A Smartphone-Based Approach to Screening for Sudden Sensorineural Hearing Loss: Cross-Sectional Validity Study

Validated mobile applications in otolaryngology head and neck surgery for patient and physicians: A systematic literature review

IMPORTANCE

Mobile apps in the field of ORL-HNS, are widely used by patients and physicians, but neither necessarily developed in collaboration with healthcare professionals nor subjected to regulations by the United States Food and Drug Administration guidelines, with a resultant potential of risk for its users.

OBJECTIVE

To provide the ORL-HNS physician with an updated list of scientific peer review literature- validated mobile apps for safe use for both the clinician and the patients, for screening, diagnosis, therapy and follow up for various ORL-HNS pathologies.

EVIDENCE REVIEW

A comprehensive systematic review of the scientific literature was conducted in "PubMed," "EMBASE," and "Web of Science" without limitation of publication date up to January 1st, 2023. The included papers validated mobile apps in the ORL-HNS discipline. Each study was evaluated using the "Strengthening the Reporting of Observational Studies in Epidemiology" (STROBE) tool.

FINDINGS

From the thousands of unregulated ORL-HNS mobile apps available for download and use in the various app stores, only 17 apps were validated for safe use by the clinician and/or patient. Their information is listed.

CONCLUSIONS AND RELEVANCE

The limited number of validated mobile apps highlights the importance to use validated apps in clinical practice, to improve evidence-based medicine and patient safety. Physician are encouraged to use and recommend their patients to use validated mobile apps only, like any other tool in clinical practice in the evidence-based era.

Access to Sudden Sensorineural Hearing Loss Care at Private Equity-Owned Otolaryngology Clinics

OBJECTIVE

Characterizing access to sudden sensorineural hearing loss (SSNHL) care at private practice otolaryngology clinics of varying ownership models.

STUDY DESIGN

Cross-sectional prospective review.

SETTING

Private practice otolaryngology clinics.

METHODS

We employed a Secret Shopper study design with private equity (PE) owned and non-PE-owned clinics within 15 miles of one another. Using a standardized script, researchers randomly called 50% of each clinic type between October 2021 and January 2022 requesting an appointment on behalf of a family member enrolled in either Medicaid or private insurance (PI) experiencing SSNHL. Access to timely care was assessed between clinic ownership and insurance type.

RESULTS

Seventy-eight total PE-owned otolaryngology clinics were identified across the United States. Only 40 non-PE clinics could be matched to the PE clinics; 39 PE and 28 non-PE clinics were called as Medicaid patients; 39 PE and 25 non-PE clinics were called as PI patients; 48.7% of PE and 28.6% of non-PE clinics accepted Medicaid. The mean wait time to new appointment ranged between 9.55 and 13.21 days for all insurance and ownership types but did not vary significantly (P > .480). Telehealth was significantly more likely to be offered for new Medicaid patients at non-PE clinics compared to PE clinics (31.8% vs 0.0%, P = .001). The mean cost for an appointment was significantly greater at PE clinics than at non-PE clinics ($291.18 vs $203.75, P = .004).

CONCLUSIONS

Patients seeking SSNHL care at PE-owned otolaryngology clinics are likely to face long wait times prior to obtaining an initial appointment and reduced telehealth options.

Optimizing age-related hearing risk predictions: an advanced machine learning integration with HHIE-S

OBJECTIVES

The elderly are disproportionately affected by age-related hearing loss (ARHL). Despite being a well-known tool for ARHL evaluation, the Hearing Handicap Inventory for the Elderly Screening version (HHIE-S) has only traditionally been used for direct screening using self-reported outcomes. This work uses a novel integration of machine learning approaches to improve the predicted accuracy of the HHIE-S tool for ARHL in older adults.

