Year: 2025
Type: article
Study design: Observational Study
Abstract: Background/Objectives: Cochlear implantation (CI) is a transformative intervention for individuals with sensorineural hearing loss, providing auditory and speech perception improvements. Traditional CI activation occurs 4–6 weeks post-surgery; however, recent advancements allow for early activation within 1–2 days. The integration of data logging in modern CI systems offers objective insights into processor usage and auditory exposure, which are crucial for optimizing rehabilitation outcomes. Methods: A retrospective study was conducted on 63 patients with bilateral simultaneous CIs using MED-EL SONNET2/RONDO3 devices. Patients were classified into early activation (n = 30, activation within 1–2 days) and classical activation groups (n = 33, activation after day 2). Data logging metrics, patient demographics, and implant details were analyzed using the Wilcoxon rank-sum test and Poisson regression. Results: Daily processor usage did not significantly differ between groups (9.5 ± 3.0 h/day for classical vs. 9.4 ± 3.7 h/day for early activation, p = 0.927). Subgroup analysis showed a significant 18% increase in processor usage with each additional year of patient age (IRR = 1.18, p < 0.001) and a 15% decrease in usage with each year delay in implantation age (IRR = 0.85, p < 0.001) among early activation users. Switch-on frequencies were comparable between groups, with no significant differences observed (p = 1.0). Conclusions: Early activation is feasible and associated with consistent CI usage, providing potential benefits in auditory rehabilitation. Future research should explore its impact on long-term speech and language outcomes to inform evidence-based practices.
Source: Journal of Clinical Medicine
DOI: 10.3390/jcm14030961
Institutions: King Saud Medical City, King Saud University
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,137
Funder: King Saud University
OpenAlex ID: W4407141166
