July 17, 2007 Features

Otoacoustic Emissions: Reducing and Preventing Noise-Induced Hearing Loss

Hearing conservationists need effective schemes to determine whether their hearing-conservation programs (HCPs) are successful, determine whether new interventions are helpful, and establish which personnel in their care have an increased risk for noise-induced hearing loss (NIHL). Currently, these goals cannot be achieved because the measure of success is also the measure of failure—by the time a hearing loss is recorded, personnel have already been damaged and the HCP has failed. Tests are needed that enable audiologists to catch hearing loss before it becomes clinically significant and—better still—stop a hearing loss from ever occurring. An otoacoustic emission (OAE) test may be the solution.

OAEs are sounds produced by the inner ear that are measured in the ear canal with a special microphone. There are various types of OAEs: the most common are distortion-product OAEs (DPOAEs), which are evoked with two tones, and transient-evoked OAEs (TEOAEs), which are evoked with clicks or chirps. OAEs indicate the activity of outer hair cells in the cochlea, which are very sensitive to noise over-exposure. Normal-hearing ears produce OAEs, while noise-damaged ears produce smaller OAEs—or none at all—because of damage to the outer hair cells and surrounding cochlear structures.

Studies have shown that on average, OAEs may decrease after noise exposure before hearing thresholds increase (see summary of studies in Lapsley Miller & Marshall, 2007). In addition, groups of normal-hearing people regularly exposed to hazardous noise levels tend to have lower OAEs than similar groups of normal-hearing people without such exposure. In individual normal-hearing ears, low-level OAEs may predict susceptibility to future NIHL.

OAEs are widely and successfully used for infant hearing screening, in which a single measurement is made and a pass/refer criterion applied. Infants with normal hearing have large OAEs that are easy to measure. In adults, OAEs provide an objective, sensitive, physiological measurement, but interpreting the results is not as clear-cut. Unlike infants with normal hearing, many adults with normal hearing have low-level OAEs. In adult HCPs, the ability to detect low-level OAEs and small OAE changes over time is required. Achieving valid and reliable measurements of low-level OAEs pushes the limits of standard clinical OAE equipment, which invariably has been designed with infant screening in mind. Despite these challenges, OAEs can be used in HCPs. The following questions and answers explain the potential benefit and use of OAEs in HCPs.

Can OAEs replace audiograms?

No. Although OAEs can reliably distinguish ears with normal hearing from ears with various degrees of hearing loss, they are not yet able to directly provide a measure of hearing level in an individual ear with sufficient accuracy (e.g., Gorga, Neely, Dorn, & Hoover, 2003). Audiologists should not throw out their audiometers just yet!

Can OAEs be used to evaluate HCP effectiveness?

In principle, yes. In many HCPs, the permanent hearing threshold shift (PTS) rate is used to gauge effectiveness. However, because NIHL is slow to develop, it can take too long to find out that there is a problem with an HCP. This challenge can be further exacerbated by transient workers who are enrolled for an insufficient time in the same program to detect NIHL. The HCP effectiveness should be evaluated before PTSs develop in individual ears. The biggest benefit that OAEs provide over audiograms is that changes in OAEs may be detected long before there are changes in hearing. This allows problems in an HCP to be identified before detectable changes in hearing occur, which may prevent hearing loss.

OAE data would be collected similarly to audiometric monitoring, with a baseline measurement, regular testing for significant OAE shifts, and follow-up noise-free testing to confirm permanent otoacoustic emission shifts (PES). OAE data could then be used in a number of ways. 

Permanent OAE Shifts (PES) Rate

The PES rate has not yet been used to evaluate HCPs, but in principle it could be done. To do this, the PES should be established statistically, for the OAE type, population, and environment in question (e.g., as in Lapsley Miller, Marshall, Heller, & Hughes, 2006). A PES criterion must be greater than the test-retest variability (based on the standard error of measurement) of the OAE measurement. This can be established from the test-retest variability in a demographically matched control group with no noise exposure. Test-retest variability also can be estimated by using the noise-exposed group as its own control by testing the OAEs twice with no intervening noise exposure.

If no control group is feasible, then HCP effectiveness can still be assessed by applying a PES criterion obtained elsewhere, such as from research by others using the same OAE type. If the PES rate is too high, or higher than previous measurements, then there is cause for concern. The downside to this approach is that without a control group, it is impossible to tell whether a high PES rate is due to poor test-retest reliability or because people have acquired hearing loss. Either way, the HCP is broken, requiring further investigation.

Another compromise is to have matched comparison groups in which the degree of noise exposure varies, so comparisons can be made, for example, among low-, moderate-, and high-exposure groups. Although this method may not capture all noise-induced change, it could at least show there has been some change, which would be expected to be worse in the more noise-exposed group.

