Operator Influence on Blinded Diagnostic Accuracy of Point-of-Care Antigen Testing for Group A Streptococcal Pharyngitis
Bibliographic record
Abstract
Background. Acute pharyngitis caused by Group A Streptococcus (GAS) is a common presentation to pediatric emergency departments (ED). Diagnosis with conventional throat culture requires 18-24 hours, which prevents point-of-care treatment decisions. Rapid antigen detection tests (RADT) are faster, but previous reports demonstrate significant operator influence on performance. Objective. To measure operator influence on the diagnostic accuracy of a RADT when performed by pediatric ED nurses and clinical microbiology laboratory technologists, using conventional culture as the reference standard. Methods. Children presenting to a pediatric ED with suspected acute pharyngitis were recruited. Three pharyngeal swabs were collected at once. One swab was used to perform the RADT in the ED, and two were sent to the clinical microbiology laboratory for RADT and conventional culture testing. Results. The RADT when performed by technologists compared to nurses had a 5.1% increased sensitivity (81.4% versus 76.3%) (p = 0.791) (95% CI for difference between technologists and nurses = -11% to +21%) but similar specificity (97.7% versus 96.6%). Conclusion. The performance of the RADT was similar between technologists and ED nurses, although adequate power was not achieved. RADT may be employed in the ED without clinically significant loss of sensitivity.
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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 | 0.089 | 0.280 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 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".