Newborn and infant hearing screening for early detection of hearing loss in Nairobi, Kenya.

Background: Early detection of hearing loss and subsequent intervention leads to better speech, language and educational outcomes giving way to improved social economic prospects in adult life. This can be achieved through establishing newborn and infant hearing screening programs. Objective: To determine the prevalence of hearing loss in newborns and infants in Nairobi, Kenya. Methods: A cross-sectional pilot study was conducted at the National hospital and at a sub county hospital immunization clinic. A total of 9,963 babies aged 0-3 years, were enrolled in the hearing screening program through convenient sampling over a period of nine months. A case history was administered followed by Distortion Product Oto-acoustic emissions (DPOAEs) and automated auditory brainstem response (AABR) hearing screening. Results: The screening coverage rate was 98.6% (9963/10,104). The referral rate for the initial screen was 3.6% (356/ 9,963), the return rate for follow-up rescreening was 72% (258 babies out of 356) with a lost to follow-up rate of 28% (98/356). The referral rate of the second screen was 10% (26/258). All the 26 babies referred from the second screen returned for diagnostic hearing evaluation and were confirmed with hearing loss, yielding a prevalence of 3/1000. Conclusions: Establishing universal newborn and infant hearing screening programs is essential for early detection and intervention for hearing loss. Data management and efficient follow-up systems are an integral part of achieving diagnostic confirmation of hearing loss and early intervention.

Newborn Hearing Screening - An Implementation Analysis.

BACKGROUND/AIM: Hearing impairment affects a small but significant percentage of newborns (0.1-0.4%). Newborn hearing screening (NHS) is recommended for early detection and treatment. The implementation of NHS can vary among countries. In this study, we present the methodology, organization, and technical requirements of NHS. This study analyzed results from a tertiary hospital, identified issues, and proposed solutions. PATIENTS AND METHODS: In the studied region, there are five maternity hospitals and a perinatal intensive care center and in 2020, there were 5,864 live births. Screening is performed at three levels. The first screening is conducted on the 2nd-3rd day of a newborn's life in a maternity hospital, the first rescreening on the 3rd-6th week at a relevant ENT department, and the second rescreening on the 3rd-6th month of life at the regional screening center where the central database is also held. RESULTS: In the studied region, 5,793 out of 5,864 (98.79%) newborns received NHS in 2020. Of these, 120 (2.07%) were tested positive on their first screening. Ninety-four patients (78.3%) of those attended the ENT department for a first rescreening. Thirty-four patients (0.59% of total) were tested positive again and referred to the regional screening center. Out of the 27 patients who attended the second rescreening, four (0.07% of the total) were ultimately diagnosed with hearing impairment. CONCLUSION: Our study found that newborn hearing screening (NHS) in our region achieved a high compliance rate of 98.8% for initial screenings in 2020. However, challenges remain in the rescreening process due to data management issues, inter-regional cooperation, and public awareness. The recent implementation of mandatory screenings, updated guidelines, and a centralized database is expected to enhance the effectiveness of NHS. Further research is needed to evaluate these improvements.

Prevalence of self-reported hearing difficulty on the Revised Hearing Handicap Inventory and associated factors.

