International journal of occupational medicine and environmental health · 2023
The adaptation of noise-induced temporary hearing threshold shift predictive models for modelling the public health policy.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Dudarewicz Adam, Pawlaczyk-Łuszczyńska Małgorzata, Zaborowski Kamil, Pontoppidan Niels Henrik, Wolniakowska Anna, Bramsløw Lars, Christensen Jeppe Høy, Katrakazas Panagiotis, Brdaric Dario, Samardžić Senka, Śliwińska-Kowalska Mariola
Аннотация
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.
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.