背景:产程活跃期的诊断是至关重要的临床决策,因此需要准确的评估。本研究旨在建立和验证一个预测模型,根据产妇的体征和症状,确定宫颈扩张≥4厘米。
方法:一项前瞻性研究于2018年5月至9月在一个二级产妇单位进行(发展数据),2019年5月至9月在I级产妇单位(验证数据)。单身的女人,足月妊娠,在初步评估期间,我们连续纳入头颅表现和宫缩情况,以诊断产程.女性<18岁,排除语言障碍或引产。从多变量逻辑模型中获得了用于计算11种母体体征和症状的宫颈扩张≥4cm的预测的列线图。通过内部和外部验证对模型的预测性能进行了研究。
结果:共分析了288项评估。所有母体体征和症状对增加宫颈扩张≥4cm的可能性有重大影响。在最终的逻辑模型中,“节奏”(或6.26),收缩的“持续时间”(OR8.15)和“显示”(OR4.29)证实了它们的重要性,出乎意料的是,收缩的“频率”没有影响。子宫活动模子的ROC曲线下面积为0.865(发育数据)和0.927(验证数据),分别增加到0.905和0.956,添加母体标志时。子宫活动模型的Brier评分误差为0.140(发育数据)和0.097(验证数据),分别递减到0.121和0.092,添加母体标志时。
结论:我们的预测模型显示出良好的性能。非侵入性工具的引入可能有助于助产士的决策过程,避免干预,从而提供证据基础护理。
BACKGROUND: The diagnosis of the active phase of labor is a crucial clinical decision, thus requiring an accurate assessment. This study aimed to build and to validate a predictive model, based on maternal signs and symptoms to identify a cervical dilatation ≥4 cm.
METHODS: A prospective study was conducted from May to September 2018 in a II Level Maternity Unit (development data), and from May to September 2019 in a I Level Maternity Unit (validation data). Women with singleton, term pregnancy, cephalic presentation and presence of contractions were consecutively enrolled during the initial assessment to diagnose the stage of labor. Women < 18 years old, with language barrier or induction of labor were excluded. A nomogram for the calculation of the predictions of cervical dilatation ≥4 cm on the ground of 11 maternal signs and symptoms was obtained from a multivariate logistic model. The predictive performance of the model was investigated by internal and external validation.
RESULTS: A total of 288 assessments were analyzed. All maternal signs and symptoms showed a significant impact on increasing the probability of cervical dilatation ≥4 cm. In the final logistic model, \"Rhythm\" (OR 6.26), \"Duration\" (OR 8.15) of contractions and \"Show\" (OR 4.29) confirmed their significance while, unexpectedly, \"Frequency\" of contractions had no impact. The area under the ROC curve in the model of the uterine activity was 0.865 (development data) and 0.927 (validation data), with an increment to 0.905 and 0.956, respectively, when adding maternal signs. The Brier Score error in the model of the uterine activity was 0.140 (development data) and 0.097 (validation data), with a decrement to 0.121 and 0.092, respectively, when adding maternal signs.
CONCLUSIONS: Our predictive model showed a good performance. The introduction of a non-invasive tool might assist midwives in the decision-making process, avoiding interventions and thus offering an evidenced-base care.