Work

Prediction Model for Etiologic Differentiation of Isolated Vestibular Syndrome in Emergency Settings

Year: 2025

Type: article

Abstract: ABSTRACT Objective This study aimed to develop and validate a predictive model for differentiating central from peripheral etiologies in patients with isolated vestibular syndrome (VS). Methods In this multicenter retrospective cohort study, 506 patients with isolated VS from five hospitals were divided into derivation ( n = 301) and validation ( n = 205) cohorts. Multivariable logistic regression was performed to determine independent predictors of central VS. These predictors were assigned weights to construct the SAV 3 E score. The performance of the SAV 3 E was assessed using the area under the curve (AUC), calibration, and decision curve analysis (DCA) and compared with that of the TriAGe+ and STANDING models. Results The SAV 3 E score incorporated five predictors: absence of vestibular vagal symptoms (OR, 0.233; 95% CI, 0.084–0.648; p = 0.005), prior stroke (OR, 15.204; 95% CI, 4.455–51.884; p < 0.001), ABCD 2 score of 4–7 (OR, 1.903; 95% CI, 1.206–3.004; p = 0.006), central video oculography nystagmus (OR, 38.377; 95% CI, 8.631–170.644; p < 0.001), and positive video head impulse test (OR, 0.078; 95% CI, 0.033–0.188; p < 0.001). It displayed good discriminative performance with AUCs 0.910 and 0.886 in the derivation and validation cohorts, respectively. It outperformed TriAGe+ (AUC: 0.706) and STANDING (AUC: 0.779) models. Furthermore, calibration analysis revealed good model fit across cohorts (Hosmer‐Lemeshow test results: derivation cohort, p = 0.899; validation cohort, p = 0.789). DCA confirmed good clinical utility across a wide range of probability thresholds (derivation cohort: 0.01–0.86, validation cohort: 0.01–1.00). Conclusion The SAV 3 E score is a validated tool aimed at differentiating central versus peripheral VS, with the potential to improve diagnostic accuracy for urgent etiologies such as stroke.

Source: Annals of Clinical and Translational Neurology

DOI: 10.1002/acn3.70213