Performance of an Automated Detection Algorithm to Assess Objective Pulsatile Tinnitus.
Sander W J Ubbink, J Marc C van Dijk, Rutger Hofman and 1 others
PMID 36395514WHAT IT FOUND
An automated algorithm detected pulse-synchronous tinnitus sounds in ear recordings with good accuracy compared to expert listeners.
It offers an objective measure to help distinguish cases needing further imaging, though it requires validation in broader patient groups before clinical use.
Key findings
01The algorithm's performance in detecting pulsatile sounds, compared to the majority judgement of three blinded observers, resulted in an area under the curve (AUC) of 0.83.
02At a specific cut-off value of 0.7 for the pulsatile-tinnitus-coherence-index, the algorithm achieved 93% sensitivity and 69% specificity.
03There was substantial agreement among the three blinded observers when judging the presence of pulsatile sounds in the recordings, with an overall agreement of 83.33%.
STILL TO COME
How it was doneWhat they foundWhat it means for SLPs
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What it does not show
The study included a small number of patients (36) who were already selected for invasive testing, so the results may not apply to the general population with pulsatile tinnitus. The algorithm's performance was measured against human observers, not against a gold-standard diagnosis of the underlying vascular cause. One case with a pulsatile sound judged by observers had a very low algorithm score, indicating the algorithm may miss sounds that are not continuously present above background noise.
Declared interests
The authors declared no conflicts of interest or financial disclosures.
The easy way to misread this
Do not assume this algorithm identifies the specific cause of the tinnitus. It only detects the presence of a pulse-synchronous sound; it does not diagnose the underlying vascular pathology or replace the need for appropriate imaging when indicated.