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EN
Noise exposure during lifespan is one of the main causes of hearing loss. The highest risk of noise-induced hearing loss (NIHL) is related to exposures in the workplace, and affects about 7% of the population. Occupational NIHL is irreversible, thus its prevention must be considered a priority. Although current hearing conservation programs (HCPs) have proved to be very beneficial, the incidence of occupational NIHL is still high, reaching about 18% of overexposed workers. This paper reviews recent research on the effects of noise on hearing in pursuit of more effective methods for the prevention of occupational NIHL. The paper discusses the translational significance of noise-induced cochlear neuropathy, as recently shown in animals, and the concept of hidden hearing loss in relation to current NIHL damage risk criteria. The anticipated advantages of monitoring the incidents of the temporary threshold shift (TTS) in workers exposed to high levels of noise have been analyzed in regard to the preclinical diagnostics of NIHL, i.e., at the stage when hearing loss is still reversible. The challenges, such as introducing speech-in-noise audiometry and TTS computational predictive models into HCPs, have been discussed. Finally, the paper underscores the need to develop personalized medical guidelines for the prevention of NIHL and to account for several NIHL risk factors other than these included in the ISO 1999:2013 model. Implementing the steps mentioned above would presumably further reduce the incidence of occupational NIHL, as well as associated social costs.
EN
Objectives It has been shown that monitoring temporary threshold shift (TTS) after exposure to noise may have a predictive value for susceptibility of developing permanent noise-induced hearing loss. The aim of this study is to present the assumptions of the TTS predictive model after its verification in normal hearing subjects along with demonstrating the usage of this model for the purposes of public health policy. Material and Methods The existing computational predictive TTS models were adapted and validated in a group of 18 bartenders exposed to noise at the workplace. The performance of adapted TTS predictive model was assessed by receiver operating characteristic (ROC) analysis. The demonstration example of the usage of this model for estimating the risk of TTS in general unscreened population after exposure to loud music in discotheque bars or music clubs is provided. Results The adapted TTS predictive model shows a satisfactory agreement in distributions of actual and predicted TTS values and good correlations between these values in examined bartenders measured at 4 kHz, and as a mean at speech frequencies (0.5–4 kHz). An optimal cut-off level for recognizing the TTS events, ca. 75% of young people (aged ca. 35 years) may experience TTS >5 dB, while <10% may exhibit TTS of 15–18 dB. Conclusions The final TTS predictive model proposed in this study needs to be validated in larger groups of subjects exposed to noise. Actual prediction of TTS episodes in general populations may become a helpful tool in creating the hearing protection public health policy. Int J Occup Med Environ Health. 2023;36(1):125–38
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