BACKGROUND: Hearing loss is common in aging adults and is an important public health concern. Self-reported measures of hearing difficulty are often used in research and clinical practice, as they capture the functional impacts of hearing loss on individuals. However, little research has evaluated the prevalence or factors associated with self-reported hearing difficulty. Therefore, the purpose of this study was to determine the prevalence of self-reported hearing difficulty, measured by the Revised Hearing Handicap Inventory (RHHI), and associated factors. METHODS: This study was conducted in a community-based cohort study based in Charleston, SC. We determined the prevalence of RHHI self-reported hearing difficulty (score ≥ 6 points) and evaluated associated factors with logistic regression models. Results are presented as odds ratios (OR) with corresponding 95% confidence intervals (95% CI). RESULTS: There were 1558 participants included in this study (mean age 63.7 [SD 14.4], 56.9% female, 20.0% Minority race). The prevalence of RHHI self-reported hearing difficulty was 48.8%. In a multivariable model, older age (per + 1 year; OR 0.97 [95% CI 0.96, 0.98]), Minority (vs. White) race (OR 0.68 [95% CI 0.49, 0.94]), and speech-in-noise scores that are better than predicted (OR 0.99 [95% CI 0.98, 1.00]) were associated with lower odds of RHHI self-reported hearing difficulty. Furthermore, female (vs. male) sex (OR 1.39 [95% CI 1.03, 1.86]), higher PTA in the worse ear (per + 1 dB; OR 1.10 [95% CI 1.09, 1.12]), more comorbid conditions (vs. 0; 1 condition: OR 1.50 [95% CI 1.07, 2.11]; 2 conditions: OR 1.96 [95% CI 1.32, 2.93]; 3 + conditions: OR 3.00 [95% CI 1.60, 5.62]), noise exposure (OR 1.54 [95% CI 1.16, 2.03]), bothersome tinnitus (OR 2.16 [95% CI 1.59, 2.93]), and more depressive symptoms (OR 1.04 [95% CI 1.01, 1.07]) were associated with higher odds of RHHI self-reported hearing difficulty. CONCLUSIONS: The prevalence of RHHI self-reported hearing difficulty is high, and associated factors included demographics, audiometric hearing and other hearing-related factors, and physical and mental health. The RHHI likely captures functional impacts of hearing loss that are not captured by audiometry alone. Study findings can support the correct interpretation of the RHHI in research and clinical settings.

In-situ Audiometry Compared to Conventional Audiometry for Hearing Aid Fitting.

The use of in-situ audiometry for hearing aid fitting is appealing due to its reduced resource and equipment requirements compared to standard approaches employing conventional audiometry alongside real-ear measures. However, its validity has been a subject of debate, as previous studies noted differences between hearing thresholds measured using conventional and in-situ audiometry. The differences were particularly notable for open-fit hearing aids, attributed to low-frequency leakage caused by the vent. Here, in-situ audiometry was investigated for six receiver-in-canal hearing aids from different manufacturers through three experiments. In Experiment I, the hearing aid gain was measured to investigate whether corrections were implemented to the prescribed target gain. In Experiment II, the in-situ stimuli were recorded to investigate if corrections were directly incorporated to the delivered in-situ stimulus. Finally, in Experiment III, hearing thresholds using in-situ and conventional audiometry were measured with real patients wearing open-fit hearing aids. Results indicated that (1) the hearing aid gain remained unaffected when measured with in-situ or conventional audiometry for all open-fit measurements, (2) the in-situ stimuli were adjusted for up to 30 dB at frequencies below 1000 Hz for all open-fit hearing aids except one, which also recommends the use of closed domes for all in-situ measurements, and (3) the mean interparticipant threshold difference fell within 5 dB for frequencies between 250 and 6000 Hz. The results clearly indicated that modern measured in-situ thresholds align (within 5 dB) with conventional thresholds measured, indicating the potential of in-situ audiometry for remote hearing care.

The word-with-noise test: development, validation and reference values. / Teste de palavras no ruído: desenvolvimento, validação e valores de referência.

PURPOSE: To propose an instrument for assessing speech recognition in the presence of competing noise. To define its application strategy for use in clinical practice. To obtain evidence of criterion validity and present reference values. METHODS: The study was conducted in three stages: Organization of the material comprising the Word-with-Noise Test (Stage 1); Definition of the instrument's application strategy (Stage 2); Investigation of criterion validity and definition of reference values for the test (Stage 3) through the evaluation of 50 normal-hearing adult subjects and 12 subjects with hearing loss. RESULTS: The Word-with-Noise Test consists of lists of monosyllabic and disyllabic words and speech spectrum noise (Stage 1). The application strategy for the test was defined as the determination of the Speech Recognition Threshold with a fixed noise level at 55 dBHL (Stage 2). Regarding criterion validity, the instrument demonstrated adequate ability to distinguish between normal-hearing subjects and subjects with hearing loss (Stage 3). Reference values for the test were established as cut-off points expressed in terms of signal-to-noise ratio: 1.47 dB for the monosyllabic stimulus and -2.02 dB for the disyllabic stimulus. Conclusion: The Word-with-Noise Test proved to be quick to administer and interpret, making it a useful tool in audiological clinical practice. Furthermore, it showed satisfactory evidence of criterion validity, with established reference values.

