ObjectiveTo investigate the effect of distortion product otoacoustic emission (DPOAE) in hearing assessment for children with mumps, by comparing the results of DPOAE and auditory brainstem response (ABR) threshold value examination. MethodsA total of 116 children (232 ears) with mumps and 50 healthy children (100 ears) without mumps received DPOAE and ABR threshold value examination between March 2010 and October 2012. The results of these two examinations were compared in the first place. Then, The passing rate of DPOAE and the normal rate of ABR were compared between the two groups. ResultsThe passing rate in the mumps group was significantly lower than that in the control group[94.83% (220/232), 100.00% (232/232); P<0.05]. The pure tone test of 6 children (12 ears) in the mumps group who did not pass the DPOAE screening test showed that they had slight or moderate hearing loss. The ABR hearing thresholds of all children were normal. No significant difference was detected in Ⅲ wave latency, Ⅰ-Ⅲ and Ⅲ-Ⅴ intervals based on 75 dB nHL (P>0.05). However, there was a significant difference in the latency of I wave, V wave and interval between Ⅰ and Ⅴ between the two groups (P<0.05). The normal rate of ABR was significantly higher than the passing rate of DPOAE in the mumps group (P<0.05). ConclusionThe hearing is normal in all mumps children. However, mumps virus infection can affect the function of the eighth nerve and some auditory nuclei in the brainstem. Although DPOAE can be a useful method for hearing assessment in the mumps children, other hearing tests including ABR should also be considered.
Multilevel models are applicable to both the quantitative data and categorical variables. We used the methods, including the multilevel models, analysis of covariance and CMH chi-square test, to analyse different types of data, to explore the application of multilevel models in the analysis of the multicenter clinical trial center effect. The results showed that the analysis of covariance is more sensitive to find the center effect for quantitative data, while multilevel models are more sensitive to categorical variables. It can be seen that results with different analytical methods for center effect are not the same, and the most appropriate method should be selected in accordance with the characteristics of data, the objective of research, and the applicable conditions of the various methods in practical use.