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Objectives: The growing adoption of cochlear implants (CIs) necessitates understanding the factors influencing long-term performance and improved outcomes. This work investigated the long-term effect of early activation of CIs on electrode impedance in a large sample of CI users at different time points. Methods: A retrospective study on 915 ears from CI patients who were implanted between 2015 and 2020. According to their CI audio processor activation time, the patients were categorized into early activation (activated 1 day after surgery, n = 481) and classical activation (activated 4 weeks after surgery, n = 434) groups. Then, the impact of the activation times on the electrode impedance values, along the electrode array contacts, at different time points up to two years was studied and analyzed. Results: The early activation group demonstrated lower impedance values across all the electrode array sections compared to the classical activation at 1 month, 1 year, and 2 years post-implantation. At 1 month, early activation was associated with a reduction of 0.34 kΩ, 0.46 kΩ, and 0.37 kΩ in the apical, middle, and basal sections, respectively. These differences persisted at subsequent intervals. Conclusions: Early activation leads to sustained reductions in the electrode impedance compared to classical activation (CA), suggesting that earlier activation might positively affect long-term CI outcomes. [ABSTRACT FROM AUTHOR]

Cochlear implantation is the common treatment for severe to profound sensorineural hearing loss if there is no benefit from hearing aids. Measuring the electrode impedance along the electrode array at different time points after surgery is crucial in verifying the electrodes' status, determining the compliance levels, and helping to identify the electric dynamic range. Increased impedance values without proper reprogramming can affect the patient's performance. The prediction of acceptable levels of electrode impedance at different time points after the surgery could help clinicians during the fitting sessions through a comparison of the predicted with the measured levels. Accordingly, clinicians can decide if the measured levels are within the predicted normal range or not. In this work, we used a dataset of 80 pediatric patients who had received cochlear implants with the MED-EL FLEX 28 electrode array. We predicted the impedance of the electrode arrays in each channel at different time points: at one month, three months, six months, and one year after the date of surgery. We used different machine learning algorithms such as linear regression, Bayesian linear regression, decision forest regression, boosted decision tree regression, and neural networks. The used features include the patient's age and the intra-operative electrode impedance at different electrodes. Our results indicated that the best algorithm varies depending on the channel, while the Bayesian linear regression and neural networks provide the best results for 75% of the channels. Furthermore, the accuracy level ranges between 83% and 100% in half of the channels one year after the surgery, when an error range between 0 and 3 KΩ is defined as an acceptable threshold. Moreover, the use of the patient's age alone can provide the best prediction results for 50% of the channels at six months or one year after surgery. This reflects that the patient's age could be a predictor of the electrode impedance after the surgery. [ABSTRACT FROM AUTHOR]

Objectives/hypothesis: This study aimed to compare the predicted anatomy‐based frequency allocation of cochlear implant electrodes with the default standard frequencies. Study Design: Retrospective study. Methods: A retrospective analysis was performed using computed tomography (CT) images of patients who received cochlear implants at a tertiary referral center. Patients were excluded if they had any congenital or acquired cochlear anatomical anomalies. The CT images of the patients were uploaded to the surgical planning software. Two independent reviewers allocated the anatomical parameters of the cochlea. The software then used these parameters to calculate the frequency allocation for each electrode according to the type of electrode and the length of the organ of Corti (OC) in each patient. These anatomy‐based frequency allocations were compared with the default frequency settings. Main Outcome Measure: Frequency‐to‐place mismatch in semitones. Results: A total of 169 implanted ears in 102 patients were included in this study. The readings of the two reviewers were homogenous, with a Cronbach's alpha of 0.98. The mean anatomy‐based frequency allocation was 487.3 ± 202.9 Hz in electrode 1; 9,298.6 ± 490.6 Hz in electrode 12. The anatomy‐based frequency allocations were found to be significantly higher than the frequencies of the default frequencies for each corresponding electrode (one‐sample t‐test, P <.001). The frequency‐to‐place mismatch was negatively correlated with cochlear coverage and positively correlated with the cochlear duct length (Pearson correlation > 0.65, P <.003). Conclusions: The anatomy‐based frequency allocation of each electrode is significantly different from the default frequency setting. This frequency‐to‐place mismatch was affected mainly by the cochlear coverage. Level of Evidence: 3 Laryngoscope, 132:2224–2231, 2022 [ABSTRACT FROM AUTHOR]