Speech recognition with hearing aids for 10 standard audiograms : English version

Accuracy and Consistency of Confidence Limits for Monosyllable Identification Scores Derived Using Simulation, the Harrell-Davis Estimator, and Nonlinear Quantile Regression

BACKGROUND

Audiological diagnosis and rehabilitation often involve the assessment of whether the maximum speech identification score (PBmax) is poorer than expected from the pure-tone average (PTA) threshold. This requires the estimation of the lower boundary of the PBmax values expected for a given PTA (one-tailed 95% confidence limit, CL). This study compares the accuracy and consistency of three methods for estimating the 95% CL.

METHOD

The 95% CL values were estimated using a simulation method, the Harrell-Davis (HD) estimator, and non-linear quantile regression (nQR); the latter two are both distribution-free methods. The first two methods require the formation of sub-groups with different PTAs. Accuracy and consistency in the estimation of the 95% CL were assessed by applying each method to many random samples of 50% of the available data and using the fitted parameters to predict the data for the remaining 50%.

STUDY SAMPLE

A total of 642 participants aged 17 to 84 years with sensorineural hearing loss were recruited from audiology clinics. Pure-tone audiograms were obtained and PBmax scores were measured using monosyllables at 40 dB above the speech recognition threshold or at the most comfortable level.

RESULTS

For the simulation method, 6.7 to 8.2% of the PBmax values fell below the 95% CL for both ears, exceeding the target value of 5%. For the HD and nQR methods, the PBmax values fell below the estimated 95% CL for approximately 5% of the ears, indicating good accuracy. Consistency, estimated from the standard deviation of the deviations from the target value of 5%, was similar for all the methods.

CONCLUSIONS

The nQR method is recommended because it has good accuracy and consistency, and it does not require the formation of arbitrary PTA sub-groups.

Impact of unilateral vs. bilateral evaluation on cochlear implant candidacy

BACKGROUND

The indication criteria for cochlear implantation differ considerably across regions.

OBJECTIVES

To estimate the effects of different candidacy criteria on the number of cochlear implant (CI) candidates.

METHODS

We analysed a very large clinical audiological database comprising pure-tone thresholds and speech-audiometric data in order to identify CI candidates on the basis of different audiometric candidacy criteria. In particular, we simulated the effects of three different CI candidacy criteria.

RESULTS

The bilateral evaluation of CI candidacy has the strongest influence on the number of potential CI candidates. Additionally, the cut-off criteria for middle-ear implants have a large effect on numbers of candidates when air conduction has deteriorated.Conclusions and Significance: Expanding the indication criteria opens up the possibility of improving the accurate identification of individual cases suitable for cochlear-implant provision.

Outcome Prediction of Speech Perception in Quiet and in Noise for Cochlear Implant Candidates Based on Pre-Operative Measures

(1) Background: The fitting of cochlear implants (CI) is an established treatment, even in cases with considerable residual hearing but insufficient speech perception. The aim of this study was to evaluate a prediction model for speech in quiet and to provide reference data and a predictive model for postoperative speech perception in noise (SPiN) after CI provision. (2) Methods: CI candidates with substantial residual hearing (either in hearing threshold or in word recognition scores) were included in a retrospective analysis (n = 87). Speech perception scores in quiet 12 months post-surgery were compared with the predicted scores. A generalized linear model was fitted to speech reception thresholds (SRTs) after CI fitting to identify predictive variables for SPiN. (3) Results: About two-thirds of the recipients achieved the expected outcome in quiet or were better than expected. The mean absolute error of the prediction was 13.5 percentage points. Age at implantation was the only predictive factor for SPiN showing a significant correlation (r = 0.354; p = 0.007). (4) Conclusions: Outcome prediction accuracy for speech in quiet was comparable to previous studies. For CI recipients in the included study population, the SPiN outcome could be predicted only based on the factor age.

Tone Decay Reconsidered: Preliminary Results of a Prospective Study in Hearing-Aid Users with Moderate to Severe Hearing Loss

Among hearing aid (HA) users, there is a considerable variability in word recognition scores (WRSs). This variability is most pronounced among individuals with moderately severe to severe hearing loss. The variability cannot be adequately explained by factors such as pure-tone audiogram, audiogram type or age. This prospective study was designed to investigate the relationship between tone decay (TD) and WRS in a group of HA users with corresponding pure-tone hearing loss. The study population included 22 patients with hearing loss between 50 and 80 dB HL. Aided WRS, unaided WRS and TD were assessed for both ears. TD was found to be frequency-dependent. TD and WRS were correlated, with up to R = -0.66. The TD test was revealed to be a feasible method for explaining variability in WRS among HA users with hearing loss below 80 dB. This may contribute to improved differential diagnostics. The TD test may thus offer a better understanding of the limitations of HA use in the context of cochlear implant candidacy assessment for HA users.

