"Association of High Risk Factors and Hearing Impairment in Infants-A Hospital Based Study".

The aim of the study was to find the association of various risk factors with permanent hearing impairment in infants. A case-control study was designed on 420 infants with permanent hearing impairment and normal hearing. The case control ratio was 1:1. Alternate sampling method was used for selecting the control group. Review of medical records and parent interview was done to collect the information of risk factors. Family history(adj. OR 7.5; 95% CI 3, 14; P = 0.000), Consanguinity (adj. OR: 4; 95% CI 2,4; P = 0.000), intra uterine infection (adj. OR 18, 95% CI: 2.3-126.5, P = 0.000), post natal infection (adj. OR 3, 95% CI: 1.3-5, P = 0.004), low Apgar score (adj.OR: 4.6, 95% CI: 1.3-15), craniofacial anomaly (OR-4.6, 95% CI: 1.4-9.5, P = 0.005) and low birth weight (adj. OR: 2.3, 95% CI: 1.2-3.8) were significantly associated with hearing impairment. Among the risk factors, intra uterine infection was having highest significant association with permanent hearing impairment. This is followed by family history, low Apgar score, craniofacial anomaly, consanguinity, post natal infection and low birth weight.

A study of self-perception and communication success as perceived by adolescents with cochlear implants and their significant others.

OBJECTIVES: The objectives of this prospective, cross-sectional study were to compare self-perception and communication-success ratings of adolescents with cochlear implant (AWCI) and their caregivers (C-AWCI) and to explore associations with age at CI, implant age, and chronological age. METHOD: Fourteen CI centers across India participated. The Think About it Quiz (TAIQ), Self Assessment of Communication-Adolescent (SAC-A), and Significant Other Assessment of Communication-Adolescent (SOAC-A) were translated into five languages. Data were collected from 173 AWCI aged 10;0-19;6 years and an associated caregiver for each participant. RESULTS: On the TAIQ, self-ratings by AWCI were significantly lower than the ratings by C-AWCI. Peer acceptance correlated with athletic competence for both groups. For the SAC-A versus SOAC-A, there was no significant difference between AWCI and C-AWCI ratings. Except for a negative correlation between peer-acceptance and chronological age for caregiver ratings, no other associations were found between any other ratings and age at CI, implant age, and chronological age. CONCLUSIONS: Caregiver judgments of their adolescents with CI were not in equal agreement with self-ratings by the adolescents across various aspects of performance. Caregivers appeared to underestimate the self-perception issues faced by adolescents with CI but had excellent agreement with their adolescents' self-rating of communication success. The inclusion of activities to improve children's participation in sports could possibly improve peer acceptance.

Electrophysiological Correlates of Behavioral Comfort Levels in Cochlear Implantees: A Prospective Study.

Indications for cochlear implantation have expanded today to include very young children and those with syndromes/multiple handicaps. Programming the implant based on behavioral responses may be tedious for audiologists in such cases, wherein matching an effective MAP and appropriate MAP becomes the key issue in the habilitation program. In 'Difficult to MAP' scenarios, objective measures become paramount to predict optimal current levels to be set in the MAP. We aimed, (a) to study the trends in multi-modal electrophysiological tests and behavioral responses sequentially over the first year of implant use, (b) to generate normative data from the above, (c) to correlate the multi-modal electrophysiological thresholds levels with behavioral comfort levels, and (d) to create predictive formulae for deriving optimal comfort levels (if unknown), using linear and multiple regression analysis. This prospective study included ten profoundly hearing impaired children aged between 2 and 7 years with normal inner ear anatomy and no additional handicaps. They received the Advanced Bionics HiRes 90K Implant with Harmony Speech processor and used HiRes-P with Fidelity 120 strategy. They underwent, Impedance Telemetry, Neural Response Imaging, Electrically Evoked Stapedial Response Telemetry and Electrically Evoked Auditory Brainstem Response tests at 1, 4, 8 and 12 months of implant use, in conjunction with behavioral Mapping. Trends in electrophysiological and behavioral responses were analyzed using paired t test. By Karl Pearson's correlation method, electrode-wise correlations were derived for NRI thresholds versus Most Comfortable Levels (M-Levels) and offset based (apical, mid-array and basal array) correlations for EABR and ESRT thresholds versus M-Levels were calculated over time. These were used to derive predictive formulae by linear and multiple regression analysis. Such statistically predicted M-Levels were compared with the behaviorally recorded M-Levels among the cohort, using Cronbach's Alpha Reliability test method for confirming the efficacy of this method. NRI, ESRT and EABR thresholds showed statistically significant positive correlations with behavioral M-Levels, which improved with implant use over time. These correlations were used to derive predicted M-Levels using regression analysis. Such predicted M-Levels were found to be in proximity to the actual behavioral M-Levels recorded among this cohort and proved to be statistically reliable. When clinically applied, this method was found to be successful among subjects of our study group. Although there existed disparities of a few clinical units, between the actual and predicted comfort levels among the subjects, this statistical method was able to provide a working MAP, close to the behavioral MAP used by these children. The results help to infer that behavioral measurements are mandatory to program cochlear implantees, but in cases where they are difficult to obtain, this study method may be used as reference for obtaining additional inputs, in order to set an optimal MAP. The study explores the trends and correlations between electrophysiological tests and behavioral responses, recorded over time among a cohort of cochlear implantees and provides a statistical method which may be used as a guideline to predict optimal behavioral levels in difficult situations among future implantees. In 'Difficult to MAP' scenarios, following a protocol of sequential behavioral programming, in conjunction with electrophysiological correlates will provide the best outcomes.

