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Journal ArticleDOI

Prevention of perinatal death and adverse perinatal outcome using low-dose aspirin: a meta-analysis

TL;DR: To compare early vs late administration of low‐dose aspirin on the risk of perinatal death and adversePerinatal outcome, a large number of patients with at-risk children were referred for treatment with aspirin.
Abstract: Objective Tocompareearly vslateadministrationoflowdose aspirin on the risk of perinatal death and adverse perinatal outcome. Methods Databases were searched for keywords related to aspirin and pregnancy. Only randomized controlled trials that evaluated the prophylactic use of low-dose aspirin(50–150mg/day)during pregnancywereincluded. The primary outcome combined fetal and neonatal death. Pooled relative risks (RR) with their 95% CIs were compared according to gestational age at initiation of low-dose aspirin (≤16 vs >16 weeks of gestation). Results Out of 8377 citations, 42 studies (27222 women) were included. Inclusion criteria were risk factors for pre-eclampsia, including: nulliparity, multiple pregnancy, chronic hypertension, cardiovascular or endocrine disease, prior gestational hypertension or fetal growth restriction, and/or abnormal uterine artery Doppler. When compared with controls, low-dose aspirin started at ≤16 weeks’ gestation compared with low-dose aspirin started at >16 weeks’ gestation was associated with a greater reduction of perinatal death (RR =0.41 (95% CI, 0.19–0.92) vs 0.93 (95% CI, 0.73–1.19), P =0.02),pre-eclampsia(RR =0.47(95%CI,0.36–0.62) vs 0.78 (95% CI, 0.61–0.99), P < 0.01), severe preeclampsia (RR =0.18 (95% CI, 0.08–0.41) vs 0.65 (95% CI, 0.40–1.07), P < 0.01), fetal growth restriction (RR =0.46 (95% CI, 0.33–0.64) vs 0.98 (95% CI, 0.88–1.08), P < 0.001) and preterm birth (RR =0.35 (95% CI, 0.22–0.57) vs 0.90 (95% CI, 0.83–0.97), P < 0.001).
Citations
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TL;DR: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascul...
Abstract: Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascul...

3,034 citations

Journal ArticleDOI
TL;DR: The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update as discussed by the authors .
Abstract: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

1,483 citations

Journal ArticleDOI
TL;DR: Treatment with low‐dose aspirin in women at high risk for preterm preeclampsia resulted in a lower incidence of this diagnosis than placebo, and there were no significant between‐group differences in the incidence of neonatal adverse outcomes or other adverse events.
Abstract: BackgroundPreterm preeclampsia is an important cause of maternal and perinatal death and complications. It is uncertain whether the intake of low-dose aspirin during pregnancy reduces the risk of preterm preeclampsia. MethodsIn this multicenter, double-blind, placebo-controlled trial, we randomly assigned 1776 women with singleton pregnancies who were at high risk for preterm preeclampsia to receive aspirin, at a dose of 150 mg per day, or placebo from 11 to 14 weeks of gestation until 36 weeks of gestation. The primary outcome was delivery with preeclampsia before 37 weeks of gestation. The analysis was performed according to the intention-to-treat principle. ResultsA total of 152 women withdrew consent during the trial, and 4 were lost to follow up, which left 798 participants in the aspirin group and 822 in the placebo group. Preterm preeclampsia occurred in 13 participants (1.6%) in the aspirin group, as compared with 35 (4.3%) in the placebo group (odds ratio in the aspirin group, 0.38; 95% confidenc...

