From lab to field: Evaluation of a rapid, low-cost, point-of-care ferritin assay for detection of iron deficiency
Notice bibliographique
Résumé
Abstract Background: Iron deficiency (ID) is among the most common global hematologic disorders and a leading contributor to the global disease burden. Over 1/3 of individuals worldwide have iron deficiency anemia (IDA), with children and pregnant women living in low- and middle-income countries (LMICs) disproportionately impacted. The most sensitive and specific test to diagnose ID is measurement of serum ferritin, with values reflective of body iron stores. However, hemoglobin concentration is more commonly used as the primary screening test in both high- and low-resource settings due to its low cost, widespread availability, and ease of fingerstick-based point-of-care (POC) testing. While IDA is the most common cause, anemia in LMICs is often multifactorial, with overlapping causes including malaria, sickle cell disease, infections, and thalassemias. The Gazelle™ is a low-cost (~$500), battery-operated POC platform that has been validated across the world for diagnosing hemoglobinopathies using miniaturized electrophoresis. In this study, we evaluated the accuracy of the newly developed tool for this same Gazelle device to quantify serum ferritin. Methods: This study used de-identified, leftover clinical blood samples for which ferritin levels were previously measured using the Abbott Alinity system. Samples were collected under an IRB-approved protocol, stored cold, and tested on the Gazelle™ Ferritin fluorescent lateral flow immunoassay (FIA) within 48 hours. The Gazelle FIA uses antibody sandwich format with fluorescent detection. Ferritin in the sample binds to fluorescently labeled anti-ferritin antibodies on the conjugate pad, forming immune complexes that migrate via capillary action. These complexes are captured at the test line by immobilized anti-ferritin antibodies, while a control line confirms test validity. Fluorescence intensity at the test line is proportional to ferritin concentration and is quantitatively analyzed by the Gazelle Reader using pre-programmed algorithms. Results are available within 15 minutes at the POC. Results: To date, a total of 54 patient samples were collected and run in triplicate using whole blood on the Gazelle machine ferritin assay. Seven samples with ferritin values >500 ng/mL were excluded from the primary analysis to avoid data skewing. For the 47 remaining samples, the median ferritin concentration was 54 ng/mL (IQR 20-131, range 3-513). Notably, 22 samples had ferritin ≤ 50 ng/mL and 15 had ferritin ≤ 25 ng/mL, below common thresholds to diagnose ID. The assay demonstrated excellent internal reproducibility (alpha = 0.96) and strong correlation with the gold standard Alinity (r = 0.95, R² = 0.89). The average coefficient of variation was 10.5%. Among 45 runs for samples with ferritin values ≤25 ng/mL, a common threshold to define iron deficiency, Gazelle accurately reported values for these samples as ≤30 ng/mL for 93% of runs. For samples with ferritin >500 ng/mL, the assay identified 5/7 as >500 ng/mL, with the remaining 2 correctly flagged as high but below the assay's upper limit of detection. Discussion: These data demonstrate the initial feasibility and accuracy of the Gazelle device to quantify serum ferritin with values that approximate those obtained by the gold standard. This study provides important data to support the continued evaluation and optimization of this device for future use in LMICs to diagnose iron deficiency at the point of care. In combination with POC hemoglobin testing and testing with the Gazelle for both sickle cell disease and ferritin could result in a low-cost and rapid (<15 minutes) comprehensive step-wise screening strategy for anemia that could have tremendous implications in addressing the global burden of anemia and iron deficiency. There is a potential role for this tool in high resource settings as a screening tool by general pediatricians or obstetricians, who are still using hemoglobin as the screening tool for iron deficiency. Future testing will evaluate the accuracy of ferritin values as a screening tool for iron deficiency given that ferritin is an acute phase reactant and may be artificially elevated in the setting of other acute and chronic illnesses that are common in sub-Saharan Africa and other LMICs. In conclusion, these findings support further deployment and clinical validation of the Gazelle platform to address global gaps in anemia diagnosis and iron deficiency management.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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