The Association Between the Risk of Hypertensive Disorders of Pregnancy and Folic Acid: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
PURPOSE: Although folic acid (FA) supplementation has been shown to reduce general cardiovascular risks, its impact on hypertensive disorders of pregnancy (HDP) is unclear. We performed a systematic review and meta-analysis to clarify the association between FA and the risk of HDP (pre-eclampsia (PE) and gestational hypertension (GH)). METHODS: PubMed, EmBase, and Cochrane Library were searched up to June 18, 2020, stratified by type of disease, initiation time of FA, form of FA and pre-conception Body Mass Index (BMI). The quality assessment of included studies was evaluated using Newcastle-Ottawa Scale (NOS) for cohort studies and Cochrane Collaboration's Risk of Bias Assessment Tool for randomized controlled trials (RCTs). Between-study heterogeneity was quantified using Cochran's Q-statistic and I2 statistics. Sensitivity analysis was performed by excluding the studies one by one, and publication bias was analyzed using funnel plots. RESULTS: Twenty studies with 359041 patients were identified for inclusion in the meta-analysis which included 3 RCTs and 17 cohort studies. Pooled estimates showed RR of 0.83 (95%CI 0.74-0.93, P=0.0008) for association between low dose FA (LD-FA) and the risk of PE, but LD-FA was not associated with GH (RR 1.05, 95% CI 0.97-1.13, P=0.20). In addition, the results of subgroup analysis showed that post-conception LD-FA had a 31% decreased risk of PE (RR 0.69, 95% CI 0.59-0.80, P<0.00001), and LD-FA in patients with pre-conception BMI<25 kg/m2 had a 32% decreased risk of PE (RR 0.68, 95% CI 0.56-0.81, P<0.0001) Conclusions: LD-FA significantly decreased the risk of PE but not GH, and post-conception LD-FA and pre-conception BMI<25 kg/m2 were considered as protective factors to reduce the risk of PE.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.041 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".