G A Macones1, S Y Segel, D M Stamilio, M A Morgan. 1. Department of Obstetrics and Gynecology and the Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Health System, Philadelphia, USA. macones@cceb.medupenn.edu
Abstract
OBJECTIVE: To develop a prediction rule using clinical admission characteristics for women treated with parenteral tocolysis for preterm labor who are at highest risk of delivery within 48 hours. METHODS: We performed a case-control study of patients treated with magnesium sulfate for idiopathic preterm labor. A case was defined as a patient who received magnesium sulfate tocolysis and delivered within 48 hours of admission. We selected a 48-hour delay to delivery as a clinically relevant endpoint for the maximization of steroid benefit. Controls were patients who received magnesium sulfate tocolysis and remained undelivered 48 hours after admission. Cases and controls were identified by merging a pharmacy billing database with International Classification of Disease codes for premature labor. Medical records were reviewed and risk factor information was obtained. We focused on risk factors within the first hour of admission, because our goal was to identify patients at high risk of delivery early in their hospital course. Backward stepwise logistic regression was used to develop explanatory and predictive models. The focus of the predictive model was to maximize the test's sensitivity and negative predictive value. RESULTS: We identified 50 cases and 150 controls. The following six variables were included in the initial multivariable models based on bivariate analyses: white blood cell count at least 14.0 (1000/microL), cervical dilation at least 2 cm, bleeding, substance abuse, parity, and previous abortion. A two-variable model containing cervical dilation and bleeding had an overall accuracy of 73%, sensitivity of 62%, and specificity of 76%, and it was as sensitive and specific as more complex models. CONCLUSION: Cervical dilation of at least 2 cm and bleeding on admission had an overall accuracy of 73% in predicting the likelihood of delivery within 48 hours in women receiving magnesium sulfate.
OBJECTIVE: To develop a prediction rule using clinical admission characteristics for women treated with parenteral tocolysis for preterm labor who are at highest risk of delivery within 48 hours. METHODS: We performed a case-control study of patients treated with magnesium sulfate for idiopathic preterm labor. A case was defined as a patient who received magnesium sulfate tocolysis and delivered within 48 hours of admission. We selected a 48-hour delay to delivery as a clinically relevant endpoint for the maximization of steroid benefit. Controls were patients who received magnesium sulfate tocolysis and remained undelivered 48 hours after admission. Cases and controls were identified by merging a pharmacy billing database with International Classification of Disease codes for premature labor. Medical records were reviewed and risk factor information was obtained. We focused on risk factors within the first hour of admission, because our goal was to identify patients at high risk of delivery early in their hospital course. Backward stepwise logistic regression was used to develop explanatory and predictive models. The focus of the predictive model was to maximize the test's sensitivity and negative predictive value. RESULTS: We identified 50 cases and 150 controls. The following six variables were included in the initial multivariable models based on bivariate analyses: white blood cell count at least 14.0 (1000/microL), cervical dilation at least 2 cm, bleeding, substance abuse, parity, and previous abortion. A two-variable model containing cervical dilation and bleeding had an overall accuracy of 73%, sensitivity of 62%, and specificity of 76%, and it was as sensitive and specific as more complex models. CONCLUSION: Cervical dilation of at least 2 cm and bleeding on admission had an overall accuracy of 73% in predicting the likelihood of delivery within 48 hours in women receiving magnesium sulfate.