辑回归分析确定不良生殖结局的独立危险因素，随后构建列线图预测模型。使用ROC曲线评估模型的预测性能。此外，在不良生殖结局组内进行了亚组分析。对复发性流产、反复种植失败和无可利用胚胎这三个亚组进行逻辑回归分析，以探索每个亚组的特定危险因素，并比较每个亚组预测模型的性能。单因素分析显示，年龄、AMH水平、TPOAb浓度、TSH水平和子宫内膜异位症是影响不良生殖结局的显著因素（P＜0.05）。多因素逻辑回归分析进一步证实这些因素是不良生殖结局的独立危险因素。所建立的列线图预测模型在训练集（AUC = 0.901）和验证集（AUC = 0.858）中均表现出良好的预测性能。亚组分析显示，TSH水平、TPOAb浓度、年龄、AMH水平和子宫内膜异位症是三组的共同危险因素，但权重不同。列线图模型在反复种植失败组（AUC = 0.926）中表现出最佳的预测性能，而在复发性流产组中其预测性能相对较低（AUC = 0.869）。本研究成功建立了TPOAb阳性患者不良生殖结局的列线图预测模型。通过亚组分析，我们确定了复发性流产、反复种植失败和无可利用胚胎亚组的特定危险因素和预测性能，为临床精准评估和干预提供了参考。