1,299 citations

Journal ArticleDOI
19 Apr 2016-BMJ
TL;DR: A practical evidence based list of clinical risk factors that can be assessed by a clinician at ≤16 weeks’ gestation to estimate a woman’s risk of pre-eclampsia and the use of aspirin prophylaxis in pregnancy is developed.
Abstract: Objective To develop a practical evidence based list of clinical risk factors that can be assessed by a clinician at ≤16 weeks’ gestation to estimate a woman’s risk of pre-eclampsia. Design Systematic review and meta-analysis of cohort studies. Data sources PubMed and Embase databases, 2000-15. Eligibility criteria for selecting studies Cohort studies with ≥1000 participants that evaluated the risk of pre-eclampsia in relation to a common and generally accepted clinical risk factor assessed at ≤16 weeks’ gestation. Data extraction Two independent reviewers extracted data from included studies. A pooled event rate and pooled relative risk for pre-eclampsia were calculated for each of 14 risk factors. Results There were 25 356 688 pregnancies among 92 studies. The pooled relative risk for each risk factor significantly exceeded 1.0, except for prior intrauterine growth restriction. Women with antiphospholipid antibody syndrome had the highest pooled rate of pre-eclampsia (17.3%, 95% confidence interval 6.8% to 31.4%). Those with prior pre-eclampsia had the greatest pooled relative risk (8.4, 7.1 to 9.9). Chronic hypertension ranked second, both in terms of its pooled rate (16.0%, 12.6% to 19.7%) and pooled relative risk (5.1, 4.0 to 6.5) of pre-eclampsia. Pregestational diabetes (pooled rate 11.0%, 8.4% to 13.8%; pooled relative risk 3.7, 3.1 to 4.3), prepregnancy body mass index (BMI) >30 (7.1%, 6.1% to 8.2%; 2.8, 2.6 to 3.1), and use of assisted reproductive technology (6.2%, 4.7% to 7.9%; 1.8, 1.6 to 2.1) were other prominent risk factors. Conclusions There are several practical clinical risk factors that, either alone or in combination, might identify women in early pregnancy who are at “high risk” of pre-eclampsia. These data can inform the generation of a clinical prediction model for pre-eclampsia and the use of aspirin prophylaxis in pregnancy.

611 citations

Journal ArticleDOI
TL;DR: Preeclampsia and fetal growth restriction using aspirin in early pregnancy is associated with a dose‐response effect, with higher dosages of aspirin being associated with greater reduction of the 3 outcomes.

443 citations

References
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Journal ArticleDOI
TL;DR: Moher et al. as mentioned in this paper introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses, which is used in this paper.
Abstract: David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses

62,157 citations

Journal Article
TL;DR: The QUOROM Statement (QUality Of Reporting Of Meta-analyses) as mentioned in this paper was developed to address the suboptimal reporting of systematic reviews and meta-analysis of randomized controlled trials.
Abstract: Systematic reviews and meta-analyses have become increasingly important in health care. Clinicians read them to keep up to date with their field,1,2 and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research,3 and some health care journals are moving in this direction.4 As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers' ability to assess the strengths and weaknesses of those reviews. Several early studies evaluated the quality of review reports. In 1987, Mulrow examined 50 review articles published in 4 leading medical journals in 1985 and 1986 and found that none met all 8 explicit scientific criteria, such as a quality assessment of included studies.5 In 1987, Sacks and colleagues6 evaluated the adequacy of reporting of 83 meta-analyses on 23 characteristics in 6 domains. Reporting was generally poor; between 1 and 14 characteristics were adequately reported (mean = 7.7; standard deviation = 2.7). A 1996 update of this study found little improvement.7 In 1996, to address the suboptimal reporting of meta-analyses, an international group developed a guidance called the QUOROM Statement (QUality Of Reporting Of Meta-analyses), which focused on the reporting of meta-analyses of randomized controlled trials.8 In this article, we summarize a revision of these guidelines, renamed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), which have been updated to address several conceptual and practical advances in the science of systematic reviews (Box 1). Box 1 Conceptual issues in the evolution from QUOROM to PRISMA

46,935 citations

Journal ArticleDOI
04 Sep 2003-BMJ
TL;DR: A new quantity is developed, I 2, which the authors believe gives a better measure of the consistency between trials in a meta-analysis, which is susceptible to the number of trials included in the meta- analysis.
Abstract: Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice? Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis. Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4 Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted? A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …

45,105 citations

Journal ArticleDOI
13 Sep 1997-BMJ
TL;DR: Funnel plots, plots of the trials' effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials.
Abstract: Objective: Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Design: Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews . Main outcome measure: Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. Results: In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. Conclusions: A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution. Key messages Systematic reviews of randomised trials are the best strategy for appraising evidence; however, the findings of some meta-analyses were later contradicted by large trials Funnel plots, plots of the trials9 effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials Funnel plot asymmetry was found in 38% of meta-analyses published in leading general medicine journals and in 13% of reviews from the Cochrane Database of Systematic Reviews Critical examination of systematic reviews for publication and related biases should be considered a routine procedure

37,989 citations

Journal ArticleDOI
TL;DR: This paper examines eight published reviews each reporting results from several related trials in order to evaluate the efficacy of a certain treatment for a specified medical condition and suggests a simple noniterative procedure for characterizing the distribution of treatment effects in a series of studies.

33,234 citations

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