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Mitrogiannis I, Evangelou E, Efthymiou A, Kanavos T, Birbas E, Makrydimas G, Papatheodorou S. Risk factors for preterm birth: an umbrella review of meta-analyses of observational studies. BMC Med 2023; 21:494. [PMID: 38093369 PMCID: PMC10720103 DOI: 10.1186/s12916-023-03171-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 11/09/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Preterm birth defined as delivery before 37 gestational weeks is a leading cause of neonatal and infant morbidity and mortality. The aim of this study is to summarize the evidence from meta-analyses of observational studies on risk factors associated with PTB, evaluate whether there are indications of biases in this literature, and identify which of the previously reported associations are supported by robust evidence. METHODS We searched PubMed and Scopus until February 2021, in order to identify meta-analyses examining associations between risk factors and PTB. For each meta-analysis, we estimated the summary effect size, the 95% confidence interval, the 95% prediction interval, the between-study heterogeneity, evidence of small-study effects, and evidence of excess-significance bias. Evidence was graded as robust, highly suggestive, suggestive, and weak. RESULTS Eighty-five eligible meta-analyses were identified, which included 1480 primary studies providing data on 166 associations, covering a wide range of comorbid diseases, obstetric and medical history, drugs, exposure to environmental agents, infections, and vaccines. Ninety-nine (59.3%) associations were significant at P < 0.05, while 41 (24.7%) were significant at P < 10-6. Ninety-one (54.8%) associations had large or very large heterogeneity. Evidence for small-study effects and excess significance bias was found in 37 (22.3%) and 12 (7.2%) associations, respectively. We evaluated all associations according to prespecified criteria. Seven risk factors provided robust evidence: amphetamine exposure, isolated single umbilical artery, maternal personality disorder, sleep-disordered breathing (SDB), prior induced termination of pregnancy with vacuum aspiration (I-TOP with VA), low gestational weight gain (GWG), and interpregnancy interval (IPI) following miscarriage < 6 months. CONCLUSIONS The results from the synthesis of observational studies suggest that seven risk factors for PTB are supported by robust evidence. Routine screening for sleep quality and mental health is currently lacking from prenatal visits and should be introduced. This assessment can promote the development and training of prediction models using robust risk factors that could improve risk stratification and guide cost-effective preventive strategies. TRIAL REGISTRATION PROSPERO 2021 CRD42021227296.
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Affiliation(s)
- Ioannis Mitrogiannis
- Department of Obstetrics & Gynecology, General Hospital of Arta, 47100, Arta, Greece
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, Imperial College London, London, SW7 2AZ, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, 45110, Ioannina, Greece
| | - Athina Efthymiou
- Harris Birthright Research Centre for Fetal Medicine, King's College London, London, SE5 8BB, UK
- Department of Women and Children Health, NHS Foundation Trust, Guy's and St Thomas, London, SE1 7EH, UK
| | | | | | - George Makrydimas
- Department of Obstetrics & Gynecology, University Hospital of Ioannina, 45110, Ioannina, Greece
| | - Stefania Papatheodorou
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
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Mitrogiannis I, Evangelou E, Efthymiou A, Kanavos T, Birbas E, Makrydimas G, Papatheodorou S. Risk factors for preterm labor: An Umbrella Review of meta-analyses of observational studies. RESEARCH SQUARE 2023:rs.3.rs-2639005. [PMID: 36993288 PMCID: PMC10055511 DOI: 10.21203/rs.3.rs-2639005/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Preterm birth defined as delivery before 37 gestational weeks, is a leading cause of neonatal and infant morbidity and mortality. Understanding its multifactorial nature may improve prediction, prevention and the clinical management. We performed an umbrella review to summarize the evidence from meta-analyses of observational studies on risks factors associated with PTB, evaluate whether there are indications of biases in this literature and identify which of the previously reported associations are supported by robust evidence. We included 1511 primary studies providing data on 170 associations, covering a wide range of comorbid diseases, obstetric and medical history, drugs, exposure to environmental agents, infections and vaccines. Only seven risk factors provided robust evidence. The results from synthesis of observational studies suggests that sleep quality and mental health, risk factors with robust evidence should be routinely screened in clinical practice, should be tested in large randomized trial. Identification of risk factors with robust evidence will promote the development and training of prediction models that could improve public health, in a way that offers new perspectives in health professionals.
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Mohan M, Prabhu SS, Pullattayil AK, Lindow S. A meta-analysis of the prevalence of gestational diabetes in patients diagnosed with obstetrical cholestasis. AJOG GLOBAL REPORTS 2021; 1:100013. [PMID: 36277255 PMCID: PMC9563540 DOI: 10.1016/j.xagr.2021.100013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Gestational diabetes and obstetrical cholestasis are common clinical conditions seen in clinical practice. There is evidence suggesting a coexisting relationship that could have a potential clinical implication related to stillbirth outcomes. OBJECTIVE This study aimed to determine the prevalence of gestational diabetes in women with obstetrical cholestasis. STUDY DESIGN A predefined protocol with a literature search was used to obtain all possible articles. A systematic review and meta-analysis of observational studies with quantifiable data published since 2010 were performed. Articles were evaluated and included in the study with specified criteria for the risk of bias using the Newcastle-Ottawa Scale. A meta-analysis was performed using Meta-analysis of Observational Studies in Epidemiology specifications to determine the prevalence of gestational diabetes in women with obstetrical cholestasis. RESULTS A total of 16,748 patients with obstetrical cholestasis from 21 studies were included. The prevalence of gestational diabetes in women with obstetrical cholestasis was 13.9% (20 studies analyzed). Gestational diabetes was more common in women with obstetrical cholestasis than in women without obstetrical cholestasis (odds ratio, 2.129; 95% confidence interval, 1.697–2.670;10 studies). Gestational diabetes is twice more common in women with severe cholestasis than in women with mild cholestasis (odds ratio, 2.168; 95% confidence interval, 1.429–3.289; 4 studies). CONCLUSION There is an increase in the prevalence of gestational diabetes among women diagnosed with obstetrical cholestasis. Compared with women with mild cholestasis, the increased risk of gestational diabetes in women with severe cholestatis is more than doubled. This suggests that the 2 conditions may have some biological similarities that affect clinical outcomes.
