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Dive into the research topics where Christopher K. Giardina is active.

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Featured researches published by Christopher K. Giardina.


Laryngoscope | 2016

Round window electrocochleography before and after cochlear implant electrode insertion

Oliver F. Adunka; Christopher K. Giardina; Eric J. Formeister; Baishakhi Choudhury; Craig A. Buchman; Douglas C. Fitzpatrick

Previous reports have documented the feasibility of utilizing electrocochleographic (ECoG) responses to acoustic signals to assess trauma caused during cochlear implantation. The hypothesis is that intraoperative round window ECoG before and after electrode insertion will help predict postoperative hearing preservation outcomes in cochlear implant recipients.


Otology & Neurotology | 2016

The Compound Action Potential in Subjects Receiving a Cochlear Implant.

William C. Scott; Christopher K. Giardina; Andrew K. Pappa; Tatyana E. Fontenot; Meredith L. Anderson; Margaret T. Dillon; Kevin D. Brown; Harold C. Pillsbury; Oliver F. Adunka; Craig A. Buchman; Douglas C. Fitzpatrick

Hypothesis: The compound action potential (CAP) is a purely neural component of the cochleas response to sound, and may provide information regarding the existing neural substrate in cochlear implant (CI) subjects that can help account for variance in speech perception outcomes. Background: Measurement of the “total response” (TR), or sum of the magnitudes of spectral components in the ongoing responses to tone bursts across frequencies, has been shown to account for 40 to 50% of variance in speech perception outcomes. The ongoing response is composed of both hair cell and neural components. This correlation may be improved with the addition of the CAP. Methods: Intraoperative round window electrocochleography (ECochG) was performed in adult and pediatric CI subjects (n = 238). Stimuli were tones of different frequencies (250 Hz–4 kHz) at 90 dB nHL. The CAP was assessed in two ways, as an amplitude and with a scaling factor derived from a function fitted to the response. The results were correlated with consonant-nucleus-consonant (CNC) word scores at 6 months post-implantation (n = 51). Results: Only about half of the subjects had a measurable CAP at any frequency. The CNC word scores correlated weakly with both amplitude (r2 = 0.20, p < 0.001) and scaling factor (r2 = 0.25, p < 0.01). In contrast, the TR alone accounted for 43% of the variance, and addition of either CAP measurement in multiple regression did not account for additional variance. Conclusions: The underlying pathology in CI patients causes the CAP to be often absent and highly variable when present. The TR is a better predictor of speech perception outcomes than the CAP.


Frontiers in Neuroscience | 2017

Intraoperative electrocochleographic characteristics of auditory neuropathy spectrum disorder in cochlear implant subjects

William J. Riggs; Joseph P. Roche; Christopher K. Giardina; Michael S. Harris; Zachary J. Bastian; Tatyana E. Fontenot; Craig A. Buchman; Kevin D. Brown; Oliver F. Adunka; Douglas C. Fitzpatrick

Auditory neuropathy spectrum disorder (ANSD) is characterized by an apparent discrepancy between measures of cochlear and neural function based on auditory brainstem response (ABR) testing. Clinical indicators of ANSD are a present cochlear microphonic (CM) with small or absent wave V. Many identified ANSD patients have speech impairment severe enough that cochlear implantation (CI) is indicated. To better understand the cochleae identified with ANSD that lead to a CI, we performed intraoperative round window electrocochleography (ECochG) to tone bursts in children (n = 167) and adults (n = 163). Magnitudes of the responses to tones of different frequencies were summed to measure the “total response” (ECochG-TR), a metric often dominated by hair cell activity, and auditory nerve activity was estimated visually from the compound action potential (CAP) and auditory nerve neurophonic (ANN) as a ranked “Nerve Score”. Subjects identified as ANSD (45 ears in children, 3 in adults) had higher values of ECochG-TR than adult and pediatric subjects also receiving CIs not identified as ANSD. However, nerve scores of the ANSD group were similar to the other cohorts, although dominated by the ANN to low frequencies more than in the non-ANSD groups. To high frequencies, the common morphology of ANSD cases was a large CM and summating potential, and small or absent CAP. Common morphologies in other groups were either only a CM, or a combination of CM and CAP. These results indicate that responses to high frequencies, derived primarily from hair cells, are the main source of the CM used to evaluate ANSD in the clinical setting. However, the clinical tests do not capture the wide range of neural activity seen to low frequency sounds.


Current Surgery Reports | 2014

Cochlear Implants in Single-Sided Deafness

Christopher K. Giardina; Eric J. Formeister; Oliver F. Adunka

Single-sided deafness presents a unique challenge to otolaryngologists and audiologists. While the normal hearing ear may allow listeners to perform adequately on audiometric screening, individuals with only one functioning cochlea suffer when resolving speech in noisy environments and in sound localization—which both contribute to a reduced quality of life. Though there are a variety of strategies that provide contralateral routing of sound signals, the cochlear implant is the only treatment to truly restore binaural hearing. Only very recently has cochlear implantation (CI) for single-sided deafness begun in earnest, with encouraging results that demonstrate the strengths and pitfalls of implantation over traditional extracochlear methods. The purpose of this review is to update the field by emphasizing binaural benefits, discussing historical treatments of single-sided deafness, critically evaluating recent data on outcomes of CI for single-sided deafness, and recommending indications for cochlear implants in single-sided deafness in children, adults, and subjects with concurrent ipsilateral tinnitus.


