Point-of-care Diagnostic for Foetal Haemoglobin in Kids for Sickle Cell Disease in Ghana
Bibliographic record
Abstract
Abstract Presentation Date: 6/9/2024 Presentation Start Time: 2:30:00 PM Background Sickle cell disease (SCD) is an inherited blood disorder which causes acute and chronic complications and can result in early death. About three-fourth of patients with SCD live in sub-Saharan Africa; in Ghana, 1 in 50 newborns are affected with SCD. Foetal hemoglobin (Hb F) level is a strong modifier of SCD severity. High levels of Hb F inhibit sickling and hemolysis and reduce disease morbidity and mortality. Hb F monitoring is also used to assess adherence and response to disease modifying therapy such as hydroxyurea. Standard hemoglobin electrophoretic techniques are unable to quantify Hb F. In resource-limited settings like Ghana, the use of high-performance liquid chromatography (HPLC) for Hb F quantification is often challenging due to cost and logistic constraints such limited availability of adequate technology and appropriately trained personnel. In this study, we assessed the performance of a low-cost, point-of-care (POC), microchip based cellulose acetate electrophoresis “GazelleTM” compared to HPLC for Hb F quantification in children with SCD in Ghana. GazelleTM is a fast ( < 8 minutes), easy-to-use test which can be performed by minimally trained end-users using only a finger-prick volume of blood. Methods This cross-sectional study was conducted at the paediatric SCD Clinic in Korle Bu Teaching Hospital, Accra, Ghana. Study participants were children of ages ≥ 1 year to 16 years who were known to have sickle cell disease and were about to commence or were on hydroxyurea therapy and followed at the SCD clinic. Results A total of 532 children were included in the analysis. Gazelle showed a correlation of 0.98 (Pearson correlation) when compared to HPLC. Conclusions Haemoglobin variants are quantified by Gazelle offering the ability to monitor disease modifying therapy in SCD such as hydroxyurea, where quantification of Hb F levels is important in assessing treatment adherence and determining response to therapy. Gazelle has the potential to be utilized as a POC test for quantification of Hb F levels in monitoring hydroxyurea therapy for children with SCD, especially in limited-resource settings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".