Factors influencing rehabilitation effect in prelingually deafened late‐implanted cochlear implant users, and the construction of a nomogram. (15th October 2021)

• Record Type: Journal Article
• Authors: Liu, Riyuan; Wang, Qian; Jiao, Qingshan; Ji, Fei; Zhao, Hui; Li, Jianan; Yang, Shiming
• Is Part Of: Clinical otolaryngology. Volume 47:Number 1(2022)
• Page Start: 61
• Page End: 66
• Publication Date: 2021-10-15
• Subjects: cochlear implant -- nomogram -- prelingually deafened late‐implanted cochlear implant user -- rehabilitation; Otolaryngology -- Periodicals; 617.51005
• DOI: 10.1111/coa.13848
• Languages: English
• ISSNs: 1749-4478

Abstract

Abstract: Objectives: Our study aimed to identify potential factors that may influence rehabilitation outcomes in late‐implanted adolescents and adults with prelingual deafness and to construct a user‐friendly nomogram. Design: This cross‐sectional study included 120 subjects under 30 years of age who had received cochlear implantation at a single medical centre. The Categories of Auditory Performance (CAP) scale was used to evaluate the rehabilitation outcomes. A nomogram was constructed by using the R and EmpowerStats software. Results: Univariate analysis indicated higher rates of auditory performance improvement in younger aged subjects. Residual hearing and regular implant use were more frequently seen among subjects with auditory performance improvement. Multivariate analysis identified residual hearing (Hazard Ratio, 6.11; 95% Confidence Interval, 1.83–20.41; p < .01), age group (Hazard Ratio, 0.31; 95% Confidence Interval, 0.14–0.83; p = .02) and regular CI use (Hazard Ratio, 7.79; 95% Confidence Interval, 2.50–24.20; p < .01) as independent predictors for auditory performance improvement. The nomogram's predictive performance was satisfactory as shown by the calibration curve and receiver operating characteristic (ROC) curve. Conclusions: Factors such as residual hearing, younger age and regular CI use are associated with auditory performance improvement in this cochlear implant user population. The nomogram model also demonstrates a satisfactory predictive performance.