METHODS

We employed a dataset that was gathered between 2016 and 2018 and included 1,526 senior citizens from several Taipei City Hospital branches. 80% of the data were used for training (n = 1220) and 20% were used for testing (n = 356). XGBoost, Gradient Boosting, and LightGBM were among the machine learning models that were only used and assessed on the training set. In order to prevent data leakage and overfitting, the Light Gradient Boosting Machine (LGBM) model-which had the greatest AUC of 0.83 (95% CI 0.81-0.85)-was then only used on the holdout testing data.

RESULTS

On the testing set, the LGBM model showed a strong AUC of 0.82 (95% CI 0.79-0.86), far outperforming conventional techniques. Notably, several HHIE-S items and age were found to be significant characteristics. In contrast to traditional HHIE research, which concentrates on the psychological effects of hearing loss, this study combines cutting-edge machine learning techniques-specifically, the LGBM classifier-with the HHIE-S tool. The incorporation of SHAP values enhances the interpretability of the model's predictions and provides a more comprehensive comprehension of the significance of various aspects.

CONCLUSIONS

Our methodology highlights the great potential that arises from combining machine learning with validated hearing evaluation instruments such as the HHIE-S. Healthcare practitioners can anticipate ARHL more accurately thanks to this integration, which makes it easier to intervene quickly and precisely.

Diagnostic Accuracy of Mobile Health-Based Audiometry for the Screening of Hearing Loss in Adults: A Systematic Review and Meta-Analysis

Background: Hearing loss is one of the most prevalent chronic health conditions. Traditional pure tone audiometry (PTA) is the gold standard for hearing loss screening, but is not widely available outside specialized clinical centers. Mobile health (mHealth)-based audiometry could improve access and cost-effectiveness, but its diagnostic accuracy varies widely between studies. Therefore, we aimed to evaluate the diagnostic accuracy of mHealth-based audiometry for hearing loss screening in adults compared with traditional PTA. Methods: Ten English and Chinese databases were searched from inception until April 30, 2022. Two researchers independently selected studies, extracted data, and appraised methodological quality. The bivariate random-effects model was adopted to estimate the pooled sensitivity and specificity for each common threshold (i.e., the threshold to define mild or moderate hearing loss). The hierarchical summary receiver operating characteristic model was used to assess the area under the receiver operating characteristic curve (AUC) across all thresholds. Results: Twenty cohort studies were included. Only one study (n = 109) used the mHealth-based speech recognition test (SRT) as the index test. Nineteen studies (n = 1,656) used mHealth-based PTA as the index test, and all of them were included in the meta-analysis. For detecting mild hearing loss, the pooled sensitivity and specificity were 0.91 (95% confidence interval [CI] 0.80-0.96) and 0.90 (95% CI 0.82-0.94), respectively. For detecting moderate hearing loss, the pooled sensitivity and specificity were 0.94 (95% CI 0.87-0.98) and 0.87 (95% CI 0.79-0.93), respectively. For all PTA thresholds, the AUC was 0.96 (95% CI 0.40-1.00). Conclusions: mHealth-based audiometry provided good diagnostic accuracy for screening both mild and moderate hearing loss in adults. Given its high diagnostic accuracy, accessibility, convenience, and cost-effectiveness, it shows enormous potential for hearing loss screening, particularly in primary care sites, low-income regions, and settings with in-person visit limitations. Further work should evaluate the diagnostic accuracy of the mHealth-based SRT tests.

Is There an Association between Concurrent Epstein-Barr Virus Infection and Sudden Hearing Loss?-A Case-Control Study in an East Asian Population

