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Research · 02 of 05

Higher-dose vitamin D and preeclampsia: a signal of low certainty

Treat high-dose vitamin D for preeclampsia prevention as unproven until larger trials report.

Design
Systematic review and network meta-analysis of randomised trials
Population
8 trials, 4,078 high-risk pregnant women
Primary outcome
Incidence of preeclampsia versus placebo
Effect
Vitamin D 4,000 IU/day RR 0.21 (95% CI 0.06 to 0.72); 60,000 IU monthly RR 0.36 (0.19 to 0.70); statins and metformin inconsistent

A network meta-analysis combined eight randomised trials with 4,078 high-risk pregnant women, comparing statins, metformin and vitamin D regimens with placebo for preventing preeclampsia.

Higher-dose vitamin D regimens ranked best. Vitamin D 4,000 IU daily gave a risk ratio of 0.21 (95% CI 0.06 to 0.72) and 60,000 IU monthly gave 0.36 (0.19 to 0.70). The authors translate these to absolute differences of roughly 8% and 6%. Evidence for statins and metformin was inconsistent with wide intervals.

The authors themselves describe the certainty as low, the networks as sparse and the results as hypothesis-generating, not a basis for clinical practice. Rankings in a network meta-analysis show relative position, not proven effectiveness.

For now this is a reason to watch for larger trials, not to change prophylaxis. Low-dose aspirin for high-risk women remains the established approach that this analysis does not address.

  • Do not start high-dose vitamin D solely to prevent preeclampsia on this evidence.
  • Keep established risk-based prophylaxis in place; this analysis does not replace it.
  • Check vitamin D status and dose where deficiency is already a clinical concern.
  • Statin and metformin results were inconsistent; neither is supported for this use here.

Why it matters

A striking relative risk from small trials is a prompt for better trials, not for a change in antenatal prescribing.

Don't overread it

The authors rate the certainty as low and describe the findings as hypothesis-generating.

The statistics, in plain English

Very wide intervals such as 0.06 to 0.72 mean the true effect could be anywhere from large to modest. In a sparse network, a few small trials drive each estimate, so dramatic relative effects often shrink when bigger trials arrive.

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