A Method Comparison Study between Two Hemoglobinometer Models (Hemocue Hb 301 and Hb 201+) to Measure Hemoglobin Concentrations And Estimate Anemia Prevalence among Women in Preah Vihear, Cambodia
Bibliographic record
Abstract
Background Anemia affects 1.62 billion people worldwide. Defined as a hemoglobin (Hb) concentration <120 g/L for non‐pregnant women, anemia can negatively impact pregnancy outcomes and reduce work capacity. Hb is often measured in global health and nutrition surveys using a portable hemoglobinomter such as the Hemocue Hb 201+ (Hemocue, Angelholm, Sweden). More recently, a newer model was released (Hemocue Hb 301) utilizing slightly different methods to measure Hb as compared to the older model. Objective To measure bias and concordance between Hb concentrations using the Hemocue Hb 301 and Hb 201+ models in a rural field setting. Methods Hb concentration was measured in 175 rural Cambodian women (18–49 y) from Preah Vihear province using three Hemocue Hb 301 and three Hemocue Hb 201+ machines and using the same finger prick of blood in alternating order. Half of the samples (n=94) were measured using the Hb 301 model first, and the remaining samples (n=81) with the Hb 201+ first. Bias (the difference in means) and concordance were determined. Results Overall, mean ± SD Hb concentration was 116 ± 13 g/L using the Hb 201+ and 118 ± 12 g/L using the Hb 301. Anemia prevalence (Hb <120 g/L) for the Hb 201+ and Hb 301 was 58.3% (n=102) and 57.7% (n=101), respectively. Bias ± SD between methods was 2.0 ± 10.5 g/L and concordance (95% CI) was 0.63 (0.54, 0.72). Conclusions Bias was low and concordance was high between the two models, suggesting that the new Hemocue Hb 301 measures anemia prevalence comparably to the previous Hemocue Hb 201+ model. Further, anemia prevalence was very similar among the two models (57.7 vs. 58.3). The comparability of Hb measurements among different Hemocue models has important implications for the accurate estimations of anemia prevalence across time and among different surveys . Support or Funding Information The funding for this study was provided by the Danish Red Cross (Copenhagen, Denmark) and the University of Guelph (Guelph, Canada).
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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 | 0.040 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".