DEVELOPMENT OF A STATISTICAL MODEL FOR THE PREDICTION OF   BENIGN PAROXYSMAL POSITIONAL VERTIGO (BPPV)  DIAGNOSIS

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dr. Moreshwar; dr.reena singh; dr. Anupal deka

DEVELOPMENT OF A STATISTICAL MODEL FOR THE PREDICTION OF BENIGN PAROXYSMAL POSITIONAL VERTIGO (BPPV) DIAGNOSIS

Authors: dr. Moreshwar, dr.reena singh, dr. Anupal deka

Unique Paper ID: 180739
Volume: 12
Issue: 1
PageNo: 6256-6274

Keywords: Thesis Medical Vertigo VEMP

Abstract:
This study aimed to improve the diagnosis of vertigo in emergency settings by developing a questionnaire-based predictive model combined with traditional clinical practices. The study sought to identify key symptoms and diagnostic tools associated with vertigo, with a focus on evaluating the relationship between dizziness and other symptoms, including headaches. Methods: A cross-sectional, questionnaire-based study was conducted over two years at the Emergency Department and Department of ENT at Max Superspecialty Hospital, Dehradun, India. Patients aged 18 and older who presented with vertigo as their primary complaint were included. Clinical evaluations, including history, vital signs, and ENT referrals, were conducted. A detailed questionnaire was administered to eligible patients to capture specific vertigo-related symptoms, and the responses were analyzed using logistic regression for predictive analysis. Diagnostic investigations such as Vestibular Evoked Magnetic Potential (VEMP), CT scans, MRI, and Dix-Hallpike tests were performed. Results: The analysis of 271 reported cases reveals that the majority of patients presented with symptoms related to balance and spatial orientation. Dizziness was the most common complaint, accounting for 30.3% of cases, followed by visual vertigo (27.7%), giddiness (12.2%), and benign paroxysmal positional vertigo (BPPV) (11.1%). Together, these symptoms constituted over 80% of all cases, indicating a strong predominance of vestibular or balance-related issues. Less common symptoms included motion sensitivity (5.9%), traumatic brain injury (3.0%), syncope (2.6%), and tinnitus (1.8%). Rare diagnoses such as stroke, TIA, vestibular neuritis, and various ear-related conditions were each reported in 0.4% to 0.7% of cases. Conclusion: The study demonstrated the utility of combining clinical evaluations with a symptom-based questionnaire to improve the diagnosis of vertigo in emergency settings. Findings regarding the association between dizziness and headaches, particularly light sensitivity and prolonged dizziness, emphasize the importance of considering both vestibular and neurological causes in diagnosis. The study supports the use of a multifaceted approach to enhance diagnostic accuracy and management of vestibular disorders.

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Cite This Article

ISSN: 2349-6002
Volume: 12
Issue: 1
PageNo: 6256-6274

DEVELOPMENT OF A STATISTICAL MODEL FOR THE PREDICTION OF BENIGN PAROXYSMAL POSITIONAL VERTIGO (BPPV) DIAGNOSIS

Available:https://ijirt.org/article?manuscript=180739

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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