Predictive nomograms and an algorithm for managing patients with probable Meniere's disease.

ABSTRACT

PURPOSE: To explore the efficacy of diagnostic tests in accurately reclassifying patients initially diagnosed with probable Meniere's disease (MD) into either definite or non-MD categories. MATERIALS AND METHODS: A retrospective cohort study was conducted at a neurotology clinic between 1/2016 and 5/2022. Patients underwent a battery of tests, from which sensitivity, specificity, positive and negative predictive values, as well as positive and negative likelihood ratios, were calculated. Additionally, prediction nomograms were developed. RESULTS: Of the 69 patients, 25 (36.2 %) were initially classified as definite MD, 21 (30.4 %), probable MD, and 23 (33.4 %) non-MD. The mean follow-up was 3.5 years. The sensitivity of electrocochleography (ECochG) was the highest (92 %), with a negative likelihood ratio of 15 %. Magnetic resonance imaging (MRI) with MD-protocol had the highest specificity (100 %), with a positive likelihood ratio of 100 %. Videonystagmography, video head impulse test, and cervical vestibular-evoked myogenic potentials, had lower sensitivity and specificity. We were able to reclassify 18 (86 %) patients with probable MD 12 (57 %) were diagnosed with definite MD, and 6 (29 %) were diagnosed with non-MD, consistent with their clinical course. CONCLUSIONS: The combination of ECochG and MRI with MD-protocol provides the most reliable approach to reclassify patients with Probable MD, ensuring a precise and accurate diagnosis. Vestibular tests express the functional status of the labyrinth and may not be reliable. Our findings provide valuable insights into clinical decision-making for patients with Probable MD and raise the consideration of additional diagnostic tests as supplementary to the existing clinical-only diagnosis criteria.