A clinical study of electrophysiological correlates of behavioural comfort levels in cochlear implantees.

OBJECTIVES: Indications for cochlear implantation have expanded today to include very young children and those with syndromes/multiple handicaps. Programming the implant based on behavioural responses may be tedious for audiologists in such cases, wherein matching an effective Measurable Auditory Percept (MAP) and appropriate MAP becomes the key issue in the habilitation program. In 'Difficult to MAP' scenarios, objective measures become paramount to predict optimal current levels to be set in the MAP. We aimed to (a) study the trends in multi-modal electrophysiological tests and behavioural responses sequentially over the first year of implant use; (b) generate normative data from the above; (c) correlate the multi-modal electrophysiological thresholds levels with behavioural comfort levels; and (d) create predictive formulae for deriving optimal comfort levels (if unknown), using linear and multiple regression analysis. METHODS: This prospective study included 10 profoundly hearing impaired children aged between 2 and 7 years with normal inner ear anatomy and no additional handicaps. They received the Advanced Bionics HiRes 90 K Implant with Harmony Speech processor and used HiRes-P with Fidelity 120 strategy. They underwent, impedance telemetry, neural response imaging, electrically evoked stapedial response telemetry (ESRT), and electrically evoked auditory brainstem response (EABR) tests at 1, 4, 8, and 12 months of implant use, in conjunction with behavioural mapping. Trends in electrophysiological and behavioural responses were analyzed using paired t-test. By Karl Pearson's correlation method, electrode-wise correlations were derived for neural response imaging (NRI) thresholds versus most comfortable level (M-levels) and offset based (apical, mid-array, and basal array) correlations for EABR and ESRT thresholds versus M-levels were calculated over time. These were used to derive predictive formulae by linear and multiple regression analysis. Such statistically predicted M-levels were compared with the behaviourally recorded M-levels among the cohort, using Cronbach's alpha reliability test method for confirming the efficacy of this method. RESULTS: NRI, ESRT, and EABR thresholds showed statistically significant positive correlations with behavioural M-levels, which improved with implant use over time. These correlations were used to derive predicted M-levels using regression analysis. On an average, predicted M-levels were found to be statistically reliable and they were a fair match to the actual behavioural M-levels. When applied in clinical practice, the predicted values were found to be useful for programming members of the study group. However, individuals showed considerable deviations in behavioural M-levels, above and below the electrophysiologically predicted values, due to various factors. While the current method appears helpful as a reference to predict initial maps in 'difficult to Map' subjects, it is recommended that behavioural measures are mandatory to further optimize the maps for these individuals. CONCLUSION: The study explores the trends, correlations and individual variabilities that occur between electrophysiological tests and behavioural responses, recorded over time among a cohort of cochlear implantees. The statistical method shown may be used as a guideline to predict optimal behavioural levels in difficult situations among future implantees, bearing in mind that optimal M-levels for individuals can vary from predicted values. In 'Difficult to MAP' scenarios, following a protocol of sequential behavioural programming, in conjunction with electrophysiological correlates will provide the best outcomes.