4 research outputs found
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Assessment of inter-examiner agreement and variability in the manual classification of auditory brainstem response
Abstract
Background: The analysis of the Auditory Brainstem Response (ABR) is of
fundamental importance to the investigation of the auditory system behaviour,
though its interpretation has a subjective nature because of the manual process
employed in its study and the clinical experience required for its analysis. When
analysing the ABR, clinicians are often interested in the identification of ABR signal
components referred to as Jewett waves. In particular, the detection and study of
the time when these waves occur (i.e., the wave latency) is a practical tool for the
diagnosis of disorders affecting the auditory system. Significant differences in
inter-examiner results may lead to completely distinct clinical interpretations of the
state of the auditory system. In this context, the aim of this research was to evaluate
the inter-examiner agreement and variability in the manual classification of ABR.
Methods: A total of 160 ABR data samples were collected, for four different stimulus
intensity (80dBHL, 60dBHL, 40dBHL and 20dBHL), from 10 normal-hearing subjects
(5 men and 5 women, from 20 to 52 years). Four examiners with expertise in the
manual classification of ABR components participated in the study. The Bland-Altman
statistical method was employed for the assessment of inter-examiner agreement
and variability. The mean, standard deviation and error for the bias, which is the
difference between examiners’ annotations, were estimated for each pair of
examiners. Scatter plots and histograms were employed for data visualization and
analysis.
Results: In most comparisons the differences between examiner’s annotations were
below 0.1 ms, which is clinically acceptable. In four cases, it was found a large error
and standard deviation (>0.1 ms) that indicate the presence of outliers and thus,
discrepancies between examiners.
Conclusions: Our results quantify the inter-examiner agreement and variability of
the manual analysis of ABR data, and they also allows for the determination of
different patterns of manual ABR analysis
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Analysis of the variability of auditory brainstem response components through linear regression
(ABR) is of fundamental importance to the investiga- tion of the auditory system behavior, though its in- terpretation has a subjective nature because of the manual process employed in its study and the clinical experience required for its analysis. When analyzing the ABR, clinicians are often interested in the identi- fication of ABR signal components referred to as Jewett waves. In particular, the detection and study of the time when these waves occur (i.e., the wave la- tency) is a practical tool for the diagnosis of disorders affecting the auditory system. In this context, the aim of this research is to compare ABR manual/visual analysis provided by different examiners. Methods: The ABR data were collected from 10 normal-hearing subjects (5 men and 5 women, from 20 to 52 years). A total of 160 data samples were analyzed and a pair- wise comparison between four distinct examiners was executed. We carried out a statistical study aiming to identify significant differences between assessments provided by the examiners. For this, we used Linear Regression in conjunction with Bootstrap, as a me- thod for evaluating the relation between the responses given by the examiners. Results: The analysis sug- gests agreement among examiners however reveals differences between assessments of the variability of the waves. We quantified the magnitude of the ob- tained wave latency differences and 18% of the inves- tigated waves presented substantial differences (large and moderate) and of these 3.79% were considered not acceptable for the clinical practice. Conclusions: Our results characterize the variability of the manual analysis of ABR data and the necessity of establishing unified standards and protocols for the analysis of these data. These results may also contribute to the
validation and development of automatic systems that are employed in the early diagnosis of hearing loss