Continuous quality monitoring in the field: an evaluation of the performance of the Fio Deki Reader™ for rapid HIV testing in South Africa
Bibliographic record
Abstract
BACKGROUND: Rapid diagnostic tests (RDTs) are a cornerstone of HIV diagnosis and rely on good quality processing and interpretation, particularly in the era of test and treat. The Deki Reader (Fio Corporation®, Toronto, Ontario, Canada) is a portable device designed specifically for analysing RDTs and was selected for evaluation in South Africa in the context of HIV RDT analysis. METHODS: This study consisted of a laboratory evaluation and two-part field evaluation of the Deki Reader v100, covering two RDT testing algorithms, and an evaluation of the continuous quality monitoring through the Fionet™ web portal. Based on user feedback from the field evaluation, the device underwent hardware and software redesign, and the Deki Reader v200 was evaluated in the laboratory. Ethics approval for this evaluation was obtained from the University of the Witwatersrand Human Research Ethics Committee: M150160. RESULTS: The intra- and inter-device laboratory precision of the Deki Reader v100 were 98.3 and 99.2% respectively, and 99.3 and 100% for the Deki Reader v200. The laboratory concordances compared to standard-of-care reporting were 99.5 and 98.0% for the two respective models, while sensitivity and specificity were 99.5 and 99.4% for the Deki Reader V100 and 100 and 93.1% for the Deki Reader V200 respectively. Screening and confirmatory concordances in the field were 99.3 and 96.5% under algorithm 1 and 99.7 and 100% under algorithm 2. Sensitivity and specificity for the field evaluation were 99.8 and 97.7%. Overall robustness of the device was acceptable and continuous quality monitoring through Fionet™ was feasible. CONCLUSIONS: The Deki Reader provides an option for improved and reliable quality assessment for rapid diagnosis of HIV using RDTs to enhance the quality of healthcare at the point-of-care. However, the introduction of new RDTs and modification of current algorithms necessitates ongoing and agile RDT reader adjustments, which will require cost modelling to ensure sustainability of devices implemented into national HIV 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 | 0.021 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".