Patient-Level Modeling of Ménière’s Disease vs. Vestibular Migraine: Performance of Speech Discrimination and Caloric-vHIT Dissociation

TL;DR

This study shows that speech discrimination scores alone can effectively distinguish Ménière’s disease from vestibular migraine, better than other vestibular tests.

Contribution

The study demonstrates that speech discrimination scores alone outperform vestibular test patterns in differentiating Ménière’s disease from vestibular migraine at the patient level.

Findings

Bilateral speech discrimination scores achieved an AUC of 0.866 for distinguishing MD from VM.

Caloric–vHIT dissociation (CalHiT-A) was more common in MD but did not improve diagnostic performance when added to SDS.

SDS-only models showed better calibration and decision benefit compared to models including CalHiT-A.

Abstract

Background: Differentiating Ménière’s disease (MD) from vestibular migraine (VM) remains difficult because current diagnostic frameworks are predominantly clinical and incorporate pure-tone thresholds, risking incorporation bias. We asked whether speech discrimination scores (SDS) alone can separate MD from VM at the patient level and whether adding a prespecified vestibular marker, the caloric–vHIT dissociation, pattern A (abnormal calorics with normal horizontal vHIT), improves performance. Methods: In a retrospective cohort (2015–2018) including definite MD (n = 60) and definite VM (n = 40) by Bárány/ICHD criteria, we trained patient-level logistic regression models with 5-fold out-of-fold validation and in-fold preprocessing. To avoid incorporation bias, PTA was excluded from all models. Predefined feature sets were as follows: (1) SDS-only (bilateral SDS), (2) CalHiT-A-only (Yes/No; canal paresis ≥22% with horizontal-canal vHIT gain ≥0.80 in either ear), and (3) SDS+CalHiT-A. Discrimination was assessed by ROC–AUC with bootstrap 95% CIs; calibration and decision-curve analysis (DCA) are reported. An exploratory model encoded SDS as “affected/healthy.” Results: The SDS-only model achieved AUC 0.866 (95% CI 0.787–0.937). CalHiT-A-only yielded AUC 0.674 (0.561–0.778). Adding CalHiT-A to SDS did not improve discrimination (SDS+CalHiT-A AUC 0.844 [0.760–0.913]). The exploratory “affected/healthy” SDS encoding underperformed (AUC 0.801 [0.706–0.882]). CalHiT-A was significantly more prevalent in MD than in VM (56.7% [34/60] vs. 17.5% [7/40]; Fisher’s exact p = 1.49 × 10−4). Calibration favored SDS-only, and DCA showed the highest net benefit for SDS-only across thresholds p = 0.05–0.40. Conclusions: Bilateral SDS alone provides robust, well-calibrated discrimination between MD and VM and outperforms CalHiT-A and the affected/healthy SDS encoding. In this cohort, vestibular test dissociation did not add diagnostic value beyond SDS at the patient level, supporting SDS-centered diagnostic workflows while reserving CalHiT-A for adjudication and phenotyping rather than primary classification.

Figures