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Updated: Jul 2, 2025

Neuro-rehabilitation Approach for Sudden Sensorineural Hearing Loss
Published on: January 25, 2016
Predictive Model for Prognosis of Sudden Sensorineural Hearing Loss by Nomogram
Aidan Dong1, Jianhua Peng2, Renyu Lin2
1Department of Otolaryngology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
Abstract:
Objective: To explore the prognostic factors of patients with sudden sensorineural hearing loss (SSNHL), analyze the possible influencing factors, and construct a nomogram for personalized evaluation of their prognosis. Methods: A retrospective study was conducted on 269 patients with SSNHL. The prognostic factors were analyzed by univariate analysis and multivariate logistic regression analysis. The nomogram was constructed based on the results of multivariate logistic regression analysis, and the model was verified by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results: Among the 269 patients hospitalized, 136 cases were improved (44 cases were cured, 28 cases were markedly effective, 64 cases were effective) and 133 cases were ineffective. After univariate analysis, it was found that age, duration from onset to treatment, audiometric configuration, serum albumin (ALB), and neutrophil-to-lymphocyte ratio (NLR) were associated with hearing outcomes. Duration from onset to treatment and audiometric configuration were independent risk factors when the treatment outcome was divided into ineffective, effective, significant improvement, and complete recovery groups or divided into improvement and ineffective groups after multivariate logistic regression analysis. The factors according to univariate analysis and multivariate logistic regression analysis results were included in the nomogram to construct the prediction models. The area under the ROC curve of model discrimination was 0.752 [95% confidence interval (CI): 0.695-0.808] when the treatment outcome was divided into 2 groups. The calibration curve showed the consistency of the results, and the DCA prediction curve showed good clinical efficacy. The C-index was 0.756 (95% CI: 0.710-0.802) when the treatment outcome was divided into 4 groups. Conclusion: Age, duration from onset to treatment, audiometric configuration, ALB, and NLR are influencing factors for SSNHL. Duration from onset to treatment and audiometric configuration are independent risk factors for SSNHL. The nomogram presents the prognosis of patients with SSNHL in an intuitive, visual, and readable graph, providing clinicians with a personalized assessment.

