During March of this year (2016), leading researchers based out of Boston published a landmark paper presenting a method for identifying hidden hearing loss among patient populations. Hidden hearing loss is gaining more attention among audiologists when a patient arrives to their clinic with complaints of not understanding their loved ones, particularly when partners speak softly or while listening in background noise. With complaints that directly overlap with complaints by those who are diagnosed with overt hearing losses, clinicians use their standard test battery and find no indication of hearing loss, leaving patients to wonder why they struggle with hearing in light of these normal test results.
What does the standard audiometric battery tell an audiologist?
If normal results are obtained from a standard test battery, patients are often counseled regarding their normal hearing status. They may be counseled regarding use of good communication strategies such as reducing background noise and gaining facial cues from their communication partner, and encouraging focused attention with a quick mention of the communication partner’s name at the beginning of a sentence. (Stay tuned for a future post “Communication Strategies For Everyone” for more helpful tips!) Although these strategies are immensely helpful, the patient is left to wonder why they struggle with hearing given normal test results. Evaluation of hidden hearing loss allows patients to understand these struggles.
Does your patient have hidden hearing loss?
Although not clinically validated at this time, the authors presented methods to diagnose hidden hearing loss. According to this study, in order to determine presence of hidden hearing loss, the audiologist would need to perform a standard audiometric battery to evaluate whether any overt hearing loss is present. If the patient has audiometric thresholds that fall within the normal hearing range, the audiologist will then complete three additional tests.
First, otoacoustic emissions, to evaluate health of outer hair cells. Otoacoustic emissions should be robust across all frequencies in both cases of normal hearing and hidden hearing loss. Second, the audiologist will evaluate auditory brainstem response (ABR) in quiet, to determine if the central auditory nervous system is intact through the level of the lateral lemniscus and inferior colliculus. The usual clinical evaluation of Wave V of the ABR in quiet should be normal in latency, given the normal hearing thresholds and other normal findings. Third, the audiologist would introduce notched noise to eliminate off-frequency listening and to assure high spontaneous rate fibers are prevented from contributing to the response. Finally, comparison of the measured Wave V ABR latencies in quiet and in noise will reveal potential hidden hearing loss: difference between the two latencies indicates possibility for cochlear synaptopathy while similar latencies indicate largely normal hearing.
But what is hidden hearing loss, exactly?
Although mechanisms underlying the processes of hidden hearing loss are still controversial, those with noise exposure history or undergoing aging processes tend to be more likely to have hidden hearing loss. These etiologies lead to decreased connections between the sensory cell (hair cell) and the connecting auditory nerve fiber that sends information to the brain by disruption of the ribbon synapse, a structure that is required for proper communication between these two structures.
The authors of the study cited here suggest an alternate approach to hidden hearing loss, however. They suggest that there are differing contributions to the incoming auditory signal by two populations of auditory nerve fibers: fibers with a low-spontaneous rate and fibers with a high-spontaneous rate. Nerve fibers with a high spontaneous rate tend to be stimulated more easily while nerve fibers with a low spontaneous rate tend to require more stimulation to propagate an auditory signal. In background noise, low spontaneous rate fibers would only send on reliable information (the intended signal) whereas high spontaneous rate fibers would send more noise along with the reliable information. In other words, if one were to use only high spontaneous fibers to send along an auditory signal, then it would likely be filled with accompanying noise.
Using their elegant research design, the researchers occupied the high spontaneous nerve fibers with noise to allow for direct measurement of the contribution of auditory nerve fibers with a low spontaneous rate. Applying knowledge of the underlying auditory nerve fibers, the researchers intend to reveal the contribution of the more reliable auditory signal, the low spontaneous rate fibers through measurement of ABR in quiet and in noise.
If there is a significant difference between these two conditions (quiet and noise), then it’s likely the low spontaneous rate fibers are contributing less information than is necessary for a signal to be perceived with accuracy and precision. Without contribution from low spontaneous rate auditory nerve fibers, the patient will rely on high spontaneous rate auditory nerve fibers to relay information, reducing their ability to eliminate background noise. The results for a patient with hidden hearing loss would demonstrate a robust OAE response and normal ABR results in quiet, but increased latency for ABR Wave V in noise.
Wow! This seems like an easy way to determine hidden hearing loss. Can I use this on my next patient?
Hold on! While this research shows great promise, it is not yet validated due to its extremely recent publication. Stay tuned for additional studies and tools to introduce this to your clinic with efficiency and accuracy.
Check out the research article in its entirety to evaluate their methods yourself.
Mehraei, G., Hickox, A. E., Bharadwaj, H. M., Goldberg, H., Verhulst, S., Liberman, M. C. and Shinn-Cunningham, B. G. (2016) ‘Auditory Brainstem Response Latency in Noise as a Marker of Cochlear Synaptopathy.’, The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, 36(13), pp. 3755–64. doi: 10.1523/JNEUROSCI.4460-15.2016.