Prevalence and Characteristics of Veterans with Severe Hearing Loss: A Descriptive Study

Hearing loss is common among Veterans, and extensive hearing care resources are prioritized within the Veterans Administration (VA). Severe hearing loss poses unique communication challenges with speech understanding that may not be overcome with amplification. We analyzed data from the VA Audiometric Repository between 2005 and 2017 and the relationship between hearing loss severity with speech recognition scores. We hypothesized that a significant subset of Veterans with severe or worse hearing loss would have poor unaided speech perception outcomes even with adequate audibility. Sociodemographic characteristics and comorbidities were compiled using electronic medical records as was self-report measures of hearing disability. We identified a cohort of 137,500 unique Veterans with 232,789 audiograms demonstrating bilateral severe or worse hearing loss (four-frequency PTA > 70 dB HL). The median (IQR; range) age of Veterans at their first audiogram with severe or worse hearing loss was 81 years (74 to 87; 21-90+), and a majority were male (136,087 [99%]) and non-Hispanic white (107,798 [78.4%]). Among those with bilateral severe or worse hearing loss, 41,901 (30.5%) also had poor speech recognition scores (<50% words), with greater hearing loss severity correlating with worse speech perception. We observed variability in speech perception abilities in those with moderate-severe and greater levels of hearing loss who may derive limited benefit from amplification. Veterans with communication challenges may warrant alternative approaches and treatment strategies such as cochlear implants to support communication needs.

Evolving a Model for Cochlear Implant Outcome

BACKGROUND

Cochlear implantation is an efficient treatment for postlingually deafened adults who do not benefit sufficiently from acoustic amplification. Implantation is indicated when it can be foreseen that speech recognition with a cochlear implant (CI) is superior to that with a hearing aid. Especially for subjects with residual speech recognition, it is desirable to predict CI outcome on the basis of preoperative audiological tests.

PURPOSE

The purpose of the study was to extend and refine a previously developed model for CI outcome prediction for subjects with preoperative word recognition to include subjects with no residual hearing by incorporating additional results of routine examinations.

RESULTS

By introducing the duration of unaided hearing loss (DuHL), the median absolute error (MAE) of the prediction was reduced. While for subjects with preoperative speech recognition, the model modification did not change the MAE, for subjects with no residual speech recognition before surgery, the MAE decreased from 23.7% with the previous model to 17.2% with the extended model.

CONCLUSIONS

Prediction of word recognition with CI is possible within clinically relevant limits. Outcome prediction is particularly important for preoperative counseling and in CI aftercare to support systematic monitoring of CI fitting.

A flexible data-driven audiological patient stratification method for deriving auditory profiles

For characterizing the complexity of hearing deficits, it is important to consider different aspects of auditory functioning in addition to the audiogram. For this purpose, extensive test batteries have been developed aiming to cover all relevant aspects as defined by experts or model assumptions. However, as the assessment time of physicians is limited, such test batteries are often not used in clinical practice. Instead, fewer measures are used, which vary across clinics. This study aimed at proposing a flexible data-driven approach for characterizing distinct patient groups (patient stratification into auditory profiles) based on one prototypical database (N = 595) containing audiogram data, loudness scaling, speech tests, and anamnesis questions. To further maintain the applicability of the auditory profiles in clinical routine, we built random forest classification models based on a reduced set of audiological measures which are often available in clinics. Different parameterizations regarding binarization strategy, cross-validation procedure, and evaluation metric were compared to determine the optimum classification model. Our data-driven approach, involving model-based clustering, resulted in a set of 13 patient groups, which serve as auditory profiles. The 13 auditory profiles separate patients within certain ranges across audiological measures and are audiologically plausible. Both a normal hearing profile and profiles with varying extents of hearing impairments are defined. Further, a random forest classification model with a combination of a one-vs.-all and one-vs.-one binarization strategy, 10-fold cross-validation, and the kappa evaluation metric was determined as the optimal model. With the selected model, patients can be classified into 12 of the 13 auditory profiles with adequate precision (mean across profiles = 0.9) and sensitivity (mean across profiles = 0.84). The proposed approach, consequently, allows generating of audiologically plausible and interpretable, data-driven clinical auditory profiles, providing an efficient way of characterizing hearing deficits, while maintaining clinical applicability. The method should by design be applicable to all audiological data sets from clinics or research, and in addition be flexible to summarize information across databases by means of profiles, as well as to expand the approach toward aided measurements, fitting parameters, and further information from databases.

Effects of demographic, audiologic, and hearing-aid-related variables on the outcomes of using hearing aids

PURPOSE

To examine the influence of demographic, audiologic, and hearing-aid (HA)-related variables on HA outcomes.

METHODS

In total, 235 adults with hearing loss (HL) who used HAs for at least 3 months were included in the study, and completed audiologic tests and the Chinese version of the International Outcome Inventory for Hearing Aids (IOI-HA). Spearman correlation analysis and Wilcoxon test were conducted to identify factors related to IOI-HA overall and subscales scores. Stepwise multiple linear regression analysis was subsequently performed to determine the influence of factors on HA outcomes.

