Assessing Accuracy and Precision of Hemoglobin Determination in Venous, Capillary Pool, and Single-Drop Capillary Blood Specimens Using three Different HemoCue® Hb Models: The Multicountry Hemoglobin Measurement (HEME) Study
Bibliographic record
Abstract
BACKGROUND: Anemia prevalence estimates reported in population surveys can vary based on the blood specimen source (capillary or venous) and analytic device (hematology autoanalyzers or portable hemoglobinometers) used for hemoglobin (Hb) determination. OBJECTIVES: This study aimed to compare accuracy and precision of Hb measurement in three blood specimen types on three models of hemoglobinometers against the results from venous blood from the same individuals measured on automated analyzers (AAs). METHODS: This multisite (Cambodia, Ethiopia, Guatemala, Lebanon, Nigeria, and Tanzania) study assessed Hb measurements in paired venous and capillary blood specimens from apparently healthy women (aged 15-49 y) and children (aged 12-59 mo) using three HemoCue® Hb models (201+, 301, and 801). Measurements were compared against reference values: venous blood in hematology AA and adjusted via regression calibration or mean difference in HemoCue® Hb. Venous, capillary pool, and single-drop capillary blood specimens were assessed for accuracy and precision. RESULTS: Venous blood measured using HemoCue® Hb 301 exhibited a positive mean error, whereas responses in HemoCue® Hb 201+ and 801 were nondirectional compared with the reference. Adjustment with the reference harmonized mean errors for all devices across study sites to <1.0 g/L using venous blood. Precision was highest for venous blood (±5-16 g/L) in all sites, lowest for single-drop capillary (±9-37 g/L), and intermediate (±9-28 g/L) for capillary pool blood specimen. Imprecision differed across sites, especially with both capillary blood specimens, suggesting different levels of personnel skills. CONCLUSIONS: Findings suggest that venous blood is needed for accurate and precise Hb determination. Single-drop capillary blood use should be discouraged owing to high measurement variability. Further research should evaluate the viability and reliability of capillary pool blood for this purpose. Accuracy of HemoCue® Hb devices can be improved via standardization against results from venous blood assessed using AA.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".