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Townsend R, Sileo FG, Allotey J, Dodds J, Heazell A, Jorgensen L, Kim VB, Magee L, Mol B, Sandall J, Smith G, Thilaganathan B, von Dadelszen P, Thangaratinam S, Khalil A. Prediction of stillbirth: an umbrella review of evaluation of prognostic variables. BJOG 2020; 128:238-250. [PMID: 32931648 DOI: 10.1111/1471-0528.16510] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/17/2020] [Indexed: 12/23/2022]
Abstract
BACKGROUND Stillbirth accounts for over 2 million deaths a year worldwide and rates remains stubbornly high. Multivariable prediction models may be key to individualised monitoring, intervention or early birth in pregnancy to prevent stillbirth. OBJECTIVES To collate and evaluate systematic reviews of factors associated with stillbirth in order to identify variables relevant to prediction model development. SEARCH STRATEGY MEDLINE, Embase, DARE and Cochrane Library databases and reference lists were searched up to November 2019. SELECTION CRITERIA We included systematic reviews of association of individual variables with stillbirth without language restriction. DATA COLLECTION AND ANALYSIS Abstract screening and data extraction were conducted in duplicate. Methodological quality was assessed using AMSTAR and QUIPS criteria. The evidence supporting association with each variable was graded. RESULTS The search identified 1198 citations. Sixty-nine systematic reviews reporting 64 variables were included. The most frequently reported were maternal age (n = 5), body mass index (n = 6) and maternal diabetes (n = 5). Uterine artery Doppler appeared to have the best performance of any single test for stillbirth. The strongest evidence of association was for nulliparity and pre-existing hypertension. CONCLUSION We have identified variables relevant to the development of prediction models for stillbirth. Age, parity and prior adverse pregnancy outcomes had a more convincing association than the best performing tests, which were PAPP-A, PlGF and UtAD. The evidence was limited by high heterogeneity and lack of data on intervention bias. TWEETABLE ABSTRACT Review shows key predictors for use in developing models predicting stillbirth include age, prior pregnancy outcome and PAPP-A, PLGF and Uterine artery Doppler.
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Affiliation(s)
- R Townsend
- Molecular and Clinical Sciences Research Institute, St George's, University of London and St George's University Hospitals NHS Foundation Trust, London, UK.,Fetal Medicine Unit, St George's University Hospitals NHS Foundation Trust, London, UK
| | - F G Sileo
- Molecular and Clinical Sciences Research Institute, St George's, University of London and St George's University Hospitals NHS Foundation Trust, London, UK.,Fetal Medicine Unit, St George's University Hospitals NHS Foundation Trust, London, UK
| | - J Allotey
- Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK.,Pragmatic Clinical Trials Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - J Dodds
- Pragmatic Clinical Trials Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.,Centre for Women's Health, Institute of Population Health Sciences, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - A Heazell
- St Mary's Hospital, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK.,Faculty of Biology, Medicine and Health, Maternal and Fetal Health Research Centre, School of Medical Sciences, University of Manchester, Manchester, UK
| | | | - V B Kim
- The Robinson Institute, University of Adelaide, Adelaide, SA, Australia
| | - L Magee
- Faculty of Life Sciences and Medicine, School of Life Course Sciences, King's College London, London, UK
| | - B Mol
- Department of Obstetrics and Gynaecology, School of Medicine, Monash University, Melbourne, Vic., Australia
| | - J Sandall
- Health Service and Population Research Department, Centre for Implementation Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Department of Women and Children's Health, Faculty of Life Sciences & Medicine, School of Life Course Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Gcs Smith
- Department of Obstetrics and Gynaecology, University of Cambridge, NIHR Cambridge Biomedical Research Centre, Cambridge, UK.,Department of Physiology, Development and Neuroscience, Centre for Trophoblast Research (CTR), University of Cambridge, Cambridge, UK
| | - B Thilaganathan
- Molecular and Clinical Sciences Research Institute, St George's, University of London and St George's University Hospitals NHS Foundation Trust, London, UK.,Fetal Medicine Unit, St George's University Hospitals NHS Foundation Trust, London, UK
| | - P von Dadelszen
- Faculty of Life Sciences and Medicine, School of Life Course Sciences, King's College London, London, UK
| | - S Thangaratinam
- Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK.,Pragmatic Clinical Trials Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - A Khalil
- Molecular and Clinical Sciences Research Institute, St George's, University of London and St George's University Hospitals NHS Foundation Trust, London, UK.,Fetal Medicine Unit, St George's University Hospitals NHS Foundation Trust, London, UK
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