RESULTS

Age, daily use time, HA price, pure tone average (PTA) threshold, word recognition score (WRS), fitting (bilateral or unilateral), and HA style were associated with IOI-HA overall and subscales scores. However, only WRS, daily HA use time, HA price, and age entered the final regression model and were factors determining HA outcomes.

CONCLUSIONS

HA outcome is a multi-dimensional construct. In this study, WRS had the greatest influence on HA outcomes and seemed to be a primary predictor. Thus, HA owners with a higher WRS before HA fitting may indicate better satisfaction. Daily use time, HA price, and patient age also made significant contributions to HA outcomes and should be considered in clinical practice to facilitate auditory rehabilitation.

Objective and Subjective Outcomes in Patients with Hearing Aids: A Cross-Sectional, Comparative, Associational Study

INTRODUCTION

Outcome assessment for hearing aids (HAs) is an essential part of HA fitting and validation. There is no consensus about the best or standard approach for evaluating HA outcomes. And, the relationship between objective and subjective measures is ambiguous. This study aimed to determine the outcomes after HA fitting, explore correlations between subjective benefit and acoustic gain improvement as well as objective audiologic tests, and investigate several variables that may improve patients' perceived benefits.

METHODS

Eighty adults with bilateral symmetrical hearing loss using HAs for at least 1 month were included in this study. All subjects completed the pure tone average (PTA) threshold and word recognition score (WRS) tests in unaided and aided conditions. We also administered the Chinese version of International Outcome Inventory for Hearing Aids (IOI-HA), to measure participants' subjective benefits. Objective HA benefit (acoustic gain improvement) was defined as the difference in thresholds or scores between aided and unaided conditions indicated with ΔPTA and ΔWRS. Thus, patients' baseline hearing levels were taken into account. Correlations were assessed among objective audiologic tests (PTA and WRS), acoustic gain improvement (ΔPTA and ΔWRS), multiple potential factors, and IOI-HA overall scores.

RESULTS

PTA decreased significantly, but WRS did not increase when aided listening was compared to unaided listening. Negative correlations between PTAs and IOI-HA scores were significant but weak (r = -0.370 and r = -0.393, all p < 0.05). Significant weak positive correlations were found between WRSs and IOI-HA (r = 0.386 and r = 0.309, all p < 0.05). However, there was no correlation among ΔPTA, ΔWRS, and IOI-HA (r = 0.056 and r = -0.086, all p > 0.05). Moreover, 2 nonaudiological factors (age and daily use time) were significantly correlated with IOI-HA (r = -0.269 and r = 0.242, all p < 0.05).

CONCLUSIONS

Correlations among objective audiologic tests, acoustic gain, and subjective patient-reported outcomes were weak or absent. Subjective questionnaires and objective tests do not reflect the same hearing capability. Therefore, it is advisable to evaluate both objective and subjective outcomes when analyzing HA benefits on a regular basis and pay equal attention to nonaudiological and audiological factors.

Cochlear Implantation in Candidates With Moderate-to-Severe Hearing Loss and Poor Speech Perception

OBJECTIVES/HYPOTHESIS

To determine the improvement in word recognition score (WRS65 ) after cochlear implant (CI) surgery in hearing aid (HA) users with preoperative hearing threshold ≤80 dB HL and inadequate speech recognition scores with HA. Secondarily, to identify predictive factors for WRS65 with a CI (WRS65 [CI]) 6 months after surgery, derived from the standard German CI preoperative assessment.

STUDY DESIGN

Retrospective chart review.

METHODS

Retrospective review of all adult patients who received a Nucleus cochlear implant in the ear, nose, and throat department of the University Hospital of Erlangen between January 2010 and April 2019. The inclusion criteria were a preoperative hearing threshold ≤80 dB HL in the ear to receive the implantation, German as the native language, and at least 6 months postimplantation care at our center.

RESULTS

The inclusion criteria were met by 128 patients. All but two patients (98.4%) showed a significant improvement, WRS65 (CI) versus WRS65 with an (HA) (WRS65 [HA]), of at least 15 percentage points (pp). The median improvement was 55 pp with a median WRS65 (CI) of 70%. Three preoperative audiometric measures, the maximum word recognition score, age at implantation, and WRS65 (HA) were identified as predictive factors for WRS65 (CI). For three-quarters of the CI recipients, the score was not poorer than 12 pp below the predicted WRS65 (CI).

CONCLUSIONS

For patients with a hearing loss ≤80 dB HL, cochlear implantation should be considered when speech perception with an HA is insufficient. The prediction model can support counseling in this patient group.

LEVEL OF EVIDENCE

4 Laryngoscope, 131:E940-E945, 2021.