Easley Henry Alexander, Beste Todd Michael
Department of Obstetrics and Gynecology, UNC School of Medicine, Wilmington Campus, Wilmington, North Carolina.
AJP Rep. 2019 Jul;9(3):e262-e267. doi: 10.1055/s-0039-1693162. Epub 2019 Aug 20.
To evaluate the diagnostic accuracy of a multivariable prediction model, the Shoulder Screen (Perigen, Inc.), and compare it with the American College of Obstetricians and Gynecologists (ACOG) guidelines to prevent harm from shoulder dystocia. The model was applied to two groups of 199 patients each who delivered during a 4-year period. One group experienced shoulder dystocia and the other group delivered without shoulder dystocia. The model's accuracy was analyzed. The performance of the model was compared with the ACOG guideline. The sensitivity, specificity, positive, and negative predictive values of the model were 23.1, 99.5, 97.9, and 56.4%, respectively. The sensitivity of the ACOG guideline was 10.1%. The false-positive rate of the model was 0.5%. The accuracy of the model was 61.3%. A multivariable prediction model can predict shoulder dystocia and is more accurate than ACOG guidelines.
为评估多变量预测模型“肩部筛查”(Perigen公司)的诊断准确性,并将其与美国妇产科医师学会(ACOG)预防肩难产危害的指南进行比较。该模型应用于两组各199例在4年期间分娩的患者。一组经历了肩难产,另一组分娩时未发生肩难产。分析了该模型的准确性。将该模型的性能与ACOG指南进行了比较。该模型的敏感性、特异性、阳性预测值和阴性预测值分别为23.1%、99.5%、97.9%和56.4%。ACOG指南的敏感性为10.1%。该模型的假阳性率为0.5%。该模型的准确性为61.3%。多变量预测模型可以预测肩难产,并且比ACOG指南更准确。