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Ukah UV, De Silva DA, Payne B, Magee LA, Hutcheon JA, Brown H, Ansermino JM, Lee T, von Dadelszen P. Prediction of adverse maternal outcomes from pre-eclampsia and other hypertensive disorders of pregnancy: A systematic review. Pregnancy Hypertens 2017; 11:115-123. [PMID: 29198742 DOI: 10.1016/j.preghy.2017.11.006] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Revised: 11/03/2017] [Accepted: 11/20/2017] [Indexed: 01/04/2023]
Abstract
BACKGROUND The hypertensive disorders of pregnancy are a leading cause of maternal and perinatal mortality and morbidity. The ability to predict these complications using simple tests could aid in management and improve outcomes. We aimed to systematically review studies that reported on potential predictors of adverse maternal outcomes among women with a hypertensive disorder of pregnancy. METHODS We searched MEDLINE, Embase and CINAHL (inception - December 2016) for studies of predictors of severe maternal complications among women with a hypertensive disorder of pregnancy. Studies were selected in a two-stage process by two independent reviewers, excluding those reporting only on adverse fetal outcomes. We extracted data on study and test(s) characteristics and outcomes. Accuracy of prediction was assessed using sensitivity, specificity, likelihood ratios and area under the receiver operating curve (AUROC). Strong evidence of prediction was taken to be a positive likelihood ratio >10 or a negative likelihood ratio <0.1, and for multivariable models, an AUROC ≥0.70. Bivariate random effects models were used to summarise performance when possible. RESULTS Of 32 studies included, 28 presented only model development and four examined external validation. Tests included symptoms and signs, laboratory tests and biomarkers. No single test was a strong independent predictor of outcome. The most promising prediction was with multivariable models, especially when oxygen saturation, or chest pain/dyspnea were included. CONCLUSION Future studies should investigate combinations of tests in multivariable models (rather than single predictors) to improve identification of women at high risk of adverse outcomes in the setting of the hypertensive disorders of pregnancy.
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Affiliation(s)
- U Vivian Ukah
- Department of Obstetrics and Gynaecology, University of British Columbia, Vancouver, BC, Canada; Healthy Starts Theme, BC Children's Hospital Research, Vancouver, BC, Canada.
| | - Dane A De Silva
- Department of Obstetrics and Gynaecology, University of British Columbia, Vancouver, BC, Canada
| | - Beth Payne
- Healthy Starts Theme, BC Children's Hospital Research, Vancouver, BC, Canada; Department of Anaesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Laura A Magee
- School of Life Course Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Jennifer A Hutcheon
- Department of Obstetrics and Gynaecology, University of British Columbia, Vancouver, BC, Canada
| | - Helen Brown
- Woodward Library, University of British Columbia, Vancouver, BC, Canada
| | - J Mark Ansermino
- Healthy Starts Theme, BC Children's Hospital Research, Vancouver, BC, Canada
| | - Tang Lee
- Department of Obstetrics and Gynaecology, University of British Columbia, Vancouver, BC, Canada; Healthy Starts Theme, BC Children's Hospital Research, Vancouver, BC, Canada
| | - Peter von Dadelszen
- School of Life Course Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
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Thangaratinam S, Allotey J, Marlin N, Dodds J, Cheong-See F, von Dadelszen P, Ganzevoort W, Akkermans J, Kerry S, Mol BW, Moons KGM, Riley RD, Khan KS. Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models. BMC Med 2017; 15:68. [PMID: 28356148 PMCID: PMC5372261 DOI: 10.1186/s12916-017-0827-3] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Accepted: 02/23/2017] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Unexpected clinical deterioration before 34 weeks gestation is an undesired course in early-onset pre-eclampsia. To safely prolong preterm gestation, accurate and timely prediction of complications is required. METHOD Women with confirmed early onset pre-eclampsia were recruited from 53 maternity units in the UK to a large prospective cohort study (PREP-946) for development of prognostic models for the overall risk of experiencing a complication using logistic regression (PREP-L), and for predicting the time to adverse maternal outcome using a survival model (PREP-S). External validation of the models were carried out in a multinational cohort (PIERS-634) and another cohort from the Netherlands (PETRA-216). Main outcome measures were C-statistics to summarise discrimination of the models and calibration plots and calibration slopes. RESULTS A total of 169 mothers (18%) in the PREP dataset had adverse outcomes by 48 hours, and 633 (67%) by discharge. The C-statistics of the models for predicting complications by 48 hours and by discharge were 0.84 (95% CI, 0.81-0.87; PREP-S) and 0.82 (0.80-0.84; PREP-L), respectively. The PREP-S model included maternal age, gestation, medical history, systolic blood pressure, deep tendon reflexes, urine protein creatinine ratio, platelets, serum alanine amino transaminase, urea, creatinine, oxygen saturation and treatment with antihypertensives or magnesium sulfate. The PREP-L model included the above except deep tendon reflexes, serum alanine amino transaminase and creatinine. On validation in the external PIERS dataset, the reduced PREP-S model showed reasonable calibration (slope 0.80) and discrimination (C-statistic 0.75) for predicting adverse outcome by 48 hours. Reduced PREP-L model showed excellent calibration (slope: 0.93 PIERS, 0.90 PETRA) and discrimination (0.81 PIERS, 0.75 PETRA) for predicting risk by discharge in the two external datasets. CONCLUSIONS PREP models can be used to obtain predictions of adverse maternal outcome risk, including early preterm delivery, by 48 hours (PREP-S) and by discharge (PREP-L), in women with early onset pre-eclampsia in the context of current care. They have a potential role in triaging high-risk mothers who may need transfer to tertiary units for intensive maternal and neonatal care. TRIAL REGISTRATION ISRCTN40384046 , retrospectively registered.
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Affiliation(s)
- Shakila Thangaratinam
- Women’s Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Multidisciplinary Evidence Synthesis Hub (mEsh), Queen Mary University of London, London, UK
| | - John Allotey
- Women’s Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Multidisciplinary Evidence Synthesis Hub (mEsh), Queen Mary University of London, London, UK
| | - Nadine Marlin
- Pragmatic Clinical Trials Unit, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University London, London, UK
| | - Julie Dodds
- Women’s Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Multidisciplinary Evidence Synthesis Hub (mEsh), Queen Mary University of London, London, UK
| | - Fiona Cheong-See
- Women’s Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Multidisciplinary Evidence Synthesis Hub (mEsh), Queen Mary University of London, London, UK
| | - Peter von Dadelszen
- Institute of Cardiovascular and Cell Sciences, St George’s, University of London, London, UK
| | - Wessel Ganzevoort
- Departments of Obstetrics and Gynecology, University of Amsterdam, Academic Medical Center, Amsterdam, The Netherlands
| | - Joost Akkermans
- Department of Obstetrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Sally Kerry
- Pragmatic Clinical Trials Unit, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University London, London, UK
| | - Ben W. Mol
- The Robinson Research Institute, School of Paediatrics and Reproductive Health, University of Adelaide, Adelaide, Australia
- The South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Karl G. M. Moons
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Richard D. Riley
- Research Institute for Primary Care and Health Sciences, Keele University, Keele, Staffordshire UK
| | - Khalid S. Khan
- Women’s Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Multidisciplinary Evidence Synthesis Hub (mEsh), Queen Mary University of London, London, UK
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