Abstract
BACKGROUND We aimed to address which antihypertensives are superior to placebo/no therapy or another antihypertensive for controlling nonsevere pregnancy hypertension and provide future sample size estimates for definitive evidence. METHODS Randomized trials of antihypertensives for nonsevere pregnancy hypertension were identified from online electronic databases, to February 28, 2021 (registration URL: https://www.crd.york.ac.uk/PROSPERO/; unique identifier: CRD42020188725). Our outcomes were severe hypertension, proteinuria/preeclampsia, fetal/newborn death, small-for-gestational age infants, preterm birth, and admission to neonatal care. A Bayesian random-effects model generated estimates of direct and indirect treatment comparisons. Trial sequential analysis informed future trials needed. RESULTS Of 1246 publications identified, 72 trials were included; 61 (6923 women) were informative. All commonly prescribed antihypertensives (labetalol, other β-blockers, methyldopa, calcium channel blockers, and mixed/multi-drug therapy) versus placebo/no therapy reduced the risk of severe hypertension by 30% to 70%. Labetalol decreased proteinuria/preeclampsia (odds ratio, 0.73 [95% credible interval, 0.54-0.99]) and fetal/newborn death (odds ratio, 0.54 [0.30-0.98]) compared with placebo/no therapy, and proteinuria/preeclampsia compared with methyldopa (odds ratio, 0.66 [0.44-0.99]) and calcium channel blockers (odds ratio, 0.63 [0.41-0.96]). No other differences were identified, but credible intervals were wide. Trial sequential analysis indicated that 2500 to 10 000 women/arm (severe hypertension or safety outcomes) to >15 000/arm (fetal/newborn death) would be required to provide definitive evidence. CONCLUSIONS In summary, all commonly prescribed antihypertensives in pregnancy reduce the risk of severe hypertension, but labetalol may also decrease proteinuria/preeclampsia and fetal/newborn death. Evidence is lacking for many other safety outcomes. Prohibitive sample sizes are required for definitive evidence. Real-world data are needed to individualize care.
