BACKGROUND: Patient characteristics may contribute to the progress and pain of labor. Quantitative evaluation of the effects of patient characteristics requires robust mathematical models of labor progress and labor pain. METHODS: The authors retrospectively studied 100 sequential deliveries from each of five self-reported ethnic groups (Asian, Black, Hispanic, Other, and White). Demographic variables, cervical dilation, and numerical rating scores for pain before analgesia and cervical dilation were abstracted from the automated medical record. Labor progress was modeled with a biexponential function describing the latent and active phases of labor. Labor pain was modeled as a sigmoid function of cervical dilation by using a previously validated mathematical model. The covariates, including self-described ethnicity, were analyzed with NONMEM. RESULTS: The biexponential function described the time course of labor progress better than several alternative functions, including the sigmoidal function introduced by Friedman. The sigmoidal function of labor pain described its dynamic nature well, with substantial intersubject variability. Asian women had slower active labor than other ethnicities (P < 0.01). Asian women also reported less pain during their labor compared to all other patients (P < 0.001). Slower labor progress was associated with less rapid progression of pain, but this did not obviate the effect of Asian ethnicity on pain. Neuraxial analgesia is strongly associated with slower labor (P < 0.0001). Greater maternal weight was associated with slower active labor (P < 0.0001). CONCLUSIONS: Mathematical models can be used to detect subtle effects of patient covariates on the progress and pain of the first stage of labor. Asian women and heavier women had slower labor and slower onset of labor pain than others. These effects were modest compared with the substantial remaining unexplained subject-to-subject variability in labor progress and labor pain.
BACKGROUND:Patient characteristics may contribute to the progress and pain of labor. Quantitative evaluation of the effects of patient characteristics requires robust mathematical models of labor progress and labor pain. METHODS: The authors retrospectively studied 100 sequential deliveries from each of five self-reported ethnic groups (Asian, Black, Hispanic, Other, and White). Demographic variables, cervical dilation, and numerical rating scores for pain before analgesia and cervical dilation were abstracted from the automated medical record. Labor progress was modeled with a biexponential function describing the latent and active phases of labor. Labor pain was modeled as a sigmoid function of cervical dilation by using a previously validated mathematical model. The covariates, including self-described ethnicity, were analyzed with NONMEM. RESULTS: The biexponential function described the time course of labor progress better than several alternative functions, including the sigmoidal function introduced by Friedman. The sigmoidal function of labor pain described its dynamic nature well, with substantial intersubject variability. Asian women had slower active labor than other ethnicities (P < 0.01). Asian women also reported less pain during their labor compared to all other patients (P < 0.001). Slower labor progress was associated with less rapid progression of pain, but this did not obviate the effect of Asian ethnicity on pain. Neuraxial analgesia is strongly associated with slower labor (P < 0.0001). Greater maternal weight was associated with slower active labor (P < 0.0001). CONCLUSIONS: Mathematical models can be used to detect subtle effects of patient covariates on the progress and pain of the first stage of labor. Asian women and heavier women had slower labor and slower onset of labor pain than others. These effects were modest compared with the substantial remaining unexplained subject-to-subject variability in labor progress and labor pain.
Authors: Russell S Miller; Richard M Smiley; Danette Daniel; Chunhua Weng; Charles W Emala; Jean-Louis Blouin; Pamela D Flood Journal: Am J Obstet Gynecol Date: 2011-04-02 Impact factor: 8.661
Authors: Elena Reitman; Jessamyn Conell-Price; Jennifer Evansmith; Luke Olson; Sofia Drosinos; Nancy Jasper; Paula Randolph; Richard M Smiley; Steven Shafer; Pamela Flood Journal: Anesthesiology Date: 2011-04 Impact factor: 7.892