Results from Arm 1 participants were included in a one-way repeated measures ANOVA to determine whether there was a statistically significant change in CNC word scores or Baby Bio scores at +5 dB SNR from pre- to postoperative listening programs. For the first analysis, CNC word scores in rau were compared for each program (preoperative HA, postoperative EAS, and FE). Mean scores in rau were 24.89 (SD = 14.31) when measured preoperatively with an HA, 37.21 (SD = 13.58) with the FE program, and 61.67 (SD = 14.02) with the EAS program. There was a significant effect of time point, F(2,16) = 18.606; p < 0.001; partial η2 = 0.699. Post hoc analysis revealed that CNC rau scores did increase significantly from the preoperative HA condition when measured with EAS (M = 36.77; 95% confidence interval, 13.52, 60.03; p = 0.004), but not when measured with FE programs (M = 12.32; 95% confidence interval, −4.30, 28.94; p = 0.167). A second analysis compared scores obtained in each program on the Baby Bio in noise test. Mean rau scores were 19.39 (SD = 44.92) when measured preoperatively with an HA, 41.25 (SD = 26.93) with FE, and 67.23 (SD = 31.39) with EAS. Taking a Greenhouse-Geisser correction into account, there was a significant effect of time point, F(1.187,9.497) = 8.589; p = 0.013; partial η2 = 0.518. Post hoc analysis indicated that the increase in scores from listening with an HA to an EAS program was statistically significant (M = 47.84; 95% confidence interval, 9.028, 86.658; p = 0.018). Despite more a more than two-fold increase in scores, there was no significant difference between the HA and FE programs (M = 21.86; 95% confidence interval, −21.758, 65.472; p = 0.507). Results are presented in Figure 4.
A Spearman rank-order correlation was again used to analyze secondary factors of age at implantation and length of device use between difference scores. For these analyses, scores obtained preoperatively with an HA were subtracted from those obtained with the EAS program. There was no correlation between the difference in scores for CNC words or the Baby Bio at a +5 dB SNR. Statistical data are listed in Table 3.
The scores obtained with the FE program were subtracted from the scores obtained with the EAS program for a difference score. Secondary factors of age at implantation, time since EAS fitting, and time since CI fitting were included in a Spearman rank-order correlation. There was no significant correlation to the difference score for any of these factors for either measure. Correlation and significance values can be found in Table 3.
In this study, children with residual hearing performed better on both single words in quiet and sentences in noise with EAS when compared with conventional FE programs. These findings are similar to those reported by Wolfe et al. (2017) who also found that children with residual hearing benefit from the use of EAS in noise; however, findings of the current study did reach statistical significance. In addition, the current study used FE programs rather than truncated electric maps, allowing access to a wider frequency spectrum. These results echo outcomes of many adult studies investigating unilateral EAS use as well (Gantz et al. 2005; Gstoettner et al. 2008; Adunka et al. 2010a; Adunka et al. 2013; Mahmoud et al. 2014; Sheffield et al. 2015; Pillsbury et al. 2018).
In general, however, the CNC word scores in the FE programs are rather low. As all but one participant in this group was a full-time user based on datalogging, the mean age of implant (9.89 years) is a concern. All of the children were born with some degree of hearing loss and over half of them were progressive. Often children with significant levels of residual hearing are not referred for implantation until professionals and caregivers feel that there is a plateau in language development or difficulty in school. It may be that these children were referred after an extended period of time listening to degraded input and would have had better outcomes if they had been implanted sooner. Unfortunately, the preoperative histories of this cohort are not enough to make a conclusion.
Low CNC word scores in the FE program is of concern for the participants in this Arm as well. Again, the mean age of implant (7.5 years) may be a factor. Many of these children were implanted when centers were just beginning to expand indications to include children with greater levels of residual hearing. They may have had poor word recognition and an extended period of time listening to degraded input before referral.
Overall, the current study provides evidence that children with residual hearing who have been wearing FE programs can adapt to EAS and benefit. Scholz et al. (2017) also fit EAS on children with long-term use of FE programs, but did not find statistical significance. The authors note the variability in outcomes within their group and the difficulty their subjects had with acceptance after 4 weeks of acclimatization time. Two of the Arm 2 subjects have opted to discontinue use of the acoustic component. Neither liked using the receiver in canal (RIC) device. One recognized the benefit but was not comfortable with dome or personal earmold fitting. The other was an exceptional performer with his FE program, and while he liked the sound quality, he and his parents did not feel the benefits outweighed the additional troubleshooting and care of the RIC. Other subjects have continued to use their acoustic component, and three of the four bimodal listeners in Arm 2 decided to become bilateral EAS users rather than bimodal listeners. All four bimodal users enrolled in Arm 1 have since received a second CI and are currently bilateral EAS users. Acceptance in this study seems to be greater than what was found by Scholz et al. (2017) and more closely aligned with findings by Wolfe et al. (2017).
This study did not concentrate on optimizing settings such as acoustic bandwidth, electric start frequencies, or acoustic fitting formula. Future studies should be designed to establish best practices for programming EAS in this special population. Optimal fittings of the RIC devices for smaller ears and ideal acoustic targets should be a focus. In the current study, DSL targets were used in order to ensure audibility soft and loud speech for children still developing language. In truth, DSL was designed for a full bandwidth of acoustic hearing, and children who are utilizing EAS are using acoustic information in a completely different way. They may require a specific pediatric EAS fitting formula that has yet to be developed.
Whether new implant recipients or long-term CI users, children with residual hearing should be afforded the opportunity to use EAS. In most cases, children with functional low-frequency hearing who may be able to benefit from a CI do not meet candidacy criteria under manufacturer labeling; however, this study supports consideration for implantation. Children with HAs who have residual hearing, but insufficient access to high-frequency sounds, should be considered for CI surgery and fit with EAS when hearing is preserved. The potential for improved speech understanding in quiet and in noise, as documented here, could increase the accessibility of spoken language. Higher speech perception scores in general are related to higher language function (Blamey et al. 2001; Desjardin et al. 2009; Davidson et al. 2011; Geers et al. 2013). Furthermore, children with CIs are known to have greater difficulty understanding in noise than children with HAs who have moderate to severe losses (Eisenberg et al. 2004). Combining acoustic and electric information through the use of EAS provides an improvement over FE stimulation, and better hearing in noise presents more opportunities for exposure to spoken language and incidental learning.
The authors wish to thank Dr. Emily Buss for her assistance with statistical analysis.
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