D M Stamilio1, H M Sehdev, M A Morgan, K Propert, G A Macones. 1. Department of Obstetrics and Gynecology and the Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Health System, Philadelphia, Pennsylvania, USA.
Abstract
OBJECTIVE: This study was undertaken to develop a multivariable clinical predictive rule for severe preeclampsia using second-trimester clinical factors and biochemical markers. STUDY DESIGN: We performed a retrospective cohort study of all pregnant patients with single gestations from 1995 through 1997 for whom we had complete follow-up data. Through medical record review we determined whether patients had severe preeclampsia develop according to American College of Obstetricians and Gynecologists criteria. Case patients with severe preeclampsia were compared with control subjects with respect to clinical data and multiple-marker screening test results. With potential predictive factors identified in the bivariate and stratified analyses both an explanatory logistic regression model and a clinical prediction rule were created. Patients were assigned a predictive score according to the presence or absence of predictive factors, and receiver operating characteristic analysis was used to determine the optimal score cutoff point for prediction of severe preeclampsia with maximal sensitivity. RESULTS: Among the 1998 patients we found 49 patients with severe preeclampsia (prevalence, 2.5%). After we controlled for confounding variables, case patients and control subjects had similar human chorionic gonadotropin and alpha-fetoprotein levels, and the only variables that remained significantly associated with severe preeclampsia were nulliparity (relative risk, 3.8; 95% confidence interval, 1.7-8.3), history of preeclampsia (relative risk, 5.0; 95% confidence interval, 1.7-17.2), elevated screening mean arterial pressure (relative risk, 3.5; 95% confidence interval, 1.7-7.2), and low unconjugated estriol concentration (relative risk, 1.7; 95% confidence interval, 0.9-3.4). Our predictive model for severe preeclampsia, which included only these 4 variables, had a sensitivity of 76% and a specificity of 46%. CONCLUSION: Even after incorporation of the strongest risk factors, our predictive model had only modest sensitivity and specificity for discrimination of patients at risk for development of severe preeclampsia. The addition of the human chorionic gonadotropin and alpha-fetoprotein biochemical markers did not enhance the model's predictive value for severe preeclampsia.
OBJECTIVE: This study was undertaken to develop a multivariable clinical predictive rule for severe preeclampsia using second-trimester clinical factors and biochemical markers. STUDY DESIGN: We performed a retrospective cohort study of all pregnant patients with single gestations from 1995 through 1997 for whom we had complete follow-up data. Through medical record review we determined whether patients had severe preeclampsia develop according to American College of Obstetricians and Gynecologists criteria. Case patients with severe preeclampsia were compared with control subjects with respect to clinical data and multiple-marker screening test results. With potential predictive factors identified in the bivariate and stratified analyses both an explanatory logistic regression model and a clinical prediction rule were created. Patients were assigned a predictive score according to the presence or absence of predictive factors, and receiver operating characteristic analysis was used to determine the optimal score cutoff point for prediction of severe preeclampsia with maximal sensitivity. RESULTS: Among the 1998 patients we found 49 patients with severe preeclampsia (prevalence, 2.5%). After we controlled for confounding variables, case patients and control subjects had similar human chorionic gonadotropin and alpha-fetoprotein levels, and the only variables that remained significantly associated with severe preeclampsia were nulliparity (relative risk, 3.8; 95% confidence interval, 1.7-8.3), history of preeclampsia (relative risk, 5.0; 95% confidence interval, 1.7-17.2), elevated screening mean arterial pressure (relative risk, 3.5; 95% confidence interval, 1.7-7.2), and low unconjugated estriol concentration (relative risk, 1.7; 95% confidence interval, 0.9-3.4). Our predictive model for severe preeclampsia, which included only these 4 variables, had a sensitivity of 76% and a specificity of 46%. CONCLUSION: Even after incorporation of the strongest risk factors, our predictive model had only modest sensitivity and specificity for discrimination of patients at risk for development of severe preeclampsia. The addition of the human chorionic gonadotropin and alpha-fetoprotein biochemical markers did not enhance the model's predictive value for severe preeclampsia.
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