Liu An-Hao, Xu Bin, Li Xiu-Wen, Yu Yue-Wen, Guan Hui-Xin, Sun Xiao-Lu, Lin Yan-Zhen, Zhang Li-Li, Zhuo Xian-Di, Li Jia, Chen Wen-Qun, Hu Wen-Feng, Ye Ming-Zhu, Huang Xiu-Min, Chen Xun
Department of Obstetrics and Gynecology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Department of Basic Medicine, School of Medicine, Xiamen University, Xiamen, China.
PLoS One. 2024 Dec 20;19(12):e0315025. doi: 10.1371/journal.pone.0315025. eCollection 2024.
As the first model in predicting the failure of early medical abortion (EMA) was inefficient, this study aims to develop and validate a risk assessment model for predicting the failure of EMAs more accurately in a clinical setting.
The derivation cohort was obtained from a comprehensive systematic review and meta-analysis. The clinically significant risk factors were identified and combined with their corresponding odds ratios to establish a risk assessment model. The risk factors were assigned scores based on their respective weightings. The model's performance was evaluated by an external validation cohort obtained from a tertiary hospital. The outcome was defined as the incidence of EMA failure.
A total of 126,420 patients who had undergone medical abortions were included in the systematic review and meta-analysis, and the pooled failure rate was 6.7%. The final risk factors consisted of gestational age, maternal age, parity, previous termination of pregnancy, marital status, type of residence, and differences between gestational age calculated using the last menstrual period and that measured via ultrasound. The risk factors were assigned scores based on their respective weightings, with a maximum score of 19. The clinical prediction model exhibited a good discrimination, as validated by external verification (402 patients) with an area under the curve of 0.857 (95% confidence interval 0.804-0.910). The optimal cutoff value was determined to be 13.5 points, yielding a sensitivity of 83.3% and specificity of 75.4%.
This study effectively establishes a simple risk assessment model including seven routinely available clinical parameters for predicting EMA failure. In preliminary validation, this model demonstrates good performance in terms of predictive efficiency, accuracy, calibration, and clinical benefit. However, more research and validation are warranted for future application.
CRD42023485388.
由于首个预测早期药物流产(EMA)失败的模型效率不高,本研究旨在开发并验证一种风险评估模型,以便在临床环境中更准确地预测EMA失败。
推导队列来自全面的系统评价和荟萃分析。确定具有临床意义的风险因素,并将其与相应的比值比相结合,以建立风险评估模型。根据各自的权重为风险因素分配分数。通过从一家三级医院获得的外部验证队列评估该模型的性能。结局定义为EMA失败的发生率。
系统评价和荟萃分析共纳入126,420例接受药物流产的患者汇总失败率为6.7%。最终的风险因素包括孕周、产妇年龄、产次、既往终止妊娠史、婚姻状况、居住类型以及根据末次月经计算的孕周与超声测量的孕周之间的差异。根据各自的权重为风险因素分配分数,最高分为19分。外部验证(402例患者)显示,临床预测模型具有良好的区分度,曲线下面积为0.857(95%置信区间0.804-0.910)。确定最佳截断值为13.5分,敏感性为83.3%特异性为75.4%。
本研究有效建立了一个简单的风险评估模型,该模型包含七个常规可用的临床参数,用于预测EMA失败。在初步验证中,该模型在预测效率、准确性、校准和临床效益方面表现良好。然而,未来应用还需要更多的研究和验证。
CRD42023485388。