Diagnosing streptococcal sore throat in adults: randomized controlled trial of in-office aids.
Bibliographic record
Abstract
OBJECTIVE: To determine whether use of clinical decision rules or rapid streptococcal antigen detection tests (alone or in combination) can lower the number of unnecessary prescriptions for antibiotics for adults with acute sore throats. DESIGN: Four-arm randomized controlled trial. SETTING: Family practice offices in eastern Newfoundland. PARTICIPANTS: Forty urban and suburban family practitioners. INTERVENTIONS: Participants were randomly assigned to one of 4 arms (usual practice, decision rules only, rapid antigen test only, decision rules and antigen test combined), and each recruited successive adult patients presenting with acute sore throat as their main symptom. Following usual care or use of decision rules or rapid antigen tests or both (where applicable), physicians were to record what they prescribed for each patient. MAIN OUTCOME MEASURES: Prescribing rates and types of antibiotics prescribed. RESULTS: The prescribing rate using decision rules (55%) did not differ significantly from the rate using usual clinical practice (58%). Physicians using rapid antigen tests, both alone and with decision rules, had significantly lower prescribing rates (27% and 38%, respectively, both P < .001). CONCLUSION: Evidence-based clinical decision rules alone do not change family doctors' prescribing behaviour. Use of rapid antigen tests might allow physicians to persuade patients that negative results (and hence, viral infection) mean antibiotic therapy is not required.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| 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 | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".