Effect of once weekly folic acid supplementation on erythrocyte folate concentrations in women to determine potential to prevent neural tube defects: a randomised controlled dose-finding trial in Malaysia
Bibliographic record
Abstract
INTRODUCTION: Folic acid (0.4 mg) taken prior to and during early pregnancy reduces the risk of neural tube defects (NTDs). Because these birth defects occur early in pregnancy, before women may know they are pregnant, many countries have mandated the addition of folic acid to food staples. In countries where fortification is not possible, and weekly iron folic acid programmes exist to reduce anaemia, the WHO recommends that 2.8 mg (7×0.4 mg) folic acid be given instead of the current weekly practice of 0.4 mg. Currently, there is a lack of evidence to support if the 2.8 mg folic acid per week dose is sufficient to raise erythrocyte folate concentrations to a level associated with a reduced risk of a NTD-affected pregnancy. We aim to conduct a three-arm randomised controlled trial to determine the effect of weekly folic acid with iron on erythrocyte folate, a biomarker of NTD risk. METHODS AND ANALYSIS: We will recruit non-pregnant women (n=300; 18-45 years) from Selangor, Malaysia. Women will be randomised to receive either 2.8, 0.4 or 0.0 (placebo) mg folic acid with 60 mg iron weekly for 16 weeks, followed by a 4-week washout period. The primary outcome will be erythrocyte folate concentration at 16 weeks and the mean concentration will be compared between randomised treatment groups (intention-to-treat) using a linear regression model adjusting for the baseline measure. ETHICS AND DISSEMINATION: Ethical approval was obtained from the University of British Columbia (H18-00768) and Universiti Putra Malaysia (JKEUPM-2018-255). The results of this trial will be presented at scientific conferences and published in peer-reviewed journals. TRIAL REGISTRATION NUMBERS: ACTRN12619000818134 and NMRR-19-119-45736.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".