Literature DB >> 20084042

Predictive model for improvement of idiopathic sudden sensorineural hearing loss.

Ting-Kuang Chao1, Tony Hsiu-Hsi Chen.   

Abstract

OBJECTIVE: To establish a predictive model for evaluating improvement in patients with idiopathic sudden sensorineural hearing loss (ISSHL). STUDY
DESIGN: Bayesian cure rate model.
SETTING: Tertiary referral center. PATIENTS: Two hundred patients whose conditions were diagnosed as ISSHL from January 2001 to April 2007 were enrolled to build a model and to train relevant parameters for prediction. MAIN OUTCOME MEASURES: The time to improvement and potential predictive factors were collected for analysis. Established factors and significant variables in the univariate analysis were included in the final model. A Bayesian approach with the WinBUGS program was applied to predict the median and 95% confidence intervals (CIs) for the time to improvement, long-term probability of improvement, and improvement probabilities at specific days.
RESULTS: The significant predictors in the final model include distortion product otoacoustic emission, auditory brainstem response, vestibular evoked myogenic potential, and audiometric types. The overall results predicted by the different combinations of covariates were summarized and organized in an Access program file that is convenient for clinical application. The results of area under the receiver operating characteristic curves at the 7th, 14th, and 30th days were 0.709 (95% CI, 0.692-0.717), 0.752 (95% CI, 0.737-0.753), and 0.807 (95% CI, 0.788-0.811), respectively. It showed that predictive validity, particularly at 1 month or so, is satisfactory.
CONCLUSION: By using the cure rate model under the context of a Bayesian survival analysis, we first identified auditory objective factors as significant predictors of improvement of ISSHL patients and further predicted the time to improvement with these correlates. The model showed a satisfactory predictive validity, particularly for 1-month individual prediction, which prompted one to make an individual prediction with an available Access program.

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Year:  2010        PMID: 20084042     DOI: 10.1097/MAO.0b013e3181cdd6d1

Source DB:  PubMed          Journal:  Otol Neurotol        ISSN: 1531-7129            Impact factor:   2.311


  2 in total

1.  Machine Learning Models for Predicting Hearing Prognosis in Unilateral Idiopathic Sudden Sensorineural Hearing Loss.

Authors:  Keon Vin Park; Kyoung Ho Oh; Yong Jun Jeong; Jihye Rhee; Mun Soo Han; Sung Won Han; June Choi
Journal:  Clin Exp Otorhinolaryngol       Date:  2020-03-12       Impact factor: 3.372

Review 2.  Vestibular evoked myogenic potentials in the prognosis of sudden hearing loss ‒ a systematic review.

Authors:  Nathalia de Paula Doyle Maia; Karen de Carvalho Lopes; Fernando Freitas Ganança
Journal:  Braz J Otorhinolaryngol       Date:  2019-11-02
  2 in total

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