Sickle cell disease (SCD) is an inherited blood disorder associated with acute illness and organ damage. In high resource settings, early screening and treatment greatly improve quality of life. In low resource settings, however, mortality rate for children is high (50-90%). Low-cost and accurate screening techniques are critical to reducing the burden of the disease, especially in remote/rural settings. The most common and severe form of SCD is sickle cell anemia (SCA), caused by the inheritance of genes causing abnormal forms of hemoglobin (called sickle hemoglobin or hemoglobin S) from both parents. The asymptomatic or carrier form of the disease, known as sickle cell trait (SCT), is caused by the inheritance of only one variant gene from one of the parents. In areas such as Nepal, β-thalassemia (another inherited blood disorder) and SCD are both prevalent, and some combinations of these diseases lead to severe symptoms.
The purpose of this study is to determine the accuracy of low-cost point-of-care techniques for screening and detecting sickle cell disease, sickle cell trait, and β-thalassaemia, which will subsequently inform on feasible solutions for detecting the disease in rural, remote, or low-resource settings. One of the goals of the study is to evaluate the feasibility of techniques, such as the sickling test with low-cost microscopy and machine learning, HbS solubility test, commercial lateral-flow assays (HemoTypeSC and Sickle SCAN), and the Gazelle Hb variant test, to supplement or replace gold standard tests (HPLC or electrophoresis), which are expensive, require highly trained personnel, and are not easily accessible in remote/rural settings.
The investigators hypothesize that:
an automated sickling test (standard sickling test enhanced using low-cost microscopy and machine learning) has a higher overall accuracy than conventional screening techniques (solubility and sickling tests) to detect hemoglobin S in blood samples
the automated sickling test can additionally classify SCD, SCT and healthy individuals with a sensitivity greater than 90%, based on morphology changes of red blood cells, unlike conventional sickling or solubility tests that do not distinguish between SCD and SCT cases
Gazelle diagnostic device can detect β-thalassaemia and SCD/SCT with an overall accuracy greater than 90%, compared with HPLC as the reference test
> 1 Year Years
Since the techniques evaluated in the study aims at detecting sickle cell disease (SCD), sickle cell trait (SCT), and β- thalassemia, the following number of participants will be included in Nepal:
20 individuals with SCD (HbSS)
20 individuals with SCT (HbAS)
20 individuals with sickle cell/β-thalassemia compound heterozygous form (HbS/β-thalassemia)
20 individuals with β-thalassemia (Hbβ/β-thalassemia)
20 individuals with β-thalassemia trait or carrier form (HbA/β- thalassemia)
20 healthy individual participants or normal participants (HbAA, participants without any known hemoglobin disorders, such as SCD, SCT or β-thalassemia)
The following number of participants will be included in Canada:
30 individuals with SCD (HbSS)
30 individuals with SCT (HbAS)
30 healthy individual participants or normal participants (HbAA, participants without any known hemoglobin disorders, such as SCD, SCT or β-thalassemia)
Participants older than 1 year of age at the time of drawing blood will be eligible. Signed and dated consent or assent forms will be required by the participants or their parents/guardians.
The exclusion criteria for the study:
Transfusion within the last 3 months
Pregnancy Participants who wish to withdraw from the study will also be excluded.