Frontiers in Neuroscience | 2017

A Model-Based Approach for Separating the Cochlear Microphonic from the Auditory Nerve Neurophonic in the Ongoing Response Using Electrocochleography

Tatyana E. Fontenot; Christopher K. Giardina; Douglas C. Fitzpatrick

Electrocochleography (ECochG) is a potential clinically valuable technique for predicting speech perception outcomes in cochlear implant (CI) recipients, among other uses. Current analysis is limited by an inability to quantify hair cell and neural contributions which are mixed in the ongoing part of the response to low frequency tones. Here, we used a model based on source properties to account for recorded waveform shapes and to separate the combined signal into its components. The model for the cochlear microphonic (CM) was a sinusoid with parameters for independent saturation of the peaks and the troughs of the responses. The model for the auditory nerve neurophonic (ANN) was the convolution of a unit potential and population cycle histogram with a parameter for spread of excitation. Phases of the ANN and CM were additional parameters. The average cycle from the ongoing response was the input, and adaptive fitting identified CM and ANN parameters that best reproduced the waveform shape. Test datasets were responses recorded from the round windows of CI recipients, from the round window of gerbils before and after application of neurotoxins, and with simulated signals where each parameter could be manipulated in isolation. Waveforms recorded from 284 CI recipients had a variety of morphologies that the model fit with an average r2 of 0.97 ± 0.058 (standard deviation). With simulated signals, small systematic differences between outputs and inputs were seen with some variable combinations, but in general there were limited interactions among the parameters. In gerbils, the CM reported was relatively unaffected by the neurotoxins. In contrast, the ANN was strongly reduced and the reduction was limited to frequencies of 1,000 Hz and lower, consistent with the range of strong neural phase-locking. Across human CI subjects, the ANN contribution was variable, ranging from nearly none to larger than the CM. Development of this model could provide a means to isolate hair cell and neural activity that are mixed in the ongoing response to low-frequency tones. This tool can help characterize the residual physiology across CI subjects, and can be useful in other clinical settings where a description of the cochlear physiology is desirable.


IEEE Transactions on Biomedical Engineering | 2018

Impedance Measures During in vitro Cochlear Implantation Predict Array Positioning

Christopher K. Giardina; Elliot Samuel Krause; Kanthaiah Koka; Douglas C. Fitzpatrick


Ear and Hearing | 2018

Residual Cochlear Function in Adults and Children Receiving Cochlear Implants: Correlations With Speech Perception Outcomes

Tatyana E. Fontenot; Christopher K. Giardina; Megan T. Dillon; Meredith A. Rooth; Holly F. B. Teagle; Lisa R. Park; Kevin D. Brown; Oliver F. Adunka; Craig A. Buchman; Harold C. Pillsbury; Douglas C. Fitzpatrick


Ear and Hearing | 2018

Intracochlear Electrocochleography: Response Patterns During Cochlear Implantation and Hearing Preservation

Christopher K. Giardina; Kevin D. Brown; Oliver F. Adunka; Craig A. Buchman; Kendall A. Hutson; Harold C. Pillsbury; Douglas C. Fitzpatrick


Ear and Hearing | 2018

Response Changes During Insertion of a Cochlear Implant Using Extracochlear Electrocochleography

Christopher K. Giardina; Tatyana E. Khan; Stephen H. Pulver; Oliver F. Adunka; Craig A. Buchman; Kevin D. Brown; Harold C. Pillsbury; Douglas C. Fitzpatrick


Otology & Neurotology | 2017

Patterns seen during electrode insertion using intracochlear electrocochleography obtained directly through a cochlear implant

Michael S. Harris; William J. Riggs; Christopher K. Giardina; Brendan P. O'Connell; Jourdan T. Holder; Robert T. Dwyer; Kanthaiah Koka; Robert F. Labadie; Douglas C. Fitzpatrick; Oliver F. Adunka

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Douglas C. Fitzpatrick

University of North Carolina at Chapel Hill

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Craig A. Buchman

Washington University in St. Louis

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Kevin D. Brown

University of North Carolina at Chapel Hill

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Tatyana E. Fontenot

University of North Carolina at Chapel Hill

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Harold C. Pillsbury

University of North Carolina at Chapel Hill

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Eric J. Formeister

University of North Carolina at Chapel Hill

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Holly F. B. Teagle

University of North Carolina at Chapel Hill

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Kanthaiah Koka

University of Colorado Denver

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Lisa R. Park

University of North Carolina at Chapel Hill

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