OBJETIVO: Propor um instrumento para a avaliação do reconhecimento de fala na presença de ruído competitivo. Definir sua estratégia de aplicação, para ser aplicado na rotina clínica. Obter evidências de validade de critério e apresentar seus valores de referência. MÉTODO: Estudo realizado em três etapas: Organização do material que compôs o Teste de Palavras no Ruído (Etapa 1); Definição da estratégia de aplicação do instrumento (Etapa 2); Investigação da validade de critério e definição dos valores de referência para o teste (Etapa 3), por meio da avaliação de 50 sujeitos adultos normo-ouvintes e 12 sujeitos com perda auditiva. RESULTADOS: O Teste de Palavras no Ruído é composto por listas de vocábulos mono e dissilábicos e um ruído com espectro de fala (Etapa 1). Foi definida como estratégia de aplicação do teste, a realização do Limiar de Reconhecimento de Fala com ruído fixo em 55 dBNA (Etapa 2). Quanto à validade de critério, o instrumento apresentou adequada capacidade de distinção entre os sujeitos normo-ouvintes e os sujeitos com perda auditiva (Etapa 3). Foram definidos como valores de referência para o teste, os pontos de corte expressos em relação sinal/ruído de 1,47 dB para o estímulo monossilábico e de -2,02 dB para o dissilábico. CONCLUSÃO: O Teste de Palavras no Ruído demonstrou ser rápido e de fácil aplicação e interpretação dos resultados, podendo ser uma ferramenta útil a ser utilizada na rotina clínica audiológica. Além disso, apresentou evidências satisfatórias de validade de critério, com valores de referência estabelecidos.

Modeling the Intelligibility Benefit of Active Noise Cancelation in Hearing Devices That Improve Signal-to-Noise Ratio.

The extent to which active noise cancelation (ANC), when combined with hearing assistance, can improve speech intelligibility in noise is not well understood. One possible source of benefit is ANC's ability to reduce the sound level of the direct (i.e., vent-transmitted) path. This reduction lowers the "floor" imposed by the direct path, thereby allowing any increases to the signal-to-noise ratio (SNR) created in the amplified path to be "realized" at the eardrum. Here we used a modeling approach to estimate this benefit. We compared pairs of simulated hearing aids that differ only in terms of their ability to provide ANC and computed intelligibility metrics on their outputs. The difference in metric scores between simulated devices is termed the "ANC Benefit." These simulations show that ANC Benefit increases as (1) the environmental sound level increases, (2) the ability of the hearing aid to improve SNR increases, (3) the strength of the ANC increases, and (4) the hearing loss severity decreases. The predicted size of the ANC Benefit can be substantial. For a moderate hearing loss, the model predicts improvement in intelligibility metrics of >30% when environments are moderately loud (>70 dB SPL) and devices are moderately capable of increasing SNR (by >4 dB). It appears that ANC can be a critical ingredient in hearing devices that attempt to improve SNR in loud environments. ANC will become more and more important as advanced SNR-improving algorithms (e.g., artificial intelligence speech enhancement) are included in hearing devices.

Automated hearing loss type classification based on pure tone audiometry data.

Hearing problems are commonly diagnosed with the use of tonal audiometry, which measures a patient's hearing threshold in both air and bone conduction at various frequencies. Results of audiometry tests, usually represented graphically in the form of an audiogram, need to be interpreted by a professional audiologist in order to determine the exact type of hearing loss and administer proper treatment. However, the small number of professionals in the field can severely delay proper diagnosis. The presented work proposes a neural network solution for classification of tonal audiometry data. The solution, based on the Bidirectional Long Short-Term Memory architecture, has been devised and evaluated for classifying audiometry results into four classes, representing normal hearing, conductive hearing loss, mixed hearing loss, and sensorineural hearing loss. The network was trained using 15,046 test results analysed and categorised by professional audiologists. The proposed model achieves 99.33% classification accuracy on datasets outside of training. In clinical application, the model allows general practitioners to independently classify tonal audiometry results for patient referral. In addition, the proposed solution provides audiologists and otolaryngologists with access to an AI decision support system that has the potential to reduce their burden, improve diagnostic accuracy, and minimise human error.

Easy as 1-2-3: Development and Evaluation of a Simple yet Valid Audiogram-Classification System.

