Using the probability of recovery from an acute unilateral vestibulopathy to determine the severity of the vestibular loss: Development of a multivariate PROBIT model.

ObjectivesThis study aims to develop a prognostic model, based on the video Head Impulse Test (vHIT)-Vestibulo-Ocular Reflex (VOR) gain, of vestibular loss after an acute Unilateral Vestibulopathy (aUVP) predicting the probability of an objective and significant recovery.DesignData gathered prospectively in patients with aUVP were re-analyzed. After an exploratory cluster analysis, a multivariate PROBIT regression model was used to objectively pinpoint the value of vHIT-VOR gain at baseline that predicts a significant recovery after 10 weeks. Significant recovery was defined as a vHIT-VOR gain superior or equal to 0.70 after 10 weeks.ResultsA total of 48 subjects were included. The final model identified 2 thresholds, respectively, at 0.53 and 0.74, to classify severe (vHIT-VOR gain ≤0.53), moderate (0.53 < vHIT-VOR gain ≤0.74), and non-significant (0.74 < vHIT-VOR gain) vestibular loss. The probability of a significant recovery was 20% ((Prediction Interval 95% (PI) [0%-43%]) for a gain of 0.50 at baseline, while it doubles (45% (PI [0%-63%]) for an initial gain of 0.60. Our final model demonstrated a good area under the curve (AUC) of 0.85. The corrected AUC after bootstrap resampling was 0.81 (CI 95% [0.74, 0.89]). A good Brier score of the predicted probabilities was also obtained, at 0.15.Conclusions and relevanceFor the first time, this paper proposes a model that objectively defines the severity of vestibular loss at baseline after an aUVP. This research lays the groundwork for future studies to validate our prognostic model and perform more precise analyses of vestibular compensation patterns.