V J C Kraaijenga1,2, A L Smit3,4, I Stegeman3,4, J J M Smilde3, G A van Zanten3,4, W Grolman3,4. 1. Department of Otorhinolaryngology - Head and Neck Surgery, University Medical Center Utrecht, Utrecht, the Netherlands. ent-research@umcutrecht.nl. 2. Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands. ent-research@umcutrecht.nl. 3. Department of Otorhinolaryngology - Head and Neck Surgery, University Medical Center Utrecht, Utrecht, the Netherlands. 4. Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands.
Abstract
OBJECTIVE: Outcomes in speech perception following cochlear implantation in adults vary widely. Many studies have been carried out to identify and quantify factors that influence outcomes. This study adds a new dimension to pre-existing literature. DESIGN: Single-centre retrospective cohort study. SETTING: University Medical Center Utrecht, the Netherlands. PARTICIPANTS: A total of 428 adults with bilateral severe-to-profound sensorineural hearing loss, unilaterally implanted between February 1988 and March 2014. MAIN OUTCOME MEASURES: Univariable and multivariable linear regression analyses were carried out to identify factors that may influence outcome after cochlear implantation. Consonant-vowel-consonant word scores were recorded pre- and post-implant and were used as outcome measure in two groups of patients (prelingually and postlingually deafened adults). As an added dimension, multiple imputation was implemented and evaluated to tackle 4% (17/407) missing data. RESULTS: For postlinguals, pre-implant speech perception score and age at onset of deafness are positive predictors and meningitis and otosclerosis as cause of deafness are negative predictors of post-implant speech perception. This model accounted for 26% of variance. For prelinguals, pre-implant speech perception score is the only strong positive predictor (β 0.524; P < 0.001). This model accounted for 31% of variance. Age at implantation was not a significant predictor in either group. CONCLUSIONS: Speech perception is predicted by pre-implant speech perception, age at onset of deafness and aetiology (meningitis and otosclerosis) for postlinguals and solely pre-implant speech perception for prelinguals. Age at implantation is of lesser importance in predicting speech perception outcome post-implant. Multiple imputation is a useful statistical technique when analysing incomplete data sets.
OBJECTIVE: Outcomes in speech perception following cochlear implantation in adults vary widely. Many studies have been carried out to identify and quantify factors that influence outcomes. This study adds a new dimension to pre-existing literature. DESIGN: Single-centre retrospective cohort study. SETTING: University Medical Center Utrecht, the Netherlands. PARTICIPANTS: A total of 428 adults with bilateral severe-to-profound sensorineural hearing loss, unilaterally implanted between February 1988 and March 2014. MAIN OUTCOME MEASURES: Univariable and multivariable linear regression analyses were carried out to identify factors that may influence outcome after cochlear implantation. Consonant-vowel-consonant word scores were recorded pre- and post-implant and were used as outcome measure in two groups of patients (prelingually and postlingually deafened adults). As an added dimension, multiple imputation was implemented and evaluated to tackle 4% (17/407) missing data. RESULTS: For postlinguals, pre-implant speech perception score and age at onset of deafness are positive predictors and meningitis and otosclerosis as cause of deafness are negative predictors of post-implant speech perception. This model accounted for 26% of variance. For prelinguals, pre-implant speech perception score is the only strong positive predictor (β 0.524; P < 0.001). This model accounted for 31% of variance. Age at implantation was not a significant predictor in either group. CONCLUSIONS: Speech perception is predicted by pre-implant speech perception, age at onset of deafness and aetiology (meningitis and otosclerosis) for postlinguals and solely pre-implant speech perception for prelinguals. Age at implantation is of lesser importance in predicting speech perception outcome post-implant. Multiple imputation is a useful statistical technique when analysing incomplete data sets.
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