Prognostic predictive model for PONV in cesarean delivery
Abstract
Introduction: Apfel simplified risk score for postoperative nausea and vomiting (PONV) has shown to be useful in anesthesia; however, since it has not been calibrated in regional anesthesia or in pregnant patients, its use in cesarean section is limited.
Objectives: To develop a prognostic predictive model for postoperative nausea and vomiting in pregnant patients undergoing cesarean section under spinal anesthesia.
Methods: In a cohort of 703 term pregnant patients scheduled of cesarean section, 15 variables were prospectively assessed, to design a prognostic predictive model for the development of postoperative nausea and vomiting. A logistic regression analysis was used to construct the model and its calibration and discrimination were based on the Hosmer-Lemeshow test, the calibration curves, and C statistic. Additionally, the internal calibration was performed with the Bootstrap resampling method.
Results: Postoperative nausea and vomiting were experienced by 27 % of the patients during the first six hours after surgery. The model included as prognostic variables the development of intraoperative nausea and vomiting, age under 28 years, a history of PONV, the mother’s BMI and the weight of the newborn baby. The model showed an adequate calibration (χ2: 4.65 p: 0.5888), though a low discrimination (Statistic C = 0.68).
Conclusions: A prognostic predictive model was created for the development of PONV in cesarean section. This model was used to build a prognostic scale for the classification of patients into risk groups.
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