Analytical performance evaluation of the biofire SPOTFIRE respiratory and sore throat panel
Bibliographic record
Abstract
The new SPOTFIRE Respiratory/Sore Throat (R/ST) Panel, approved as a Point of Care Test (POCT), enables the detection of 15 respiratory pathogens from nasopharyngeal swabs (NPS) or throat swabs (TS) within 17 min. This study aimed to verify the performance of the assay. A total of 28 NPS specimens (23 positive for 1 or 2 targets; 5 negative) and 37 TS (20 culture positive for Streptococcus pyogenes or Streptococcus dysgalactiae; 17 culture negative) were analyzed. Results were compared to the BioFire respiratory panel 2.1 (RP2.1) for NPS and S. pyogenes and S. dysgalactiae culture for TS. Contrived TS were created to assess the detection of influenza A/B and SARS-CoV-2, as well as the limit of detection (LoD) of the Streptococcus targets. For NPS, the SPOTFIRE R menu demonstrated 100 % positive percent agreement (PPA) with reference results for all targets included, and 92-100 % negative percent agreement (NPA). The PPA and NPA for the detection of S. pyogenes and S. dysgalactiae from TS and culture were 100 %. All TS replicates at concentrations around the LoD for S. pyogenes and S. dysgalactiae yielded positive results. Data from this study suggest that influenza A/B, RSV and SARS-CoV-2 are effectively detected from TS by the SPOTFIRE. In conclusion, the SPOTFIRE R/ST Panel demonstrated high agreement with the reference methods for the detection of viral and bacterial targets from NPS and the detection of S. pyogenes and S. dysgalactiae from TS Additionally, prospective studies will be required to establish the clinical impact of ultra-rapid POCT.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".