Performance of the Cue COVID-19 Molecular Test for Point of Care: Insights from a multi-site clinic service model
Bibliographic record
Abstract
Abstract The COVID-19 pandemic highlighted the critical need for rapid and accurate molecular diagnostic testing. The Cue COVID-19 Point of Care Test (Cue POCT) is a nucleic acid amplification test (NAAT), authorized by Health Canada and FDA as a POCT for SARS-CoV-2 detection. Cue POCT was deployed at a network of clinics in Ontario, Canada with n=13,848 patrons tested between July 17, 2021 to January 31, 2022. The clinical performance and operational experience with Cue POCT was examined for this testing population composed mostly of asymptomatic individuals (93.7%). A head-to-head prospective clinical verification was performed between July 17 to October 4 for all POCT service clients (n= 3037) with paired COVID-19 testing by Cue and RT-PCR. Prospective verification demonstrated a clinical sensitivity of 100% and clinical specificity of 99.4% for Cue COVID-19 POCT. The lack of false negatives and low false positive rate (0.64%), underscores the high accuracy (99.4%) of Cue POCT to provide rapid PCR quality results. Low error rates (cancellation rate of 0% and invalid rate of 0.63%) with the current software version were additionally noted. Together these findings highlight the value of accurate molecular COVID-19 POCT in a distributed service delivery model to rapidly detect cases in the community with the potential to curb transmission in high exposure settings (i.e. in-flight, congregate workplace and social events). The insights gleaned from this operational implementation are readily transferable to future POCT diagnostic services.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".