Lauren T Roland1, Dorina Kallogjeri, Belinda C Sinks, Steven D Rauch, Neil T Shepard, Judith A White, Joel A Goebel. 1. *Department of Otolaryngology - Head and Neck Surgery, Washington University in St Louis School of Medicine, St Louis, Missouri †Department of Otolaryngology, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts ‡Division of Audiology, Mayo Clinic, Rochester, Minnesota §Section of Vestibular and Balance Disorders, Head and Neck Institute, The Cleveland Clinic, Cleveland, Ohio, U.S.A.
Abstract
OBJECTIVE: Test performance of a focused dizziness questionnaire's ability to discriminate between peripheral and nonperipheral causes of vertigo. STUDY DESIGN: Prospective multicenter. SETTING: Four academic centers with experienced balance specialists. PATIENTS: New dizzy patients. INTERVENTIONS: A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. MAIN OUTCOMES: Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and nonperipheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. RESULTS: In total, 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and nonperipheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central, and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central, and other causes was considered good as measured by c-indices of 0.75, 0.7, and 0.78, respectively. CONCLUSION: This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from nonperipheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed.
OBJECTIVE: Test performance of a focused dizziness questionnaire's ability to discriminate between peripheral and nonperipheral causes of vertigo. STUDY DESIGN: Prospective multicenter. SETTING: Four academic centers with experienced balance specialists. PATIENTS: New dizzy patients. INTERVENTIONS: A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. MAIN OUTCOMES: Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and nonperipheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. RESULTS: In total, 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and nonperipheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central, and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central, and other causes was considered good as measured by c-indices of 0.75, 0.7, and 0.78, respectively. CONCLUSION: This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from nonperipheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed.
Authors: Jeff G Zhao; Jay F Piccirillo; Edward L Spitznagel; Dorina Kallogjeri; Joel A Goebel Journal: Otol Neurotol Date: 2011-02 Impact factor: 2.311
Authors: Pia Michael; Carolina Estibaliz Oliva; Marcia Nuñez; Cristian Barraza; Juan Pablo Faúndez; Hayo A Breinbauer Journal: Front Neurol Date: 2016-07-18 Impact factor: 4.003