Almost since the inception of the modern-day electroacoustic audiometer a century ago the results of pure-tone audiometry have been characterized by an audiogram. For almost as many years, clinicians and researchers have sought ways to distill the volume and complexity of information on the audiogram. Commonly used approaches have made use of pure-tone averages (PTAs) for various frequency ranges with the PTA for 500, 1000, 2000 and 4000 Hz (PTA4) being the most widely used for the categorization of hearing loss severity. Here, a three-digit triad is proposed as a single-number summary of not only the severity, but also the configuration and bilateral symmetry of the hearing loss. Each digit in the triad ranges from 0 to 9, increasing as the level of the pure-tone hearing threshold level (HTL) increases from a range of optimal hearing (< 10 dB Hearing Level; HL) to complete hearing loss (≥ 90 dB HL). Each digit also represents a different frequency region of the audiogram proceeding from left to right as: (Low, L) PTA for 500, 1000, and 2000 Hz; (Center, C) PTA for 3000, 4000 and 6000 Hz; and (High, H) HTL at 8000 Hz. This LCH Triad audiogram-classification system is evaluated using a large United States (U.S.) national dataset (N = 8,795) from adults 20 to 80 + years of age and two large clinical datasets totaling 8,254 adults covering a similar age range. Its ability to capture variations in hearing function was found to be superior to that of the widely used PTA4.

Cochlear implantation in pediatrics: Impact of newborn hearing screening on intervention time.

OBJECTIVES: The newborn hearing screening (NHS) program was globally established for early hearing loss (HL) identification and intervention. Early intervention is essential to minimize or prevent the negative consequences of HL. In Saudi Arabia, the NHS was officially implemented in 2016. Currently, its impact on the timing of cochlear implantations (CIs) in Saudi Arabia remains unclear, and information on potential hospital-related delays affecting early implantation is lacking. Thus, this study aimed to evaluate the effect of implementing the NHS on age at CI in children with prelingual deafness in a CI center in Saudi Arabia, and to evaluate the hospital timing in the CI process. METHODS: All pediatric CI users who presented for the first time to the CI committee (CIC) at a tertiary center and received their implants between 2015 and 2022 were enrolled in this study. Date of birth (DOB), date of presentation to the CI committee (DOCIC), and date of CI surgery (DOCIS) were retrospectively reviewed. RESULTS: In total, 304 CI children were included in the analysis. Approximately 55 % of the children (n = 167) were screened for HL through the NHS, whereas 45 % of the children (n = 137) were born before the launch of the NHS. Both age at the presentation to the CIC (i.e. difference between DOCIC and DOB) and age at implantation (i.e. difference between DOCIS and DOB) were significantly earlier in children who were screened for HL through the NHS than those who were not screened (P < 0.0001). The time difference between the DOCIC and DOCIS was not significantly different between the screened and unscreened children (P > 0.05). CONCLUSION: The implementation of the NHS in the tertiary center has a significant positive effect on age at presentation to the CIC and age at implantation, but not on the actual CI surgery. Further research is needed to reduce the hospital delays before the actual surgery in order to increase the likelihood of children receiving implantation early in their life.

[Study on the clinical characteristics of auditory neuropathy patients with normal pure tone average or mild hearing loss].

Objective: The purpose of this study was to analyze the clinical characteristics of auditory neuropathy (AN) patients with normal hearing or mild hearing loss. Methods: Data from Multicenter Study on Clinical Diagnosis and Intervention of Acoustic Neuropathy (registration number: ChiCTR2100050125). According to the Chinese clinical practice guideline of auditory neuropathy (version 2022), these patients divided into two groups: the normal hearing group (PTA Normal, PTAN group, the average hearing threshold<20 dB HL) and the mild hearing loss group (PTA Mild hearing loss, PTAM group, the average hearing threshold between 20-35 dBHL). The audiology characteristics, clinical features, and follow-up were analyzed. Data analysis was conducted using GraphPad Prism 8 and SPSS 20.0 software. Results: A total of 75 AN with normal hearing or mild hearing loss were included in this study. The PTAN group consisted of 19 patients (38 ears), including 12 males and 7 females. The average onset age was (16.9±4.5) years old, while the test age was (22.1±5.8) years old for PTAN group. The PTAM group consisted of 56 patients (112 ears), including 29 males and 27 females. The average onset age was (16.2±7.9) years old, while the test age was (23.9±9.0) yeas old for PTAM group. The average hearing threshold of low frequency (0.125-0.5 kHz) was significantly decreased. ABR disappeared in 86.00% (126/150) of the patients. The speech recognition rate was 71.80±22.44% in the PTAN group and 58.08±29.28% in the PTAM group.-SP/AP was 0.98±0.47 in the PTAN and 1.07±0.63 in PTAM group; 40 (53.33%) patients had tinnitus. 29 patients (58 ears) were followed up, including 10 patients (20 ears) in the PTAN group and 19 patients (38 ears) in the PTAM group. There was no significant change in hearing threshold in short-term follow-up (<3 years). With the extension of the disease duration (>3 years), the PTAN group tended to decrease at low frequency, and the PTAM group decreased at high frequency first. The hearing threshold at 0.25 kHz in the PTAN group and 4 kHz in the PTAM group decreased significantly. Conclusions: AN patients with normal hearing or mild hearing loss exhibit abnormal results in audiological examination results, including ABR, electrocochleography and speech discrimination score. A combination of audiological tests should be used to make the diagnosis of AN. With the progression of the disease, AN with normal hearing or mild hearing loss tends to decrease.

