Literature DB >> 27651587

Prediction of Adverse Maternal Outcomes in Preeclampsia Using a Risk Prediction Model.

Shruti Agrawal1, Nandita Maitra1.   

Abstract

BACKGROUND: This study was conducted to evaluate how the preeclampsia integrated estimate of risk (fullPIERS) model performs in the prediction of adverse maternal outcomes when the predictor variables are all obtained within 24-h of admission for preeclampsia.
METHODS: A prospective cohort study on 323 women who fulfilled definite inclusion and exclusion criteria was conducted. Subjects were monitored for clinical symptoms of preeclampsia, biochemical parameters, and adverse maternal and neonatal outcomes. A risk prediction score was calculated using the fullPIERS calculator. Statistical analysis of rates and ratios was carried out by assessing χ (2) test and odds ratio.
RESULTS: 18.3 % (n = 60) had adverse maternal outcome and 42.8 % (n = 138) had adverse fetal outcome, and 43 (13.35 %) had combined adverse maternal and perinatal outcome. Dyspnea, visual disturbances, epigastric pain, and [Formula: see text] appeared to be highly significant risk factors. In the biochemical variables studied, serum creatinine and serum uric acid were found to have a significant association. The association between adverse perinatal outcome and vaginal delivery was highly significant (OR 0.35, 95 % CI 0.19, 0.63), and the P value was 0.0005. The likelihood ratio associated with the highest risk group (predicted probability of the outcome ≥30 %) showed excellent performance (i.e., 17.5) of fullPIERS model as a rule in test.
CONCLUSION: The fullPIERS model performed well in the prediction of adverse maternal outcomes in women with preeclampsia. It is easy to use. The model is based on the use of few important clinical and biochemical parameters and does not require extensive laboratory testing. Although it might be of limited use in a well-equipped tertiary care facility, this model can be utilized in the setting of district or sub-district level hospitals to identify patients who are at risk of complications due to preeclampsia. Timely referral to a higher center will help in reducing the morbidity and mortality associated with this condition.

Entities:  

Keywords:  Maternal outcomes; Preeclampsia; Risk prediction

Year:  2015        PMID: 27651587      PMCID: PMC5016414          DOI: 10.1007/s13224-015-0779-5

Source DB:  PubMed          Journal:  J Obstet Gynaecol India        ISSN: 0975-6434


  15 in total

Review 1.  Pre-eclampsia.

Authors:  Eric A P Steegers; Peter von Dadelszen; Johannes J Duvekot; Robert Pijnenborg
Journal:  Lancet       Date:  2010-07-02       Impact factor: 79.321

2.  Prediction of adverse maternal outcomes in pre-eclampsia: development and validation of the fullPIERS model.

Authors:  Peter von Dadelszen; Beth Payne; Jing Li; J Mark Ansermino; Fiona Broughton Pipkin; Anne-Marie Côté; M Joanne Douglas; Andrée Gruslin; Jennifer A Hutcheon; K S Joseph; Phillipa M Kyle; Tang Lee; Pamela Loughna; Jennifer M Menzies; Mario Merialdi; Alexandra L Millman; M Peter Moore; Jean-Marie Moutquin; Annie B Ouellet; Graeme N Smith; James J Walker; Keith R Walley; Barry N Walters; Mariana Widmer; Shoo K Lee; James A Russell; Laura A Magee
Journal:  Lancet       Date:  2010-12-23       Impact factor: 79.321

3.  Current CHS and NHBPEP criteria for severe preeclampsia do not uniformly predict adverse maternal or perinatal outcomes.

Authors:  J Menzies; L A Magee; Y C Macnab; J M Ansermino; J Li; M J Douglas; A Gruslin; P Kyle; S K Lee; M P Moore; J M Moutquin; G N Smith; J J Walker; K R Walley; J A Russell; P von Dadelszen
Journal:  Hypertens Pregnancy       Date:  2007       Impact factor: 2.108

Review 4.  Accuracy of serum uric acid in predicting complications of pre-eclampsia: a systematic review.

Authors:  S Thangaratinam; K M K Ismail; S Sharp; A Coomarasamy; K S Khan
Journal:  BJOG       Date:  2006-04       Impact factor: 6.531

5.  Early-onset severe preeclampsia: induction of labor vs elective cesarean delivery and neonatal outcomes.

Authors:  Mark C Alanis; Christopher J Robinson; Thomas C Hulsey; Myla Ebeling; Donna D Johnson
Journal:  Am J Obstet Gynecol       Date:  2008-09       Impact factor: 8.661

6.  ACOG practice bulletin. Diagnosis and management of preeclampsia and eclampsia. Number 33, January 2002.

Authors: 
Journal:  Obstet Gynecol       Date:  2002-01       Impact factor: 7.661

Review 7.  How accurate are maternal symptoms in predicting impending complications in women with preeclampsia? A systematic review and meta-analysis.

Authors:  Shakila Thangaratinam; Ioannis D Gallos; Neki Meah; Sa'ada Usman; Khaled M K Ismail; Khalid S Khan
Journal:  Acta Obstet Gynecol Scand       Date:  2011-04-15       Impact factor: 3.636

8.  Using clinical symptoms to predict adverse maternal and perinatal outcomes in women with preeclampsia: data from the PIERS (Pre-eclampsia Integrated Estimate of RiSk) study.

Authors:  Tin-Wing Yen; Beth Payne; Ziguang Qu; Jennifer A Hutcheon; Tang Lee; Laura A Magee; Barry N Walters; Peter von Dadelszen
Journal:  J Obstet Gynaecol Can       Date:  2011-08

9.  Induction of labour versus expectant monitoring for gestational hypertension or mild pre-eclampsia after 36 weeks' gestation (HYPITAT): a multicentre, open-label randomised controlled trial.

Authors:  Corine M Koopmans; Denise Bijlenga; Henk Groen; Sylvia Mc Vijgen; Jan G Aarnoudse; Dick J Bekedam; Paul P van den Berg; Karin de Boer; Jan M Burggraaff; Kitty Wm Bloemenkamp; Addy P Drogtrop; Arie Franx; Christianne Jm de Groot; Anjoke Jm Huisjes; Anneke Kwee; Aren J van Loon; Annemiek Lub; Dimitri Nm Papatsonis; Joris Am van der Post; Frans Jme Roumen; Hubertina Cj Scheepers; Christine Willekes; Ben Wj Mol; Maria G van Pampus
Journal:  Lancet       Date:  2009-08-03       Impact factor: 79.321

Review 10.  Estimation of proteinuria as a predictor of complications of pre-eclampsia: a systematic review.

Authors:  Shakila Thangaratinam; Arri Coomarasamy; Fidelma O'Mahony; Steve Sharp; Javier Zamora; Khalid S Khan; Khaled M K Ismail
Journal:  BMC Med       Date:  2009-03-24       Impact factor: 8.775

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  2 in total

1.  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

Review 2.  Cardiometabolic Risk Factors in Pregnancy and Implications for Long-Term Health: Identifying the Research Priorities for Low-Resource Settings.

Authors:  Shobhana Nagraj; Stephen H Kennedy; Robyn Norton; Vivekananda Jha; Devarsetty Praveen; Lisa Hinton; Jane E Hirst
Journal:  Front Cardiovasc Med       Date:  2020-03-20
  2 in total

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