Investigation of Maximum Monosyllabic Word Recognition as a Predictor of Speech Understanding with Cochlear Implant

Abstract

Background: The cochlear implant (CI) is an established treatment option for patients with inadequate speech understanding and insufficient aided scores. Nevertheless, reliable predictive models and specific therapy goals regarding achievable speech understanding are still lacking. Method: In this retrospective study, 601 cases of CI fittings between 2005 and 2021 at the University Medical Center Freiburg were analyzed. We investigated the preoperative unaided maximum word recognition score (mWRS) as a minimum predictor for post-interventional scores at 65 dB SPL, WRS₆₅(CI). The WRS₆₅(CI) was compared with the preoperative-aided WRS, and a previously published prediction model for the WRS₆₅(CI) was reviewed. Furthermore, the effect of duration of hearing loss, duration of HA fitting, and etiology on WRS₆₅(CI) were investigated. Results: In 95.5% of the cases, a significant improvement in word recognition was observed after CI. WRS₆₅(CI) achieved or exceeded mWRS in 97% of cases. Etiology had a significant impact on WRS₆₅(CI). The predicted score was missed by more than 20 percentage points in 12.8% of cases. Discussion: Our results confirmed the minimum prediction via mWRS. A more precise prediction of the expected WRS₆₅(CI) is possible. The etiology of hearing loss should be considered in the indication and postoperative care to achieve optimal results.

Keywords: cochlear implant; hearing aid; hearing loss; maximum word recognition; speech audiometry; word recognition.

Figure 1

Distribution of etiologies of hearing loss.

Figure 2

Patient characteristics. (a) Distribution of duration of hearing loss. (b) Distribution of duration of unaided hearing loss. (c) Distribution of age at cochlear implantation.

Figure 3

Scatterplots of pre- and postoperative word recognition in relation to different preoperative measurements. (a) Four-frequency pure-tone average, 4PTA, versus mWRS; (b) 4PTA versus WRS₆₅(HA). (c) Preoperative mWRS versus WRS₆₅(HA). The boundaries around the bisectors represent the critical differences, according to Winkler and Holube [20]. Points outside these limits can be interpreted as significant differences in the respective values.

Figure 4

Scatterplots of postoperative word recognition in relation to preoperative measurements. (a) Postoperative WRS₆₅(CI) versus preoperative four-frequency pure-tone average, 4PTA. (b) WRS₆₅(CI) versus preoperative WRS₆₅(HA). (c) WRS₆₅(CI) versus preoperative mWRS. The boundaries around the bisectors represent the critical differences, according to Winkler and Holube [20]. Points outside these limits can be interpreted as significant differences in the respective values.

Figure 5

Box-whisker plots of WRS₆₅(CI) for different etiologies of hearing loss. The order of the plots is based on the ascending median values from left to right. The density and dispersion of the data points demonstrate the frequency of each etiology and the distribution of postoperative outcomes. Data points represent individual ears. * represents p < 0.05, ** represents p < 0.01 and *** represents p < 0.001.

Figure 6

Frequency distribution of the differences between measured and predicted WRS₆₅(CI) based on Equation (1). In all cases with negative values, the prediction was not achieved.