Viral infection serves as the crucial etiology for the development of sudden sensorineural hearing loss (SSNHL). We aimed to investigate whether there is an association between concurrent Epstein-Barr virus (EBV) infection and SSNHL in an East Asian population. Patients who were older than 18 years of age and met the criteria of sudden hearing loss without an identifiable etiology were enrolled from July 2021 until June 2022, followed by the serological testing of IgA antibody responses against EBV-specific early antigen (EA) and viral capsid antigen (VCA) with an indirect hemagglutination assay (IHA) and real-time quantitative polymerase chain reaction (qPCR) of EBV DNA in serum before the treatment was initiated. After the treatment for SSNHL, post-treatment audiometry was performed to record the treatment response and degree of recovery. Among the 29 patients included during enrollment, 3 (10.3%) had a positive qPCR result for EBV. In addition, a trend of poor recovery of hearing thresholds was noted for those patients with a higher viral PCR titer. This is the first study to use real-time PCR to detect possible concurrent EBV infection in SSNHL. Our study demonstrated that approximately one-tenth of the enrolled SSNHL patients had evidence of concurrent EBV infection, as reflected by the positive qPCR test results, and a negative trend between hearing gain and the viral DNA PCR level was found within the affected cohort after steroid therapy. These findings indicate a possible role for EBV infection in East Asian patients with SSNHL. Further larger-scale research is needed to better understand the potential role and underlying mechanism of viral infection in the etiology of SSNHL.

Evaluating the hearing screening effectiveness of active noise cancellation technology among young adults: A pilot study

BACKGROUND

The population of young adults who are hearing impaired increases yearly, and a device that enables convenient hearing screening could help monitor their hearing. However, background noise is a critical issue that limits the capabilities of such a device. Therefore, this study evaluated the effectiveness of commercial active noise cancellation (ANC) headphones for hearing screening applications in the presence of background noise. In particular, six confounders were used for a comprehensive evaluation.

METHODS

We enrolled 12 young adults (a total of 23 ears with normal hearing) to participate in this study. A cross-sectional self-controlled study was conducted to explore the effectiveness of hearing screening in the presence of background noise, with a total of 240 test conditions (=3 ANC models × 2 ANC function statuses × 2 noise types × 5 noise levels × 4 frequencies) for each test ear. Subsequently, a linear regression model was used to prove the effectiveness of ANC headphones for hearing screening applications in the presence of background noise with six confounders.

RESULTS

The experimental results showed that, on average, the ANC function of headphones can improve the effectiveness of hearing screening tasks in the presence of background noise. Specifically, the statistical analysis showed that the ANC function enabled a significant 10% improvement ( p < 0.001) compared with no ANC function.

CONCLUSION

This study confirmed the effectiveness of ANC headphones for young adult hearing screening applications in the presence of background noise. Furthermore, the statistical results confirmed that as confounding variables, noise type, noise level, hearing screening frequency, ANC headphone model, and sex all affect the effectiveness of the ANC function. These findings suggest that ANC is a potential means of helping users obtain high-accuracy hearing screening results in the presence of background noise. Moreover, we present possible directions of development for ANC headphones in future studies.

Long-term Follow-up of Patients With Hernia Using the Hernia-Specific Quality-of-Life Mobile App: Feasibility Questionnaire Study

BACKGROUND

Hernia repair is one of the most common surgical procedures; however, the long-term outcomes are seldom reported due to incomplete follow-up.

OBJECTIVE

The aim of this study was to examine the use of a mobile app for the long-term follow-up of hernia recurrence, complication, and quality-of-life perception.

METHODS

A cloud-based corroborative system drove a mobile app with the HERQL (Hernia-Specific Quality-of-Life) questionnaire built in. Patients who underwent hernia repair were identified from medical records, and an invitation to participate in this study was sent through the post.

RESULTS

The response rate was 11.89% (311/2615) during the 1-year study period, whereas the recurrence rate was 1.0% (3/311). Causal relationships between symptomatic and functional domains of the HERQL questionnaire were indicated by satisfactory model fit indices and significant regression coefficients derived from structural equational modeling. Regarding patients' last hernia surgeries, 88.7% (276/311) of the patients reported them to be satisfactory or very satisfactory, 68.5% (213/311) of patients reported no discomfort, and 61.1% (190/311) of patients never experienced mesh foreign body sensation. Subgroup analysis for the most commonly used mesh repairs found that mesh plug repair inevitably resulted in worse symptoms and quality-of-life perception from the group with groin hernias.