Longitudinal monitoring over a number of years is more difficult because OAEs tend to decrease in amplitude with aging. Therefore, the longer the HCP is monitored for effectiveness, the more the PES rate may increase due to the gradual decrease of OAE amplitudes with aging. For long-term evaluations of HCPs (i.e., greater than one year), the gap between test and retest for the control group should be around the same duration as for the noise-exposed group to factor in age-related PES rate changes.

Group-Average OAEs

An alternative to PES rates is to consider changes in group-average OAE levels over time. These data can be evaluated using repeated-measures statistical techniques, in which the same subjects are used for each test. Group OAE levels appear to be more sensitive to noise-induced changes than hearing tests, but this sensitivity depends on many factors, including the OAE test used, the hearing test performed, and the reliability associated with the administration of the tests. In our field research, group-average OAEs have shown greater sensitivity to what we believe are noise-induced changes (Lapsley Miller, Marshall, & Heller, 2004; Lapsley Miller et al., 2006). As with PES rates, when using group-average OAEs as a measure of HCP effectiveness it is important to consider factors such as age-related OAE changes, control groups, and baseline hearing levels. However, potentially fewer participants are needed to see noise-induced changes in group-average OAEs compared with PES or PTS rates.

A further use for OAEs in HCPs is evaluating the effectiveness of an intervention, such as an educational campaign, different hearing protection, or reducing the noise generated by machinery. Ideally, there would be an "intervention" group and a "no-intervention" group. OAEs would be monitored for both groups; if the HCP intervention was successful, the no intervention group would show a significantly higher PES rate and a significantly larger change in group-average OAE level than the intervention group. OAEs would then be monitored; if the HCP intervention was successful, there would be a significantly higher PES rate and a significantly larger change in group-average OAE level in the no-intervention group as compared with the intervention group. However, the two groups must be comparable. If there is no way to split the participants into intervention and no-intervention groups, an alternative approach is to see if the intervention decreases the historical PES rate (if the historical rate is known and somewhat stable).

For all of these applications, high test-retest variability will mask noise-induced group-average changes in hearing level or OAE amplitude and will also increase the PTS and PES criteria, meaning only large OAE or hearing changes could be detected as different from random variation. This could make an HCP look better than it actually is by producing low PTS/PES rates and small or no group-average change. Test-retest variability should be demonstrable, stated explicitly, and comparable to other published studies.

Another factor is that the low-level stimuli preferred for adult testing tend to evoke low-level OAEs, which are more likely to be affected by high noise floors, rendering them unusable. However, OAEs measured with low-level stimuli are more sensitive to changes subsequent to noise exposure. Thus, there is a trade-off between the optimal stimulus level for detecting change and the optimal stimulus level for minimizing data loss (Lapsley Miller, Marshall, & Heller, 2004).

In general, OAEs are useful only in assessing HCP effectiveness in a group of people with normal hearing. People with hearing loss have fewer or even no OAEs, making it impossible to measure OAE changes. We believe that OAEs offer some advantages over hearing tests in evaluating HCP effectiveness, but it is wise to measure both OAEs and hearing to obtain a more complete picture. Careful testing and high quality control are a prerequisite for useful data.

Can OAEs indicate who is more susceptible to NIHL?

A person is considered susceptible to NIHL if an innate or acquired factor predisposes that person to acquire NIHL at a rate higher than a comparable population. Examples of innate factors include genetic mutations or polymorphisms associated with hearing loss, normal anatomical and physiological variations such as the transfer function of the outer and middle ear, and OAE efferent strength and the middle-ear acoustic reflex. The extent to which these factors predict susceptibility to NIHL in humans has not yet been determined. To date, no innate factor such as race or eye color has shown itself to be a useful predictor of NIHL susceptibility in humans. Examples of acquired factors include previous noise exposure, chemical exposure, and disease.

The risks associated with innate factors are probably stable, and need only be measured once. The risks associated with acquired factors can increase or decrease over time, so long-term monitoring may be required. For instance, personnel in a noisy environment continue to accumulate exposure and damage to inner-ear structures, which increases their risk for NIHL over time. If they also have a disease, smoke, or are exposed to chemicals, their risk for NIHL may be higher again.

OAEs present a potentially powerful addition to HCPs. Although in principle, it appears that OAEs have much to offer, the reality is that the interpretation and use of OAEs in HCPs is still in its infancy. Large-scale, longitudinal, epidemiological studies are needed to establish clinical utility. That is not to say there is no place for OAEs in HCPs now, but their utility has not yet been fully established. Nevertheless, by using OAEs in HCPs now, we can push the science and technology further and faster.  

