Bulging Tympanic Membrane — Acute Otitis Media
Test Characteristics
| Metric | Value |
|---|---|
| False-negative rate | 47% (sensitivity 53%) |
| False-positive rate | 3% (specificity 97%) |
| Bayes factor (positive test) | 20× |
| Bayes factor (negative test) | 1/2× |
| Base rate | 50% of children with ear pain and fever |
Interpreting Results
| Scenario | Prior | + Result | − Result |
|---|---|---|---|
| Child with febrile URI, no ear-specific symptoms | 10% | 20 × 10% ≥ 100%10%× 20100% | 1/2 × 10% = 5%10%÷ 25% |
| Child with ear pain and fever | 50% | 20 × 50% ≥ 100%50%× 20100% | 1/2 × 50% = 25%50%÷ 225% |
20 × 10% ≥ 100%10%× 20100%: exact posterior is 69%. 20 × 50% ≥ 100%50%× 20100%: exact posterior is 95%. Negative-test exact posterior at 50% prior is 33% (simple approximation gives 25%). Bulging is highly specific for middle ear effusion in acutely symptomatic children — when present, it strongly indicates AOM. The negative Bayes factor is weak (1/2×) because nearly half of true AOM cases lack frank bulging on examination; cloudiness and distinctly impaired mobility were each more sensitive than bulging in the Karma data. Distinguish AOM (bulging, opaque, often hyperaemic) from OME (retracted or neutral, air-fluid level, no bulging). Crying alone can redden a TM and produce a false impression of inflammation — judge color in a calm child.
- + result: at a coin-flip prior (child with ear pain and fever, 50%), risk pushes to 95% — strong confirmation
- − result: drops to 25% (exact 33%) — bulging misses about half of AOM, so its absence doesn't rule it out
Sources:
- Karma PH, Penttilä MA, Sipilä MM, Kataja MJ. Otoscopic diagnosis of middle ear effusion in acute and non-acute otitis media. I. The value of different otoscopic findings. Int J Pediatr Otorhinolaryngol. 1989;17(1):37–49. Pooled sens 53% and spec 97% computed from Tables II and V (acute visits, bulging) vs myringotomy across 5462 visits.
- Rothman R, Owens T, Simel DL. Does this child have acute otitis media? JAMA. 2003;290(12):1633–1640. Re-analysis of Karma data with verification-bias adjustment.