An Exploration of the Memory Performance in Older Adult Hearing Aid Users on the Integrated Digit-in-Noise Test.

This study aimed to preliminarily investigate the associations between performance on the integrated Digit-in-Noise Test (iDIN) and performance on measures of general cognition and working memory (WM). The study recruited 81 older adult hearing aid users between 60 and 95 years of age with bilateral moderate to severe hearing loss. The Chinese version of the Montreal Cognitive Assessment Basic (MoCA-BC) was used to screen older adults for mild cognitive impairment. Speech reception thresholds (SRTs) were measured using 2- to 5-digit sequences of the Mandarin iDIN. The differences in SRT between five-digit and two-digit sequences (SRT5-2), and between five-digit and three-digit sequences (SRT5-3), were used as indicators of memory performance. The results were compared to those from the Digit Span Test and Corsi Blocks Tapping Test, which evaluate WM and attention capacity. SRT5-2 and SRT5-3 demonstrated significant correlations with the three cognitive function tests (rs ranging from -.705 to -.528). Furthermore, SRT5-2 and SRT5-3 were significantly higher in participants who failed the MoCA-BC screening compared to those who passed. The findings show associations between performance on the iDIN and performance on memory tests. However, further validation and exploration are needed to fully establish its effectiveness and efficacy.

Does Intraoperative Extracochlear Electrocochleography Correlate With Postoperative Audiometric Hearing Thresholds in Cochlear Implant Surgery? A Retrospective Analysis of Cochlear Monitoring.

In recent years, tools for early detection of irreversible trauma to the basilar membrane during hearing preservation cochlear implant (CI) surgery were established in several clinics. A link with the degree of postoperative hearing preservation in patients was investigated, but patient populations were usually small. Therefore, this study's aim was to analyze data from intraoperative extracochlear electrocochleography (ECochG) recordings for a larger group.During hearing preservation CI surgery, extracochlear recordings were made before, during, and after CI electrode insertion using a cotton wick electrode placed at the promontory. Before and after insertion, amplitudes and stimulus response thresholds were recorded at 250, 500, and 1000 Hz. During insertion, response amplitudes were recorded at one frequency and one stimulus level. Data from 121 patient ears were analyzed.The key benefit of extracochlear recordings is that they can be performed before, during, and after CI electrode insertion. However, extracochlear ECochG threshold changes before and after CI insertion were relatively small and did not independently correlate well with hearing preservation, although at 250 Hz they added some significant information. Some tendencies-although no significant relationships-were detected between amplitude behavior and hearing preservation. Rising amplitudes seem favorable and falling amplitudes disadvantageous, but constant amplitudes do not appear to allow stringent predictions.Extracochlear ECochG measurements seem to only partially realize expected benefits. The questions now are: do gains justify the effort, and do other procedures or possible combinations lead to greater benefits for patients?

Deep learning-based auditory attention decoding in listeners with hearing impairment.

