Reticulocyte haemoglobin equivalent (RET-He) as an early marker of responsiveness to oral iron supplementation
Bibliographic record
Abstract
Aim We investigated the potential of reticulocyte haemoglobin equivalent (RET-He) as an early marker of responsiveness to iron supplementation. Methods Data were obtained from a randomised controlled trial of daily iron supplementation in 356 Cambodian women (18–45 y) who received 60 mg elemental iron for 12 weeks. A fasted venous blood specimen was collected at baseline, 1-week and 12-week timepoints. Whole blood haemoglobin (g/L) and RET-He (pg) were measured using a Sysmex haematology analyser. RET-He measures were evaluated for their predictive ability on haemoglobin response to iron supplementation (defined as ≥10 g/L at 12 weeks). Receiver operating characteristic (ROC) curves were used to assess discrimination performance, and the area under the ROC curve (AUC ROC ) served as a measure of the ability of each predictor to discriminate between women likely or unlikely to elicit a haemoglobin response. Results Predictive ability (AUC ROC (95% CI)) of baseline, 1-week, and change from baseline to 1-week RET-He on haemoglobin response was 0.70 (0.63 to 0.76), 0.48 (0.41 to 0.56) and 0.81 (0.75 to 0.87), respectively. Based on the Youden index, an absolute increase in RET-He of ~1.1 pg or a percentage increase of ~4.4% over 1 week were optimal thresholds to predict responsiveness to iron supplementation. Conclusion Single timepoint RET-He measures have poor predictive ability; however, change in RET-He after 1 week was a strong predictor of haemoglobin response among Cambodian women receiving 60 mg elemental iron and can be measured easily and quickly after only 1 week of iron therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".