Otoscopy-based diagnosis of paediatric acute otitis media: An evaluation of guideline adherence
Bibliographic record
Abstract
Abstract Objectives Over diagnosis of acute otitis media (AOM) may lead to unnecessary antibiotic prescriptions and overuse of health care resources. To date, no study has determined which otoscopy findings frontline physicians use to diagnose AOM, and whether lack of adherence to otoscopy guidelines contributes to over diagnosis. Methods In this single-centre multisite retrospective chart review, we determined adherence to Canadian Paediatric Society (CPS) AOM diagnosis guidelines based on documented otoscopy findings in patient charts. Results Of 192 cases of nonperforated AOM with a documented physical examination, only 124 (64.6%) had otoscopy findings of both middle ear effusion and inflammation, consistent with CPS criteria. Fifty-eight cases (30.2%) had documented middle ear inflammation without effusion. The most reported otoscopy findings were a red and bulging tympanic membrane (TM) in 81 (42.2%) cases. The presence (n = 104) or absence (n = 4) of bulging was only documented in 108 (56.2%) cases. The odds ratio for cases meeting diagnostic criteria was significantly higher for those seen by paediatricians compared with general providers (OR 2.82, 95% CI: [1.44–5.53], P < 0.01), for those assessed by residents or medical students compared with staff physicians (OR 2.04, 95% CI [1.05–3.98], P = 0.03), and those of older age (OR 1.14, 95% CI [1.00–1.29], P = 0.044). Conclusions This study highlights that AOM over diagnosis may be related to lack of adherence to diagnosis guidelines. Simplification of guidelines, such as more explicitly requiring a bulging TM, may improve diagnostic accuracy and reduce health care resource overuse for this common paediatric condition.
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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 | 0.008 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| 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".