Objective.This study develops a deep learning (DL) method for fast auditory attention decoding (AAD) using electroencephalography (EEG) from listeners with hearing impairment (HI). It addresses three classification tasks: differentiating noise from speech-in-noise, classifying the direction of attended speech (left vs. right) and identifying the activation status of hearing aid noise reduction algorithms (OFF vs. ON). These tasks contribute to our understanding of how hearing technology influences auditory processing in the hearing-impaired population.Approach.Deep convolutional neural network (DCNN) models were designed for each task. Two training strategies were employed to clarify the impact of data splitting on AAD tasks: inter-trial, where the testing set used classification windows from trials that the training set had not seen, and intra-trial, where the testing set used unseen classification windows from trials where other segments were seen during training. The models were evaluated on EEG data from 31 participants with HI, listening to competing talkers amidst background noise.Main results.Using 1 s classification windows, DCNN models achieve accuracy (ACC) of 69.8%, 73.3% and 82.9% and area-under-curve (AUC) of 77.2%, 80.6% and 92.1% for the three tasks respectively on inter-trial strategy. In the intra-trial strategy, they achieved ACC of 87.9%, 80.1% and 97.5%, along with AUC of 94.6%, 89.1%, and 99.8%. Our DCNN models show good performance on short 1 s EEG samples, making them suitable for real-world applications. Conclusion: Our DCNN models successfully addressed three tasks with short 1 s EEG windows from participants with HI, showcasing their potential. While the inter-trial strategy demonstrated promise for assessing AAD, the intra-trial approach yielded inflated results, underscoring the important role of proper data splitting in EEG-based AAD tasks.Significance.Our findings showcase the promising potential of EEG-based tools for assessing auditory attention in clinical contexts and advancing hearing technology, while also promoting further exploration of alternative DL architectures and their potential constraints.

Reliability and Validity of the Turkish Version of the Vanderbilt Fatigue Scale for Adults.

PURPOSE: Listening-related fatigue (LRF) is a prominent topic of research interest. The purpose of this study is to investigate the reliability and validity of the Turkish version of the 40-item Vanderbilt Fatigue Scale for Adults (TR-VFS-A-40). METHOD: This study included 317 adults with no hearing loss and 260 adults with hearing loss in the study group, totaling 577 adults aged 18-75 years. While 31 adults in the study group did not use any hearing technology, there were 96 hearing aid users and 123 cochlear implant (CI) users. A subset of 80 CI users completed the TR-VFS-A-40 a second time, 2 weeks later, to assess test-retest reliability. Intraclass correlation coefficients were used to assess test-retest reliability. Cronbach's alpha was used to evaluate internal consistency. To examine construct validity, a confirmatory factor analysis (CFA) was performed. For concurrent validity analysis, the Checklist Individual Strength (CIS) and TR-VFS-A-40 scores were analyzed using the Spearman correlation test. RESULTS: Cronbach's alpha values were excellent for the total scale of .987 and the cognitive, emotional, physical, and social subscales (.953, .954, .955, and .946, respectively). Analyses of concurrent validity revealed strong and significant correlations between CIS and TR-VFS-A-40 scores, indicating a good concurrent validity. The CFA determined that the construct validity of the TR-VFS-A-40 was satisfactory. CONCLUSION: The TR-VFS-A-40 is a valid and reliable measure of LRF. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.25457752.

Evaluating Hearing Status and Word Recognition Ability in the Hmong Population Using Four Validated Monosyllabic White Hmong Dialect Word Recognition Tests.

PURPOSE: The study's aims were (a) to evaluate hearing status and (b) word recognition ability of Hmong speakers using four validated monosyllabic word recognition tests in the White Hmong dialect and (c) to assess the relationship between the participant's language and the average word recognition percent correct scores, adjusting for age, gender, and degree of hearing loss. METHOD: Participants listened to two randomly assigned validated Hmong word lists (male/female talker) for each ear. Pure-tone air- and bone-conduction thresholds as well as word recognition ability were measured. Descriptive statistics were calculated to analyze the percent correct of word lists and classify hearing status. A nonparametric regression analysis was used to assess the relationship between the participant's language and the average word recognition percent correct scores, adjusting for age, gender, and degree of hearing loss. RESULTS: Forty-eight Hmong (25 females, 23 males; Mage = 44.4) participated in this study. Thirty-three participants had hearing loss in at least one ear, and 15 had hearing within normal limits bilaterally. Participants with normal, mild, or steeply sloping hearing loss reached an average word recognition score of > 94% on Hmong lists by both male and female talkers. Participants with moderate-to-severe hearing loss scored 68% on average for the male talker Hmong lists and 60% on average for the female talker Hmong lists. Gender was significantly positively associated with average word recognition percent correct on the female word lists (b = -0.224, p = .047) but not statistically significant for the male word lists (b = 7.579, p = .141). CONCLUSION: Findings provide support for the use of the four Hmong word lists in clinical settings.

