Iron Deficiency Anemia in Pregnancy and Treatment Options: A Patient-Preference Study [1L]
Bibliographic record
Abstract
INTRODUCTION: As many as 17% of Canadian women suffer from iron deficiency anemia (IDA) in pregnancy. Treatment options include oral ferrous salts, haem iron, intravenous (IV) iron and blood transfusions. Trade-offs pregnant women are willing to make to alleviate symptoms of IDA have not been determined. This study elicits preferences of pregnant women for health-states arising from IDA and the use of various treatment options. METHODS: A cross-sectional study was conducted on pregnant women with and without IDA. Participants were presented with five vignettes representing maternal health-states arising from IDA in pregnancy. They were asked to rank these states and assign them values on a visual analogue scale, by the standard gamble, and by time trade-off methods. Utility values (preferences) of women with and without IDA, obtained from these methods were presented on a scale of 0-100 where 0 represented death and 100 represented perfect health. RESULTS: 60 pregnant women (30 with IDA and 30 without) completed the interviews. With all three methods, utility values were lowest for blood transfusion and highest for oral iron. Regardless of the evaluation method, there was no difference in utility values for treatment with oral ferrous salts vs. haem iron or between women with or without IDA. CONCLUSION: Women acknowledge that symptoms of IDA in pregnancy reduce quality of life. Despite side effects and frequency of administration, oral iron is preferred over IV iron and blood transfusion. Confirmation of these findings in larger studies would directly inform clinical practice and research.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".