Protocol and statistical analysis plan for a randomized controlled trial of the effect of intravenous iron on anemia in Malawian pregnant women in their third trimester (REVAMP – TT)
Bibliographic record
Abstract
<ns4:p> Background Anemia affects 40% of pregnant women globally, leading to maternal mortality, premature birth, low birth weight, and poor baby development. Iron deficiency causes over 40% of anemia cases in Africa. Oral iron supplementation is insufficient for Low-and-Middle-Income-Countries (LMICs) to meet current WHO targets. We hypothesized that a single intravenous dose of Ferric Carboxymaltose (FCM) may be more effective than oral iron treatment for anemia recovery, particularly in these settings where women present late for antenatal care. Methods This is a two-arm parallel open-label individual-randomized controlled trial in third trimester, in malaria Rapid Diagnostic Test-negative pregnant women with moderate or severe anemia - capillary hemoglobin <10 g/dL – who are randomized to receive either parenteral iron – with FCM – or standard-of-care oral iron for the remainder of pregnancy. This is the sister trial to the second-trimester <ns4:bold>REVAMP</ns4:bold> trial, funded by the Bill and Melinda Gates Foundation (trial registration ACTRN12618001268235, Gates Grant number INV-010612). In REVAMP-TT, recruitment and treatment are performed within primary health centers. The trial will recruit 590 women across Zomba district, Malawi. The primary outcome is the proportion of anemic women - venous hemoglobin <11 g/dL - at 36 weeks’ gestation or delivery (whichever occurs first). Other pre-specified key secondary clinical and safety outcomes include maternal iron-status and hypophosphatemia, neonate birth weight, infant growth and infant iron and hematological parameters. Discussion This study will determine whether FCM, delivered within primary health centers, is effective, safe and feasible for treating moderate to severe anemia in third-trimester pregnant Malawian women. This intervention could have long-term benefits for maternal and child health, resulting in improved survival and child development. </ns4:p>
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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 | 0.055 | 0.108 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.276 | 0.032 |
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".