Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, 410078, China.
Department of Medical Affairs, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
Sci Rep. 2017 Sep 12;7(1):11294. doi: 10.1038/s41598-017-11286-x.
In this study, a new model for predicting preterm delivery (PD) was proposed. The primary model was constructed using ten selected variables, as previously defined in seventeen different studies. The ability of the model to predict PD was evaluated using the combined measurement from these variables. Therefore, a prospective investigation was performed by enrolling 130 pregnant patients whose gestational ages varied from 17 to 28 weeks. The patients underwent epidemiological surveys and ultrasonographic measurements of their cervixes, and cervicovaginal fluid and serum were collected during a routine speculum examination performed by the managing gynecologist. The results showed eight significant variables were included in the present analysis, and combination of the positive variables indicated an increased probability of PD in pregnant patients. The accuracy for predicting PD were as follows: one positive - 42.9%; two positives - 75.0%; three positives - 81.8% and four positives - 100.0%. In particular, the combination of ≥2× positives had the best predictive value, with a relatively high sensitivity (82.6%), specificity (88.1%) and accuracy rate (79.2%), and was considered the cut-off point for predicting PD. In conclusion, the new model provides a useful reference for evaluating the risk of PD in clinical cases.
本研究提出了一种新的预测早产（PD）的模型。该模型的主要模型是使用之前在十七项不同研究中定义的十个选定变量构建的。使用这些变量的综合测量来评估模型预测 PD 的能力。因此，通过招募 130 名妊娠年龄在 17 至 28 周之间的孕妇进行了前瞻性研究。对患者进行了流行病学调查，并对其宫颈进行了超声测量，在管理妇产科医生进行常规窥镜检查时收集了宫颈阴道液和血清。结果表明，目前的分析中包括了八个显著变量，阳性变量的组合表明孕妇 PD 的可能性增加。预测 PD 的准确率如下：一个阳性-42.9%；两个阳性-75.0%；三个阳性-81.8%和四个阳性-100.0%。特别是，≥2×阳性的组合具有最佳的预测价值，具有较高的灵敏度（82.6%）、特异性（88.1%）和准确率（79.2%），并被认为是预测 PD 的临界点。总之，新模型为评估临床病例 PD 风险提供了有用的参考。