Lynne Marshall, is a senior research scientist at the Naval Submarine Medical Research Laboratory at the Naval Submarine Base New London in Groton, Conn., and was an assistant professor, director of audiology, and post-doctoral fellow at the University of Nebraska at Omaha and Boys Town National Research Hospital. Contact her at lynne.marshall@med.navy.mil.

Judi A. Lapsley Miller, is a hearing research consultant in Wellington, New Zealand, and was a research scientist at the Naval Submarine Medical Research Laboratory. Contact her at judi@psychophysics.org.  

cite as: Marshall, L.  & Lapsley Miller, J. A. (2007, July 17). Otoacoustic Emissions: Reducing and Preventing Noise-Induced Hearing Loss. The ASHA Leader.

Acknowledgements

Thanks to CAPT David Southerland and LCDR Heike Rentmeister-Bryant for their comments. The research at NSMRL that was described in this paper was supported by grants from the Office of Naval Research and the U.S. Army Medical Research and Materiel Command. The views expressed in this article are those of the authors and do not reflect the official policy or position of the Department of the Navy, the Department of Defense, or the United States Government.



Study: Sailors' Hearing Loss

Recently, we showed that individual differences in OAE levels may be a useful predictor of NIHL (Lapsley Miller et al., 2006), but it is unknown whether these findings reflect innate or acquired risk factors. Regardless, the ability to predict those personnel more at risk for NIHL is a significant step towards reducing its incidence.

In this study, OAEs and hearing levels were measured in a group of 338 sailors stationed on an aircraft carrier. Measurements were made before and after a six-month operational deployment, during which there were approximately 6,000 aircraft launches and recoveries. The sailors in the study all worked in hazardous noise environments. Fifteen sailors (18 ears) had confirmed PTS after the deployment. Despite the fact that all the sailors in the study had normal hearing, many had very low-level or no OAEs.

We were interested to see if having low-level OAEs at pre-deployment testing was predictive of PTS at post-deployment testing. To do this, we used Bayesian statistics to calculate the PTS rate (which was approximately 3%) and the positive predictive value, which in this case is the conditional probability of a PTS given a positive OAE test result, defined to be an OAE level below a cutoff value (Zhou, Obuchowski, & McClish, 2002). The positive predictive value is very useful because it allows clinicians to assign an actual probability of PTS based on a test result.

To calculate the positive predictive value, the sailors were split into two groupsСthose who acquired a PTS and those who did not. A cutoff was chosen based on OAE amplitude. For the two groups, we counted how many sailors also had a pre-deployment OAE level less than the cutoff. We then calculated the positive predictive value for that cutoff. By systematically varying the cutoff over the range of OAE amplitude, the entire positive predictive value function can be plotted. The results are shown in  Figure 1  [PDF] for the best OAE predictor, which was the TEOAE amplitude in the 4 kHz half-octave band. The straight dotted line indicates the PTS rate. The solid line shows the calculated positive predictive value. For our population, an OAE test result less than 0 dB SPL indicated an increased risk for PTS. This risk increased markedly as TEOAE amplitude went below -5 dB SPL.

This example provides only a proof of concept; it does not provide risk levels for use in the clinic. This is because risk depends on the specific noise exposure, length of exposure, population demographics, and other factors. Our results apply only to the population of male sailors with normal hearing on aircraft carriers who are deployed for six months. Furthermore, these results were based on 524 ears with no PTS and 17 ears with PTS (eight of whom had noise floor substitutions made for missing TEOAEs).

These are not enough cases on which to build norms; we encourage others to do similar studies with other populations and noise exposures. 



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References

Gorga, M. P., Neely, S. T., Dorn, P. A., & Hoover, B. M. (2003). Further efforts to predict pure-tone thresholds from distortion product otoacoustic emission input/output functions. Journal of the Acoustical Society of America, 113(6), 3275-3284.

Lapsley Miller, J. A., & Marshall, L. (2007). Otoacoustic emissions as a preclinical measure of NIHL and susceptibility to NIHL. In M. S. Robinette & T. J. Glattke (Eds.), Otoacoustic Emissions: Clinical Applications (Third ed.). NY: Thieme.

Lapsley Miller, J. A., Marshall, L., & Heller, L. M. (2004). A longitudinal study of changes in evoked otoacoustic emissions and pure-tone thresholds as measured in a hearing conservation program. International Journal of Audiology, 43(6), 307-322.

Lapsley Miller, J. A., Marshall, L., Heller, L. M., & Hughes, L. M. (2006). Low-level otoacoustic emissions may predict susceptibility to noise-induced hearing loss. Journal of the Acoustical Society of America, 120(1), 280-296.

Zhou, X.-H., Obuchowski, N. A., & McClish, D. K. (2002). Statistical Methods in Diagnostic Medicine. NY: Wiley-Interscience.



  

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