Validation of the Sudbury Vertigo Risk Score to risk stratify for a serious cause of vertigo.
Journal Articles
Overview
Research
Identity
View All
Overview
abstract
INTRODUCTION: In 2022, nearly 0.5 million Canadians visited an emergency department (ED) for dizziness, accounting for over 3.5% of all ED visits. Of these patients, only 2%-5% received a serious diagnosis. The cost of ED and inpatient care for dizziness in Canada exceeds $200 million per year, of which neuroimaging accounts for a large proportion. Over one-third of dizziness patients undergo a CT scan of the head, 96% of which are negative. Despite extensive investigation, patients discharged with a benign dizziness diagnosis have a 50-fold increased risk of being admitted to the hospital within 7 days with a diagnosis of stroke. Our study aimed to derive a clinical risk score to guide the investigation and referral for serious causes of vertigo in ED patients. METHODS: This multicenter historical cohort study was conducted over 7 years at three university-affiliated tertiary care EDs. Patients presenting with vertigo, dizziness, or imbalance were recruited. The main outcome was an adjudicated serious diagnosis, defined as stroke, transient ischemic attack, vertebral artery dissection, or brain tumor. We estimated a sample size of 4450 patients, based on a 2% prevalence of serious outcomes, to evaluate the sensitivity with 95% confidence intervals (CIs). RESULTS: A total of 4559 patients were enrolled (mean age 78.1 years, 57.8% women), with serious events occurring in 104 (2.3%) patients. The C-statistic was 0.95 (95% CI 0.92-0.98). The risk of a serious diagnosis ranged from 0% for a score of <5 to 16.7% for a score >8. Sensitivity for a serious diagnosis was 100% (95% CI 96.5%-100%) and specificity was 69.2% (95% CI 67.8%-70.51%) for a score <5. CONCLUSION: The Sudbury Vertigo Risk Score effectively identifies the risk of a serious diagnosis in patients with dizziness. Thus, it guides further investigation, consultation, and treatment decisions and ultimately improves resource utilization and reduces missed diagnoses.