Comparison of two “a priori” risk assessment algorithms for preeclampsia in Italy: a prospective multicenter study
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To compare the performance of the algorithms proposed by the Fetal Medicine Foundation in 2012 and BCNatal in 2013 in an Italian population.
A multicentric prospective study was carried out which included pregnancies at 11–13 weeks’ gestation from Jan 2014 through May 2017. Two previously published algorithms were used for the calculation of the “a priori” risk of preeclampsia (based on risk factors from medical history) in each individual.
In a study population of 11,632 cases, 67 (0.6%) developed early preeclampsia and 211 (1.8%) developed late preeclampsia. The detection rates (95% CI) for early and late preeclampsia were 58.2% (45.5–70.2) vs. 41.8% (29.6–54.5) (p value < 0.05) and 44.1% (37.3–51.1) vs. 38% (31.3–44.8) (p value < 0.05) for the Fetal Medicine Foundation and BCNatal, respectively (at a 10% false positive rate). The associated risk was 1:226 and 1:198 (p value ns) for early PE, and 1:17 and 1:24 (p value ns) for late PE for the Fetal Medicine Foundation and BCNatal, respectively.
The Fetal Medicine Foundation screening for preeclampsia at 11–13 weeks’ gestation scored the highest detection rate for both early and late PE. At a fixed 10% false positive rate, the estimated “a priori” risks of both the Fetal Medicine Foundation and the BCNatal algorithms in an Italian population were quite similar, and both were reliable and consistent.
KeywordsScreening for preeclampsia A priori risk ROC curves Detection rate
DDM protocol/project development, data collection, manuscript writing. BM protocol/project development, data collection. SP, BB, FG, VG, GP and LC data collection. PC protocol/project development, data collection, Manuscript writing. FP protocol/project development, data collection, manuscript writing, data analysis. CG data collection, manuscript writing. DM protocol/project development, manuscript writing. FF data collection, manuscript writing. MC, TT and NR manuscript writing. AF protocol/project development, data collection, manuscript writing, data analysis.
The authors received no specific funding for this study.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
- 2.Iams JD, Goldenberg RL, Mercer BM, Moawad A, Thom E, Meis PJ, McNellis D, Caritis SN, Miodovnik M, Menard MK, Thurnau GR, Bottoms SE, Roberts JM (1998) The preterm prediction study: recurrence risk of spontaneous preterm birth; National Institute of Child Health and Human Development maternal-fetal medicine units network. Am J Obstet Gynecol 178:1035–1040CrossRefGoogle Scholar
- 4.Knight M, Tuffnell D, Kenyon S, Shakespeare J, Gray R, Kurinczuk JJ (eds); on behalf of MBRRACE-UK (2015). Saving Lives, Improving Mothers’ Care—Surveillance of maternal deaths in the UK 2011–13 and lessons learned to inform maternity care from the UK and Ireland Confidential Enquiries into Maternal Deaths and Morbidity 2009–13. National Perinatal Epidemiology Unit: University of Oxford, OxfordGoogle Scholar
- 5.Lewis G (eds) (2007) The Confidential Enquiry into Maternal and Child Health (CEMACH). Saving mothers’ lives: reviewing maternal deaths to make motherhood safer-2003–2005. In: The seventh report on confidential enquiries into maternal deaths in the UK. London: CEMACHGoogle Scholar
- 10.Al-Rubaie Z, Askie LM, Ray JG, Hudson HM, Lord SJ (2016) The performance of risk prediction models for preeclampsia using routinely collected maternal characteristics and comparison with models that include specialized tests and with clinical guideline decision rules: a systematic review. BJOG 123:1441–1452CrossRefGoogle Scholar
- 12.O’Gorman N, Wright D, Poon LC, Rolnik DL, Syngelaki A, de Alvarado M, Carbone IF, Dutemeyer V, Fiolna M, Frick A, Karagiotis N, Mastrodima S, de Paco Matallana C, Papaioannou G, Pazos A, Plasencia W, Nicolaides KH (2017) Multicenter screening for preeclampsia by maternal factors and biomarkers at 11–13 weeks’ gestation: comparison with NICE guidelines and ACOG recommendations. Ultrasound Obstet Gynecol 49:756–760CrossRefGoogle Scholar
- 13.Rolnik DL, Wright D, Poon LC, O’Gorman N, Syngelaki A, de Paco Matallana C, Akolekar R, Cicero S, Janga D, Singh M, Molina FS, Persico N, Jani JC, Plasencia W, Papaioannou G, Tenenbaum-Gavish K, Meiri H, Gizurarson S, Maclagan K, Nicolaides KH (2017) Aspirin versus placebo in pregnancies at high risk for preterm preeclampsia. N Engl J Med 377:613–622CrossRefGoogle Scholar
- 15.Khalil A, Nicolaides KH (2013) How to record uterine artery Doppler in the first trimester. Ultrasound Obstet Gynecol 42:478–479Google Scholar
- 18.ISTAT: Il diabete in Italia. https://www.istat.it/it/archivio/202600Google Scholar
- 19.Tunstall-Pedoe H, Kuulasmaa K, Mähönen M, Tolonen H, Ruokokoski E, Amouyel P (1999) Contribution of trends in survival and coronary-event rates to changes in coronary heart disease mortality: 10-year results from 37 WHO MONICA project populations. Monitoring trends and determinants in cardiovascular disease. Lancet 353:1547–1557CrossRefGoogle Scholar
- 26.O’Gorman N, Wright D, Poon LC, Rolnik DL, Syngelaki A, Wright A, Akolekar R, Cicero S, Janga D, Jani J, Molina FS, de Paco Matallana C, Papantoniou N, Persico N, Plasencia W, Singh M, Nicolaides KH (2017) Accuracy of competing-risks model in screening for preeclampsia by maternal factors and biomarkers at 11–13 weeks’ gestation. Ultrasound Obstet Gynecol 49:751–755CrossRefGoogle Scholar