CONCLUSIONS

The mobile app has the potential to enhance the quality of care for patients with hernia and facilitate outcomes research with more complete follow-up.

Objective Signal Analysis for Investigating Feasibility of Active Noise Cancellation in Hearing Screening

With the development of active noise cancellation (ANC) technology, ANC has been used to mitigate the effects of environmental noise on audiometric results. However, objective evaluation methods supporting the accuracy of audiometry for ANC exposure to different levels of noise have not been reported. Accordingly, the audio characteristics of three different ANC headphone models were quantified under different noise conditions and the feasibility of ANC in noisy environments was investigated. Steady (pink noise) and non-steady noise (cafeteria babble noise) were used to simulate noisy environments. We compared the integrity of pure-tone signals obtained from three different ANC headphone models after processing under different noise scenarios and analyzed the degree of ANC signal correlation based on the Pearson correlation coefficient compared to pure-tone signals in quiet. The objective signal correlation results were compared with audiometric screening results to confirm the correspondence. Results revealed that ANC helped mitigate the effects of environmental noise on the measured signal and the combined ANC headset model retained the highest signal integrity. The degree of signal correlation was used as a confidence indicator for the accuracy of hearing screening in noise results. It was found that the ANC technique can be further improved for more complex noisy environments.

Telemedicine for Patients With Unilateral Sudden Hearing Loss in the COVID-19 Era

Importance

Developing a telemedicine tool to discriminate between patients who need urgent treatment for sudden sensorineural hearing loss (SSNHL) from those who do not takes on special importance during the COVID-19 pandemic.

Objective

To explore the feasibility of a telemedicine model to assist in the evaluation of new-onset unilateral sudden hearing loss (SHL) among patients who do not have access to medical resources, especially during the COVID-19 pandemic.

Design, Setting, and Participants

This prospective cohort investigation of a telemedicine model was conducted at a tertiary referral medical center between May 2020 and January 2021, with the interpreting physician blinded to the results of formal audiograms. The study included a consecutive sample of adult patients (aged ≥18 years) referred to the otolaryngology emergency department in our medical center with the chief complaint of new-onset unilateral SHL.

Interventions

The telemedicine model comprised 2 sequential steps: a Weber test using the Hum Test and a smartphone-based vibration, and uHear app-based audiometry.

Main Outcomes and Measures

Discrimination between patients with and without SSNHL by using the telemedicine model. All diagnoses subsequently confirmed by a formal audiogram.

Results

Fifty-one patients with new-onset unilateral SHL participated in the study study (median age, 45 [range, 18-76] years; 28 [54.9%] men). The sensitivity and specificity of the telemedicine model for fulfilling the audiometric criteria of SSNHL (loss of ≥30 dB in ≥3 consecutive frequencies) were 100% (95% CI, 84%-100%) and 73% (95% CI, 54%-88%), respectively. The PPV was 72% (95% CI, 53%-87%), the NPV was 100% (95% CI, 85%-100%), and the accuracy was 84.3% (95% CI, 71%-93%). Although 8 participants had false-positive results, all of them had SSNHL that did not meet the full audiometric criteria.

Conclusions and Relevance

The telemedicine model presented in this study for the diagnosis of SSNHL is valid and reliable. It may serve as a primary tool for the discrimination between patients in need of urgent care for SSNHL from those who are not, especially during the COVID-19 pandemic.