A machine learning screening model for identifying the risk of high-frequency hearing impairment in a general population.

BACKGROUND: Hearing impairment (HI) has become a major public health issue in China. Currently, due to the limitations of primary health care, the gold standard for HI diagnosis (pure-tone hearing test) is not suitable for large-scale use in community settings. Therefore, the purpose of this study was to develop a cost-effective HI screening model for the general population using machine learning (ML) methods and data gathered from community-based scenarios, aiming to help improve the hearing-related health outcomes of community residents. METHODS: This study recruited 3371 community residents from 7 health centres in Zhejiang, China. Sixty-eight indicators derived from questionnaire surveys and routine haematological tests were delivered and used for modelling. Seven commonly used ML models (the naive Bayes (NB), K-nearest neighbours (KNN), support vector machine (SVM), random forest (RF), eXtreme Gradient Boosting (XGBoost), boosting, and least absolute shrinkage and selection operator (LASSO regression)) were adopted and compared to develop the final high-frequency hearing impairment (HFHI) screening model for community residents. The model was constructed with a nomogram to obtain the risk score of the probability of individuals suffering from HFHI. According to the risk score, the population was divided into three risk stratifications (low, medium and high) and the risk factor characteristics of each dimension under different risk stratifications were identified. RESULTS: Among all the algorithms used, the LASSO-based model achieved the best performance on the validation set by attaining an area under the curve (AUC) of 0.868 (95% confidence interval (CI): 0.847-0.889) and reaching precision, specificity and F-score values all greater than 80%. Five demographic indicators, 7 disease-related features, 5 behavioural factors, 2 environmental exposures, 2 hearing cognitive factors, and 13 blood test indicators were identified in the final screening model. A total of 91.42% (1235/1129) of the subjects in the high-risk group were confirmed to have HI by audiometry, which was 3.99 times greater than that in the low-risk group (22.91%, 301/1314). The high-risk population was mainly characterized as older, low-income and low-educated males, especially those with multiple chronic conditions, noise exposure, poor lifestyle, abnormal blood indices (e.g., red cell distribution width (RDW) and platelet distribution width (PDW)) and liver function indicators (e.g., triglyceride (TG), indirect bilirubin (IBIL), aspartate aminotransferase (AST) and low-density lipoprotein (LDL)). An HFHI nomogram was further generated to improve the operability of the screening model for community applications. CONCLUSIONS: The HFHI risk screening model developed based on ML algorithms can more accurately identify residents with HFHI by categorizing them into the high-risk groups, which can further help to identify modifiable and immutable risk factors for residents at high risk of HI and promote their personalized HI prevention or intervention.

Audiometry Interpretation for Hearing Loss in Adults.

Hearing loss is a prevalent, chronic condition in the United States; it is often gradual and progressive and is underreported by patients and undertreated by physicians. The impaired ability to effectively hear and communicate may result in negative emotional, cognitive, economic, and social consequences for individuals and may pose a safety risk. Questionnaires and smartphone apps are available to help identify and evaluate self-perceived hearing loss. Physicians should assess for objective hearing impairment when the patient or family member raises a concern or if cognitive or mood symptoms are present that could be influenced by hearing loss. Three types of hearing loss exist: conductive, sensorineural, and mixed. Pure-tone audiometry uses an audiometer and is reported on an audiogram; it is the most accurate method for hearing loss detection. It can be used for screening or comprehensive testing when combined with tympanometry, speech-reception thresholds, and word-recognition testing. Audiograms that show a unilateral or asymmetrical sensorineural hearing loss can be signs of retrocochlear pathology and warrant additional evaluation by an audiologist and otolaryngologist as well as imaging studies. Medicare Parts A and B do not pay for hearing aids, although some Medicare Advantage (Part C) or supplemental plans may provide insurance coverage for hearing aids. Less expensive, over-the-counter hearing aids may help mild to moderate hearing loss. Family physicians should counsel patients on the importance of protecting their hearing.

