Rueangket Ploywarong, Rittiluechai Kristsanamon
Department of Obstetrics and Gynecology, Phramongkutklao Hospital, Bangkok, Thailand.
Front Med (Lausanne). 2021 Apr 29;8:646258. doi: 10.3389/fmed.2021.646258. eCollection 2021.
Ectopic pregnancy (EP) is a serious condition. Delayed diagnosis could lead to life-threatening outcomes. The study aimed to develop a diagnostic predictive model for EP to approach suspected cases with prompt intervention before the rupture occurred. A retrospective cross-sectional study enrolled 347 pregnant women presenting first-trimester complications (abdominal pain or vaginal bleeding) with diagnosis suspected of pregnancy of unknown location, who were eligible and underwent chart review. The data including clinical risk factors, signs and symptoms, serum human chorionic gonadotropin (hCG), and ultrasound findings were analyzed. The statistical predictive score was developed by performing logistic regression analysis. The testing data of 30 patients were performed to test the validation of predictive scoring. From a total of 22 factors, logistic regression method-derived scoring model was based on five potent factors (history of pelvic inflammatory disease, current use of emergency pills, cervical motion tenderness, serum hCG ≥1,000 mIU/ml, and ultrasound finding of adnexal mass) using a cutoff score ≥3. This predictive index score was able to determine ectopic pregnancy with an accuracy of 77.8% [95% confidence interval (CI) = 73.1-82.1], specificity of 91.0% (95% CI = 62.1-72.0), sensitivity of 67.0% (95% CI = 88.0-94.0), and area under the curve of 0.906 (95% CI = 0.875-0.937). In the validation group, no patient with negative result of this score had an EP. Statistical predictive score was derived with high accuracy and applicable performance for EP diagnosis. This score could be used to support clinical decision making in routine practice for management of EP.
异位妊娠（EP）是一种严重的病症。诊断延迟可能导致危及生命的后果。本研究旨在开发一种用于EP的诊断预测模型，以便在破裂发生前对疑似病例进行及时干预。一项回顾性横断面研究纳入了347例出现孕早期并发症（腹痛或阴道出血）且诊断为妊娠位置不明的孕妇，这些孕妇符合条件并接受了病历审查。对包括临床危险因素、体征和症状、血清人绒毛膜促性腺激素（hCG）以及超声检查结果在内的数据进行了分析。通过进行逻辑回归分析得出统计预测评分。对30例患者的测试数据进行分析以检验预测评分的有效性。在总共22个因素中，基于逻辑回归方法得出的评分模型是基于五个有效因素（盆腔炎病史、当前使用紧急避孕药、宫颈举痛、血清hCG≥1000 mIU/ml以及附件包块的超声检查结果），截断分数≥3。该预测指数评分能够以77.8%的准确率[95%置信区间（CI）= 73.1 - 82.1]、91.0%的特异性（95% CI = 62.1 - 72.0）、67.0%的敏感性（95% CI = 88.0 - 94.0）以及0.906的曲线下面积（95% CI = 0.875 - 0.937）来确定异位妊娠。在验证组中，该评分结果为阴性的患者均未发生异位妊娠。统计预测评分具有较高的准确性和适用于异位妊娠诊断的性能。该评分可用于支持日常临床实践中异位妊娠管理的临床决策。
