Point‐of‐care screening for sickle cell disease in low‐resource settings: A multi‐center evaluation of HemoTypeSC, a novel rapid test
Bibliographic record
Abstract
Sickle cell disease (SCD) is a common, life-threatening genetic disorder that is best managed when diagnosed early by newborn screening. However, SCD is most prevalent in low-resource regions of the world where newborn screening is rare and diagnosis at the point-of-care is challenging. In many such regions, the majority of affected children die, undiagnosed, before the age of 5 years. A rapid and affordable point-of-care test for SCD is needed. The diagnostic accuracy of HemoTypeSC, a point-of-care immunoassay, for SCD was evaluated in individuals who had SCD, hemoglobin C disease, the related carrier (trait) states, or a normal hemoglobin phenotype. Children and adults participated in low-, medium- and high-resource environments (Ghana [n = 383], Martinique [n = 46], and USA [n = 158]). Paired blood specimens were obtained for HemoTypeSC and a reference diagnostic assay. HemoTypeSC testing was performed at the site of blood collection, and the reference test was performed in a laboratory at each site. In 587 participants, across all study sites, HemoTypeSC had an overall sensitivity of 99.5% and specificity of 99.9% across all hemoglobin phenotypes. The test had 100% sensitivity and specificity for sickle cell anemia. Sensitivity and specificity for detection of normal and trait states were >99%. HemoTypeSC is an inexpensive (<$2 per test), accurate, and rapid point-of-care test that can be used in resource-limited regions with a high prevalence of SCD to provide timely diagnosis and support newborn screening programs.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".