Focusing on Positive Listening Experiences Improves Speech Intelligibility in Experienced Hearing Aid Users.

Negativity bias is a cognitive bias that results in negative events being perceptually more salient than positive ones. For hearing care, this means that hearing aid benefits can potentially be overshadowed by adverse experiences. Research has shown that sustaining focus on positive experiences has the potential to mitigate negativity bias. The purpose of the current study was to investigate whether a positive focus (PF) intervention can improve speech-in-noise abilities for experienced hearing aid users. Thirty participants were randomly allocated to a control or PF group (N = 2 × 15). Prior to hearing aid fitting, all participants filled out the short form of the Speech, Spatial and Qualities of Hearing scale (SSQ12) based on their own hearing aids. At the first visit, they were fitted with study hearing aids, and speech-in-noise testing was performed. Both groups then wore the study hearing aids for two weeks and sent daily text messages reporting hours of hearing aid use to an experimenter. In addition, the PF group was instructed to focus on positive listening experiences and to also report them in the daily text messages. After the 2-week trial, all participants filled out the SSQ12 questionnaire based on the study hearing aids and completed the speech-in-noise testing again. Speech-in-noise performance and SSQ12 Qualities score were improved for the PF group but not for the control group. This finding indicates that the PF intervention can improve subjective and objective hearing aid benefits.

Clinical Practice Guideline: Age-Related Hearing Loss.

OBJECTIVE: Age-related hearing loss (ARHL) is a prevalent but often underdiagnosed and undertreated condition among individuals aged 50 and above. It is associated with various sociodemographic factors and health risks including dementia, depression, cardiovascular disease, and falls. While the causes of ARHL and its downstream effects are well defined, there is a lack of priority placed by clinicians as well as guidance regarding the identification, education, and management of this condition. PURPOSE: The purpose of this clinical practice guideline is to identify quality improvement opportunities and provide clinicians trustworthy, evidence-based recommendations regarding the identification and management of ARHL. These opportunities are communicated through clear actionable statements with explanation of the support in the literature, evaluation of the quality of the evidence, and recommendations on implementation. The target patients for the guideline are any individuals aged 50 years and older. The target audience is all clinicians in all care settings. This guideline is intended to focus on evidence-based quality improvement opportunities judged most important by the guideline development group (GDG). It is not intended to be a comprehensive, general guide regarding the management of ARHL. The statements in this guideline are not intended to limit or restrict care provided by clinicians based on their experience and assessment of individual patients. ACTION STATEMENTS: The GDG made strong recommendations for the following key action statements (KASs): (KAS 4) If screening suggests hearing loss, clinicians should obtain or refer to a clinician who can obtain an audiogram. (KAS 8) Clinicians should offer, or refer to a clinician who can offer, appropriately fit amplification to patients with ARHL. (KAS 9) Clinicians should refer patients for an evaluation of cochlear implantation candidacy when patients have appropriately fit amplification and persistent hearing difficulty with poor speech understanding. The GDG made recommendations for the following KASs: (KAS 1) Clinicians should screen patients aged 50 years and older for hearing loss at the time of a health care encounter. (KAS 2) If screening suggests hearing loss, clinicians should examine the ear canal and tympanic membrane with otoscopy or refer to a clinician who can examine the ears for cerumen impaction, infection, or other abnormalities. (KAS 3) If screening suggests hearing loss, clinicians should identify sociodemographic factors and patient preferences that influence access to and utilization of hearing health care. (KAS 5) Clinicians should evaluate and treat or refer to a clinician who can evaluate and treat patients with significant asymmetric hearing loss, conductive or mixed hearing loss, or poor word recognition on diagnostic testing. (KAS 6) Clinicians should educate and counsel patients with hearing loss and their family/care partner(s) about the impact of hearing loss on their communication, safety, function, cognition, and quality of life (QOL). (KAS 7) Clinicians should counsel patients with hearing loss on communication strategies and assistive listening devices. (KAS 10) For patients with hearing loss, clinicians should assess if communication goals have been met and if there has been improvement in hearing-related QOL at a subsequent health care encounter or within 1 year. The GDG offered the following KAS as an option: (KAS 11) Clinicians should assess hearing at least every 3 years in patients with known hearing loss or with reported concern for changes in hearing.