Objective: Compare word recognition scores for adults undergoing cochlear implant evaluations (CIE) measured using earphones and hearing aids.
Study Design: Retrospective review of data obtained during adult CIEs.
Setting: Tertiary cochlear implant center.
Patients: Two hundred eight ears in 183 subjects with greater than 10% word recognition scores measured with earphones.
Interventions/main Outcomes Measured: Preoperative pure-tone thresholds and word recognition scores measured with earphones and hearing aids.
Results: A review of audiological data obtained from 2012 to 2017 during adult CIEs was conducted. Overall, a weak positive correlation (r = 0.33, 95% confidence interval 0.17-0.40, p < 0.001) was observed between word recognition scores measured with earphones and hearing aids. Earphone to aided differences (EAD) ranged from -38 to +72% (mean 14.3 ± 19.9%). Consistent with EADs, 108 ears (51.9%) had earphone scores that were significantly higher than aided word recognition scores (+EAD), as determined by 95% confidence intervals; for 14 ears (6.7%), earphone scores were significantly lower than aided scores (-EAD). Moreover, of the patients with earphone word recognition scores ≥50%, 82.6% were CI candidates based on aided AzBio+10 dB SNR scores.
Conclusion: These results demonstrate the limited diagnostic value of word recognition scores measured under earphones for patients undergoing CIE. Nevertheless, aided word recognition is rarely measured before CIEs, which limits the information available to determine CI candidacy and referral for CIEs. Earlier and routine measurement of aided word recognition may help guide clinical decision making by determining the extent to which patients are achieving maximum benefit with their hearing aids or should consider cochlear implantation.
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http://dx.doi.org/10.1097/MAO.0000000000001873 | DOI Listing |
Acta Otolaryngol
January 2025
Neuro-Otology, Department of Neurosurgery, SGPGIMS, Lucknow, Uttar Pradesh, India.
Background: Pediatric cochlear implant (CI) recipients with cochlear malformations face challenges due to variable speech recognition outcomes.
Aims/objectives: This study assesses the predictive value of intraoperative electrically evoked compound action potential (eCAP) thresholds, residual hearing, age at implantation, Intelligent Quotient (IQ), and malformation type for speech recognition outcomes.
Material And Methods: A prospective cohort of 52 children (aged 1-4 years) with cochlear malformations who underwent CI between 2016 and 2024 was analyzed.
Ear Hear
January 2025
Department of Otolaryngology/Head & Neck Surgery, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
Objectives: This study was designed to (1) compare preactivation and postactivation performance with a cochlear implant for children with functional preoperative low-frequency hearing, (2) compare outcomes of electric-acoustic stimulation (EAS) versus electric-only stimulation (ES) for children with versus without hearing preservation to understand the benefits of low-frequency acoustic cues, and (3) to investigate the relationship between postoperative acoustic hearing thresholds and performance.
Design: This was a prospective, 12-month between-subjects trial including 24 pediatric cochlear implant recipients with preoperative low-frequency functional hearing. Participant ages ranged from 5 to 17 years old.
Neuroscience
January 2025
Human Communication, Learning, and Development, Faculty of Education, The University of Hong Kong, China.
The human brain possesses the ability to automatically extract statistical regularities from environmental inputs, including visual-graphic symbols and printed units. However, the specific brain regions underlying the statistical learning of these visual-graphic symbols or artificial orthography remain unclear. This study utilized functional magnetic resonance imaging (fMRI) with an artificial orthography learning paradigm to measure brain activities associated with the statistical learning of radical positional regularities embedded in pseudocharacters containing high (100%), moderate (80%), and low (60%) levels of consistency, along with a series of random abstract figures.
View Article and Find Full Text PDFData Brief
February 2025
ADA University, Baku, Azerbaijan.
Advancements in sign language processing technology hinge on the availability of extensive, reliable datasets, comprehensive instructions, and adherence to ethical guidelines. To facilitate progress in gesture recognition and translation systems and to support the Azerbaijani sign language community we present the Azerbaijani Sign Language Dataset (AzSLD). This comprehensive dataset was collected from a diverse group of sign language users, encompassing a range of linguistic parameters.
View Article and Find Full Text PDFBehav Res Methods
January 2025
Stanford University Graduate School of Education, 520 Galvez Mall, Stanford, CA, 94305, USA.
The Rapid Online Assessment of Reading (ROAR) is a web-based lexical decision task that measures single-word reading abilities in children and adults without a proctor. Here we study whether item response theory (IRT) and computerized adaptive testing (CAT) can be used to create a more efficient online measure of word recognition. To construct an item bank, we first analyzed data taken from four groups of students (N = 1960) who differed in age, socioeconomic status, and language-based learning disabilities.
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