Development and validation of prediction model to estimate vertigo risk after endolymphatic sac decompression in Meniere's disease: a retrospective cohort study

PurposeTo study the efficacy predictors of endolymphatic sac decompression (ESD) in Meniere's disease (MD), and to establish and verify the prediction model of vertigo after ESD in patients with MD.MethodsThe retrospective cohort data of 56 patients with unilateral MD who underwent ESD surgery were recorded. A stepwise regression method was used to select optimal modeling variables, and we established a logistic regression model with the outcome of vertigo after ESD. The bootstrap method was used for internal validation.ResultsPotential predictors included sex, age, follow-up duration, disease course, attack duration, frequency of attack, pure-tone threshold average (PTA) of the patient's speech frequency, audiogram type, glycerin test results, MD subtype, and 10-year atherosclerotic cardiovascular disease risk classification. Using the stepwise regression method, we found that the optimal modeling variables were the audiogram type and PTA of the patient's speech frequency. The prediction model based on these two variables exhibited good discrimination [area under the receiver operating characteristic curve: 0.72 (95% confidence interval: 0.57-0.86)] and acceptable calibration (Brier score 0.21).ConclusionThe present model based on the audiogram type and PTA of the patient's speech frequency was found to be useful in guidance of ESD efficacy prediction and surgery selection.