Sensitivity and specificity of computerized algorithms to classify gestational periods in the absence of information on date of conception

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Abstract

To evaluate the accuracy of computerized algorithms for pinpointing periods of exposure to medications during pregnancy in the absence of data on timing of conception, the authors used data from a population-based sample of nonmalformed infants in the Slone Epidemiology Center Birth Defects Study in 1998-2006 (United States and Canada; N = 3,177). The standard was defined as any antiinfective use from 2 weeks after the last menstrual period through the third gestational month, which was compared with results obtained after defining the beginning of pregnancy as either 270 days before the birth date (delivery-date algorithm) or the date of the first prenatal visit (pregnancy-indicator algorithm). The sensitivity was 92% (95% confidence interval: 88, 95) for the delivery-date algorithm and 59% (95% confidence interval: 53, 65) for the pregnancy-indicator algorithm. The specificity was higher than 98% for both algorithms. The sensitivity for the delivery-date algorithm among women with preterm births was 66% (95% confidence interval: 49, 80). For women without pregnancy complications, subtraction of 270 days from the delivery date might be accurate for timing first-trimester prescription drug use in automated databases. However, the sensitivity of this algorithm is lower for preterm deliveries, suggesting limited validity to assess drug safety for pregnancy outcomes associated with prematurity. © The Author 2008. Published by the Johns Hopkins Bloomberg School of Public Health. All rights reserved.

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Toh, S., Mitchell, A. A., Werler, M. M., & Hernández-Díaz, S. (2008). Sensitivity and specificity of computerized algorithms to classify gestational periods in the absence of information on date of conception. American Journal of Epidemiology, 167(6), 633–640. https://doi.org/10.1093/aje/kwm367

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