Diagnostic Validity of Self-Reported Hearing Loss in Elderly Taiwanese Individuals: Diagnostic Performance of a Hearing Self-Assessment Questionnaire on Audiometry

Key Points: Question: Can the traditional Chinese version of the hearing handicap inventory for elderly screening (HHIE-S) checklist screen for age-related hearing loss (ARHL) in elderly individuals? Findings: In this cross-sectional study of 1696 Taiwanese patients who underwent annual government-funded geriatric health checkups, the Chinese version of the HHIE-S had a sensitivity of 76.9% and a specificity of 79.8% with a cutoff score greater than 6 for identifying patients with disabled hearing loss (defined as a PTA > 40 dB). Meaning: The traditional Chinese version of the HHIE-S is an effective test to detect ARHL and can improve the feasibility of large-scale hearing screening among elderly individuals. Purpose: The traditional Chinese version of the hearing handicap inventory for elderly screening (TC-HHIE-S) was translated from English and is intended for use with people whose native language is traditional Chinese, but its effectiveness and diagnostic performance are still unclear. The purpose of this study was to evaluate the validity and reliability of the traditional Chinese version of the HHIE-S for screening for age-related hearing loss (ARHL). Methods: A total of 1696 elderly people underwent the government’s annual geriatric medical examination at community hospitals. In this cross-sectional study, we recorded average conducted pure-tone averages (PTA) (0.5 kHz, 1 kHz, 2 kHz, 4 kHz), age, sex, and HHIE-S data. Receiver operating characteristic (ROC) curve analysis was used to identify the best critical point for detecting hearing impairment, and the validity of the structure was verified by the agreement between the TC-HHIE-S and PTA results. Results: The HHIE-S scores were correlated with the better-ear pure-tone threshold averages (PTAs) at 0.5–4 kHz (correlation coefficient r = 0.45). The internal consistency of the total HHIE-S score was excellent (Cronbach’s alpha = 0.901), and the test-retest reliability was also excellent (Spearman’s correlation coefficient = 0.60, intraclass correlation coefficient = 0.75). In detecting disabled hearing loss (i.e., PTA at 0.5–4 kHz > 40 dB), the HHIE-S cutoff score of > 6 had a sensitivity of 76.9% and a specificity of 79.8%. Conclusions: The traditional Chinese version of the HHIE-S is a valid, reliable, and efficient tool for large-scale screening for ARHL.

Diagnostic Accuracy of Smartphone-Based Audiometry for Hearing Loss Detection: Meta-analysis

Background

Hearing loss is one of the most common disabilities worldwide and affects both individual and public health. Pure tone audiometry (PTA) is the gold standard for hearing assessment, but it is often not available in many settings, given its high cost and demand for human resources. Smartphone-based audiometry may be equally effective and can improve access to adequate hearing evaluations.

Objective

The aim of this systematic review is to synthesize the current evidence of the role of smartphone-based audiometry in hearing assessments and further explore the factors that influence its diagnostic accuracy.

Methods

Five databases—PubMed, Embase, Cochrane Library, Web of Science, and Scopus—were queried to identify original studies that examined the diagnostic accuracy of hearing loss measurement using smartphone-based devices with conventional PTA as a reference test. A bivariate random-effects meta-analysis was performed to estimate the pooled sensitivity and specificity. The factors associated with diagnostic accuracy were identified using a bivariate meta-regression model. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

Results

In all, 25 studies with a total of 4470 patients were included in the meta-analysis. The overall sensitivity, specificity, and area under the receiver operating characteristic curve for smartphone-based audiometry were 89% (95% CI 83%-93%), 93% (95% CI 87%-97%), and 0.96 (95% CI 0.93-0.97), respectively; the corresponding values for the smartphone-based speech recognition test were 91% (95% CI 86%-94%), 88% (95% CI 75%-94%), and 0.93 (95% CI 0.90-0.95), respectively. Meta-regression analysis revealed that patient age, equipment used, and the presence of soundproof booths were significantly related to diagnostic accuracy.

Conclusions

We have presented comprehensive evidence regarding the effectiveness of smartphone-based tests in diagnosing hearing loss. Smartphone-based audiometry may serve as an accurate and accessible approach to hearing evaluations, especially in settings where conventional PTA is unavailable.