McFarlin Barbara L, Liu Yuxuan, Villegas-Downs Michelle, Mohammadi Mehrdad, Simpson Douglas G, Han Aiguo, O'Brien William D
Department of Human Development Nursing Science, UIC College of Nursing, University of Illinois Chicago, Chicago, IL, USA.
Department of Statistics, University of Illinois Urbana-Champaign, Champaign, IL, USA.
Ultrasound Med Biol. 2023 May;49(5):1145-1152. doi: 10.1016/j.ultrasmedbio.2022.12.018. Epub 2023 Feb 3.
Predicting women at risk for spontaneous pre-term birth (sPTB) has been medically challenging because of the lack of signs and symptoms of pre-term birth until interventions are too late. We hypothesized that prediction of the sPTB risk level is enhanced when using both historical clinical (HC) data and quantitative ultrasound (QUS) data compared with using only HC data. HC data defined herein included birth history prior to that of the current pregnancy as well as, from the current pregnancy, a clinical cervical length assessment and physical examination data.
The study population included 248 full-term births (FTBs) and 26 sPTBs. QUS scans (Siemens S2000 and MC9-4) were performed by registered diagnostic medical sonographers using a standard cervical length approach. Two cervical QUS scans were conducted at 20 ± 2 and 24 ± 2 wk of gestation. Multiple QUS features were evaluated from calibrated raw radiofrequency backscattered ultrasonic signals. Two statistical models designed to determine sPTB risk were compared: (i) HC data alone and (ii) combined HC and QUS data. Model comparisons included a likelihood ratio test, cross-validated receiver operating characteristic area under the curve, sensitivity and specificity. The study's birth outcomes were only FTBs and sPTBs; medically induced pre-term births were not included.
Combined HC and QUS data identified women at risk of sPTB with better AUC (0.68, 95% confidence interval [CI]: 0.57-0.78) compared with HC data alone (0.53, 95% CI: 0.40-0.66) and HC data + cervical length at 18-20 wk of gestation (average AUC = 0.51, 95% CI: 0.38-0.64). A likelihood ratio test for significance of QUS features in the classification model was highly statistically significant (p < 0.01).
Even with only 26 sPTBs among 274 births, value was added in predicting sPTB when QUS data were included with HC data.
预测自发性早产(sPTB)风险的女性一直是医学上的难题,因为在干预措施为时已晚之前,早产没有明显的体征和症状。我们假设,与仅使用历史临床(HC)数据相比,同时使用历史临床(HC)数据和定量超声(QUS)数据时,sPTB风险水平的预测效果会更好。本文定义的HC数据包括本次妊娠之前的生育史,以及本次妊娠期间的临床宫颈长度评估和体格检查数据。
研究人群包括248例足月分娩(FTB)和26例sPTB。由注册诊断医学超声医师使用标准宫颈长度测量方法进行QUS扫描(西门子S2000和MC9-4)。在妊娠20±2周和24±2周时进行两次宫颈QUS扫描。从校准后的原始射频反向散射超声信号中评估多个QUS特征。比较了两个用于确定sPTB风险的统计模型:(i)仅HC数据和(ii)HC数据与QUS数据相结合。模型比较包括似然比检验、交叉验证的曲线下受试者工作特征面积、敏感性和特异性。该研究的分娩结局仅包括FTB和sPTB;不包括医学诱导的早产。
与仅使用HC数据(0.53,95%置信区间[CI]:0.40-0.66)以及HC数据+妊娠18-20周时的宫颈长度(平均AUC=0.51,95%CI:0.38-0.64)相比,HC数据与QUS数据相结合能更好地识别有sPTB风险的女性(AUC为0.68,95%CI:0.57-0.78)。分类模型中QUS特征显著性的似然比检验具有高度统计学意义(p<0.01)。
即使在274例分娩中只有26例sPTB,当QUS数据与HC数据一起使用时,在预测sPTB方面仍有价值。