Establishment of a Predictive Model for the Efficacy of Vestibular Rehabilitation Therapy in Patients With Vestibular Peripheral Vertigo.

Aims/Background Vestibular peripheral vertigo, a common condition, is usually managed through vestibular rehabilitation therapy. However, while the current treatment approaches are effective, their efficacy varies among patients. Therefore, establishing a prediction model, evaluating rehabilitation outcomes, and optimizing treatment plans are crucial for patient rehabilitation. Hence, this study aims to explore the factors affecting the clinical efficacy of vestibular rehabilitation in peripheral vestibular vertigo and establish a prediction model based on these factors. Methods This retrospective study analyzed clinical data from 212 patients with peripheral vestibular vertigo treated at Sichuan Mental Health Center, The Third Hospital of Mianyang, China, between January 2022 and December 2023. Patients were divided into a modeling group (n = 159) and a validation group (n = 53) in a 3:1 ratio. Patients in the modeling group were further divided into two subgroups based on efficacy: a group with good efficacy (n = 108) and a group with poor efficacy (n = 51). Baseline characteristics from the patients were compared between the modeling and validation groups. Furthermore, univariate and multivariate analyses were conducted to identify factors influencing the clinical efficacy of vestibular rehabilitation in peripheral vestibular vertigo. Results There were statistically significant differences in anxiety, vertigo, concurrent headache, ear symptoms, and lack of sleep in the modeling group (p < 0.05). Multivariate logistic regression analysis identified anxiety, severity of dizziness, accompanying headaches, ear symptoms, and inadequate sleep as the independent factors affecting the clinical efficacy of vestibular rehabilitation in treating peripheral vertigo (p < 0.05). Furthermore, a model was established as follows: [Logit (P) = -2.836 + (1.673X₁) + (2.220X₂) + (0.960X₃) + (1.150X₄) + (1.202X₅)]. The calibration curves of the model in both the training and validation groups were a straight line close to 1, indicating that the predicted efficacy of the model was in agreement with the actual risk. The receiver operating characteristic (ROC) curve analysis revealed that the predicted area under the curve of the model for the clinical efficacy of vestibular rehabilitation in treating vestibular peripheral vertigo was 0.943 (95% confidence interval [CI]: 0.885-0.946, p < 0.001) in the modeling group and 0.881 (95% CI: 0.796-0.906, p < 0.001) in the validation group. Decision curve analysis (DCA) evaluated the clinical utility of the model in predicting efficacy, indicating the model's obvious positive net benefits. Conclusion Anxiety, high vertigo severity, concomitant headache, ear symptoms, and inadequate sleep adversely impact the clinical efficacy of vestibular rehabilitation in peripheral vestibular vertigo. Establishing a prediction model based on these factors can help clinicians in early clinical intervention, thereby improving patient clinical efficacy.