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New insights on labor progression: a systematic review
Xiaoqing He1, Xiaojing Zeng2, James Troendle3
1International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China; Ministry of Education -Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
The past 20 years witnessed an invigoration of research on labor progression and a change of thinking regarding normal labor. New evidence is emerging, and more advanced statistical methods are applied to labor progression analyses. Given the wide variations in the onset of active labor and the pattern of labor progression, there is an emerging consensus that the definition of abnormal labor may not be related to an idealized or average labor curve. Alternative approaches to guide labor management have been proposed; for example, using an upper limit of a distribution of labor duration to define abnormally slow labor. Nonetheless, the methods of labor assessment are still primitive and subject to error; more objective measures and more advanced instruments are needed to identify the onset of active labor, monitor labor progression, and define when labor duration is associated with maternal/child risk. Cervical dilation alone may be insufficient to define active labor, and incorporating more physical and biochemical measures may improve accuracy of diagnosing active labor onset and progression. Because the association between duration of labor and perinatal outcomes is rather complex and influenced by various underlying and iatrogenic conditions, future research must carefully explore how to integrate statistical cut-points with clinical outcomes to reach a practical definition of labor abnormalities. Finally, research regarding the complex labor process may benefit from new approaches, such as machine learning technologies and artificial intelligence to improve the predictability of successful vaginal delivery with normal perinatal outcomes.
The past 20 years witnessed an invigoration of research on labor progression and a change of thinking regarding normal labor. New evidence is emerging, and more advanced statistical methods are applied to labor progression analyses. Given the wide variations in the onset of active labor and the pattern of labor progression, there is an emerging consensus that the definition of abnormal labor may not be related to an idealized or average labor curve. Alternative approaches to guide labor management have been proposed; for example, using an upper limit of a distribution of labor duration to define abnormally slow labor. Nonetheless, the methods of labor assessment are still primitive and subject to error; more objective measures and more advanced instruments are needed to identify the onset of active labor, monitor labor progression, and define when labor duration is associated with maternal/child risk. Cervical dilation alone may be insufficient to define active labor, and incorporating more physical and biochemical measures may improve accuracy of diagnosing active labor onset and progression. Because the association between duration of labor and perinatal outcomes is rather complex and influenced by various underlying and iatrogenic conditions, future research must carefully explore how to integrate statistical cut-points with clinical outcomes to reach a practical definition of labor abnormalities. Finally, research regarding the complex labor process may benefit from new approaches, such as machine learning technologies and artificial intelligence to improve the predictability of successful vaginal delivery with normal perinatal outcomes.
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