Literature DB >> 23584890

First trimester prediction of early onset preeclampsia using demographic, clinical, and sonographic data: a cohort study.

Javier Caradeux1, Ramón Serra, Jyh-Kae Nien, Alejandra Pérez-Sepulveda, Manuel Schepeler, Francisco Guerra, Jorge Gutiérrez, Jaime Martínez, Cristián Cabrera, Horacio Figueroa-Diesel, Peter Soothill, Sebastián E Illanes.   

Abstract

OBJECTIVE: The aim of this research was to evaluate the performance of a predictive model for early onset preeclampsia (PE) during early gestation.
METHOD: Prospective multicenter cohort study was performed in women attending 11-14 weeks ultrasound. Medical history and biometrical variables were recorded and uterine artery Doppler was performed. All patients were followed until postpartum period. Constructed predictive models were compared using the area under the associated receiver operating characteristic curve. Sensitivity, specificity, and likelihood ratios were estimated for each outcome.
RESULTS: A total of 627 patients were enrolled. Sixty-five (10.4%) developed gestational hypertension, of which 29 developed PE (4.6% of the total sample) and nine occurred before 34 weeks (1.5% of total sample). Prediction model generated for early onset PE (ePE) with 5% false positive achieve sensitivity of 62.5% and specificity of 95.5%. The positive and negative likelihood ratios for ePE were 13.9 and 0.39, respectively. Development of ePE was significantly associated with history of preterm labor (p = 0.002) and diabetes mellitus (p = 0.02).
CONCLUSIONS: This study confirms the advantage of combining multiple variables for prediction of ePE.
© 2013 John Wiley & Sons, Ltd.

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Year:  2013        PMID: 23584890     DOI: 10.1002/pd.4113

Source DB:  PubMed          Journal:  Prenat Diagn        ISSN: 0197-3851            Impact factor:   3.050


  10 in total

1.  Predictive accuracy of the first trimester Doppler scan: a meta-study.

Authors:  Naira Roland Matevosyan
Journal:  Wien Med Wochenschr       Date:  2015-06-16

2.  Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: an individual participant data meta-analysis.

Authors:  John Allotey; Kym Ie Snell; Melanie Smuk; Richard Hooper; Claire L Chan; Asif Ahmed; Lucy C Chappell; Peter von Dadelszen; Julie Dodds; Marcus Green; Louise Kenny; Asma Khalil; Khalid S Khan; Ben W Mol; Jenny Myers; Lucilla Poston; Basky Thilaganathan; Anne C Staff; Gordon Cs Smith; Wessel Ganzevoort; Hannele Laivuori; Anthony O Odibo; Javier A Ramírez; John Kingdom; George Daskalakis; Diane Farrar; Ahmet A Baschat; Paul T Seed; Federico Prefumo; Fabricio da Silva Costa; Henk Groen; Francois Audibert; Jacques Masse; Ragnhild B Skråstad; Kjell Å Salvesen; Camilla Haavaldsen; Chie Nagata; Alice R Rumbold; Seppo Heinonen; Lisa M Askie; Luc Jm Smits; Christina A Vinter; Per M Magnus; Kajantie Eero; Pia M Villa; Anne K Jenum; Louise B Andersen; Jane E Norman; Akihide Ohkuchi; Anne Eskild; Sohinee Bhattacharya; Fionnuala M McAuliffe; Alberto Galindo; Ignacio Herraiz; Lionel Carbillon; Kerstin Klipstein-Grobusch; SeonAe Yeo; Helena J Teede; Joyce L Browne; Karel Gm Moons; Richard D Riley; Shakila Thangaratinam
Journal:  Health Technol Assess       Date:  2020-12       Impact factor: 4.014

Review 3.  Aspirin for Prevention of Preeclampsia.

Authors:  A Atallah; E Lecarpentier; F Goffinet; M Doret-Dion; P Gaucherand; V Tsatsaris
Journal:  Drugs       Date:  2017-11       Impact factor: 9.546

4.  Usefulness of uterine artery Doppler velocimetry as a predictor for hypertensive disorders in pregnancy in women with prehypertension before 20 weeks gestation.

Authors:  Seung Woo Yang; Soo Hyun Cho; Young Sun Kang; Seung Hwa Park; In Sook Sohn; Han Sung Kwon; Han Sung Hwang
Journal:  PLoS One       Date:  2019-01-30       Impact factor: 3.240

5.  Statistical risk prediction models for adverse maternal and neonatal outcomes in severe preeclampsia in a low-resource setting: proposal for a single-centre cross-sectional study at Mpilo Central Hospital, Bulawayo, Zimbabwe.

Authors:  Solwayo Ngwenya; Brian Jones; Alexander Edward Patrick Heazell; Desmond Mwembe
Journal:  BMC Res Notes       Date:  2019-08-13

6.  An imbalance-aware deep neural network for early prediction of preeclampsia.

Authors:  Rachel Bennett; Zuber D Mulla; Pavan Parikh; Alisse Hauspurg; Talayeh Razzaghi
Journal:  PLoS One       Date:  2022-04-06       Impact factor: 3.240

Review 7.  Adverse pregnancy and perinatal outcomes in Latin America and the Caribbean: systematic review and meta-analysis.

Authors:  Estela Blanco; Marcela Marin; Loreto Nuñez; Erika Retamal; Ximena Ossa; Katherine E Woolley; Tosin Oludotun; Suzanne E Bartington; Juana Maria Delgado-Saborit; Roy M Harrison; Pablo Ruiz-Rudolph; María Elisa Quinteros
Journal:  Rev Panam Salud Publica       Date:  2022-05-02

8.  Placental Aromatase Is Deficient in Placental Ischemia and Preeclampsia.

Authors:  Alejandra Perez-Sepulveda; Lara J Monteiro; Aneta Dobierzewska; Pedro P España-Perrot; Pía Venegas-Araneda; Alejandra M Guzmán-Rojas; María I González; Macarena Palominos-Rivera; Carlos E Irarrazabal; Horacio Figueroa-Diesel; Manuel Varas-Godoy; Sebastián E Illanes
Journal:  PLoS One       Date:  2015-10-07       Impact factor: 3.240

9.  Usefulness of circulating microRNAs for the prediction of early preeclampsia at first-trimester of pregnancy.

Authors:  Ana Luque; Abduljalil Farwati; Francesca Crovetto; Fatima Crispi; Francesc Figueras; Eduard Gratacós; Josep M Aran
Journal:  Sci Rep       Date:  2014-05-08       Impact factor: 4.379

10.  Diagnostic Performance of First Trimester Screening of Preeclampsia Based on Uterine Artery Pulsatility Index and Maternal Risk Factors in Routine Clinical Use.

Authors:  Max Mönckeberg; Valentina Arias; Rosario Fuenzalida; Santiago Álvarez; Victoria Toro; Andrés Calvo; Juan P Kusanovic; Lara J Monteiro; Manuel Schepeler; Jyh K Nien; Jaime Martinez; Sebastián E Illanes
Journal:  Diagnostics (Basel)       Date:  2020-03-26
  10 in total

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