Ultrasound in Obstetrics and Gynecology · 2017 · 255 citations · 14 references
MedicineMaternal HealthObstetricsHigh-risk PregnancyMaternal-fetal MedicinePrenatal DiagnosisMaternal EpidemiologyPerinatal Risk FactorsPregnancyPrenatal AssessmentPrenatal CarePrenatal Risk AssessmentDiagnostic Accuracy StudiesDiagnostic Testing AccuracyFalse Detection RatesObstetric Risk AssessmentObstetric Risk ScreeningPreeclampsia Risk PredictionPreeclampsia Risk ScreeningPrenatal Screening Models
OBJECTIVE: To examine the diagnostic accuracy of a previously developed model for prediction of pre-eclampsia (PE) by a combination of maternal factors and biomarkers at 11-13 weeks' gestation. METHODS: This was a prospective first-trimester multicenter study of screening for PE in 8775 singleton pregnancies. A previously published algorithm was used for the calculation of patient-specific risk of PE in each individual. The detection rates (DRs) and false-positive rates (FPRs) for delivery with PE < 32, < 37 and ≥ 37 weeks were estimated and compared with those for the dataset used for development of the algorithm. RESULTS: In the study population, 239 (2.7%) cases developed PE, of which 17 (0.2%), 59 (0.7%) and 180 (2.1%) developed PE < 32, < 37 and ≥ 37 weeks, respectively. With combined screening by maternal factors, mean arterial pressure, uterine artery pulsatility index and serum placental growth factor, the DR was 100% (95% CI, 80-100%) for PE < 32 weeks, 75% (95% CI, 62-85%) for PE < 37 weeks and 43% (95% CI, 35-50%) for PE ≥ 37 weeks, at a 10% FPR. These DRs were similar to the estimated rates for the dataset used for development of the model: 89% (95% CI, 79-96%) for PE < 32 weeks, 75% (95% CI, 70-80%) for PE < 37 weeks and 47% (95% CI, 44-51%) for PE ≥ 37 weeks. CONCLUSION: Assessment of a combination of maternal factors and biomarkers at 11-13 weeks provides effective first-trimester screening for preterm PE. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
Mark Brown, Marshall D. Lindheimer, Michael de Swiet et al. · Hypertension in Pregnancy · 2001 · 1.4K citations · Full text
Medicine, Gynecology, Obstetrics +12