Literature DB >> 29082782

How do maternal factors impact preeclampsia prediction in Brazilian population?

Karina Bilda de Castro Rezende1,2, Antônio José Ledo Alves da Cunha3,4, Cristos Pritsivelis1, Edson Chaves Faleiro1, Joffre Amim Junior1,2, Rita Guérios Bornia1,2.   

Abstract

Objective: To evaluate the impacts of maternal risk factors described by the Fetal Medicine Foundation's 2012 algorithm (FMF2012) in a Brazilian population.
Methods: All singleton pregnancies submitted to first-trimester preeclampsia (PE) screening using the FMF2012 algorithm were considered for study inclusion. Maternal factors, recorded via a patient questionnaire, were described and compared between PE outcome groups. A Gaussian regression model was derived to measure the effects of maternal factors, and to identify factors that contributed significantly (p < .05) to the alteration of gestational age at delivery, in pregnancies with PE.
Results: Of the 1934 cases considered for study inclusion, the final sample consisted of 1531 cases. The sample included 120 (7.8%) cases of PE, of which 26 (1.7%) were preterm PE (PE < 37 weeks) and 11 (0.72%) were early PE (PE < 34 weeks). The PE rate did not differ according to ethnicity, smoking, family history of PE, or use of assisted reproductive technology. Significant differences (p < .05) between the normal and PE groups in maternal age, maternal weight, previous history of PE, chronic hypertension, and types 1 and 2 diabetes were detected. Conclusions: The significance and magnitude of associations of maternal factors in our sample differed from those incorporated in the FMF2012 model, implying the need to derive a fitted model for our population.

Entities:  

Keywords:  First trimester screening; maternal history; preeclampsia; risk factors

Year:  2017        PMID: 29082782     DOI: 10.1080/14767058.2017.1399115

Source DB:  PubMed          Journal:  J Matern Fetal Neonatal Med        ISSN: 1476-4954


  4 in total

1.  Predicting preeclampsia and related risk factors using data mining approaches: A cross-sectional study.

Authors:  Zohreh Manoochehri; Sara Manoochehri; Farzaneh Soltani; Leili Tapak; Majid Sadeghifar
Journal:  Int J Reprod Biomed       Date:  2021-12-13

Review 2.  Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders.

Authors:  Eleanor P Thong; Drishti P Ghelani; Pamada Manoleehakul; Anika Yesmin; Kaylee Slater; Rachael Taylor; Clare Collins; Melinda Hutchesson; Siew S Lim; Helena J Teede; Cheryce L Harrison; Lisa Moran; Joanne Enticott
Journal:  J Cardiovasc Dev Dis       Date:  2022-02-10

3.  Reducing Perinatal Mortality in India: Two-Years Results of the IRIA Fetal Radiology Samrakshan Program.

Authors:  Rijo M Choorakuttil; Bavaharan Rajalingam; Shilpa R Satarkar; Lalit K Sharma; Anjali Gupta; Akanksha Baghel; Neelam Jain; Devarajan Palanisamy; Ramesh Shenoy; Karthik Senthilvel; Sandhya Dhankar; Kavita Aneja; Somya Dwivedi; Shweta Nagar; Sonali Kimmatkar Soni; Gulab Chhajer; Sunitha Pradeep; Prashant M Onkar; Avni K P Skandhan; Eesha Rajput; Renu Sharma; Srinivas Shentar; Suresh Saboo; Amel Antony; M R Balachandran Nair; Tejashree Y Patekar; Bhupendra Ahuja; Hemant Patel; Mohanan Kunnumal; Rajendra K Sodani; M V Kameswar Rao; Pushparaj Bhatele; Sandeep Kavthale; Deepak Patkar; Rajeev Singh; Amarnath Chelladurai; Praveen K Nirmalan
Journal:  Indian J Radiol Imaging       Date:  2022-04-19

4.  Performance of Fetal Medicine Foundation Software for Pre-Eclampsia Prediction Upon Marker Customization: Cross-Sectional Study.

Authors:  Karina Bilda De Castro Rezende; Antonio José Ledo Alves Cunha; Joffre Amim; Wescule De Moraes Oliveira; Maria Eduarda Belloti Leão; Mariana Oliveira Alves Menezes; Ana Alice Marques Ferraz De Andrade Jardim; Rita Guérios Bornia
Journal:  J Med Internet Res       Date:  2019-11-22       Impact factor: 5.428

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.