Association and prediction of amniotic fluid measurements for adverse pregnancy outcome: systematic review and meta-analysis.

BACKGROUND

Measurements of amniotic fluid volume are used for pregnancy surveillance despite a lack of evidence for their predictive ability.

OBJECTIVE

To evaluate the association and predictive value of ultrasound measurements of amniotic fluid volume for adverse pregnancy outcome.

SEARCH STRATEGY

Electronic databases (inception to October 2011), reference lists, hand searching of journals, contact with experts.

SELECTION CRITERIA

Studies comparing measurements of amniotic fluid volume with adverse outcome, excluding pre-labour ruptured membranes or congenital/structural anomalies.

DATA COLLECTION

Data on study characteristics, design, quality. Random effects meta-analysis to estimate summary odds ratios (prognostic association) and summary sensitivity, specificity and likelihood ratios (predictive ability).

MAIN RESULTS

Forty-three studies (244,493 fetuses) were included demonstrating a strong association between oligohydramnios (varying definitions) and birthweight <10th centile (summary odds ratio [OR] 6.31, 95% confidence interval [95% CI] 4.15-9.58; high-risk population [author definition] n = 6 studies, 28,510 fetuses), and mortality (neonatal death any population summary OR 8.72, 95% CI 2.43-31.26; n = 6 studies, 55,735 fetuses; and perinatal mortality high-risk population summary OR 11.54, 95% CI 4.05-32.9; n = 2 studies, 27;891 fetuses). There was a strong association between polyhydramnios (maximum pool depth >8 cm or amniotic fluid index ≥25 cm) and birthweight >90th centile (OR 11.41, 95% CI 7.09-18.36; n = 1 study, 3960 fetuses). Despite strong associations, predictive accuracy for perinatal outcome was poor.

AUTHOR'S CONCLUSION: Current evidence suggests that oligohydramnios is strongly associated with being small for gestational age and mortality, and polyhydramnios with birthweight >90th centile. Despite strong associations with poor outcome, they do not accurately predict outcome risk for individuals.