Construction and validation of a prognostic nomogram for idiopathic sudden sensorineural hearing loss based on a multicenter retrospective study
Year: 2024
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Idiopathic sudden sensorineural hearing loss (ISSNHL) is a sudden hearing loss of unknown etiology, with complex and diverse prognostic factors. Aim This study aims to identify independent prognostic factors for ISSNHL and to construct and validate a nomogram based on these factors. METHODS: This study collected multicenter retrospective data and compared the differences between effective treatment and ineffective treatment groups in terms of age, vertigo, and several serum markers. Significant prognostic factors were identified using univariate Logistic regression analysis, followed by multivariate Logistic regression to identify independent prognostic factors. Based on the results of the multivariate Logistic regression, a nomogram was constructed in the training set and its applicability was validated in both internal and external validation sets. RESULTS: A total of 400 ISSNHL patients were included in the study. Multivariate Logistic regression analysis identified age, vertigo, FIB, MLR, and CRP/Alb as independent prognostic factors. The nomogram demonstrated good predictive performance in the training set, internal validation set, and external validation set, with C-indices of 0.78, 0.79, and 0.78, respectively. CONCLUSION: This study identified independent prognostic factors for the treatment efficacy of ISSNHL and developed a nomogram with good predictive performance. This nomogram can provide clinicians with individualized prognostic assessments and treatment decision support, thereby improving the treatment outcomes and prognosis for ISSNHL patients.
Authors: Chao-qun Hong, Qiao-fei Jia, Jing-jing Zhu, Hua-jun Lu
Institution: Wenzhou Medical University
Language: English
Subfield: Neurology
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $3,630
OpenAlex ID: W4405212529
