Abstract
Acute vertigo and dizziness are frequent presenting symptoms in patients in the emergency department. These symptoms, which can be subtle and transient, present diagnostic challenges because they can be caused by a broad range of conditions that cut across many specialties and organ systems. Previous work has emphasized the value of combining structured history taking and a targeted examination focusing on subtle oculomotor signs. In this review, we discuss various diagnostic bedside algorithms proposed for the acutely dizzy patient. We analyzed these different approaches by calculating their area-under-the-curve (ROC) characteristics and sensitivity/specificity. We found that the algorithms that incorporated structured history taking and the use of subtle oculomotor signs had the highest diagnostic accuracy. In fact, both the HINTS+ bedside exam and the STANDING algorithm can more accurately diagnose acute strokes than early (<24 to 48 h after symptom onset) MRI with diffusion-weighted imaging (DWI). An important caveat is that HINTS and STANDING require moderate training to achieve this accuracy. Therefore, for physicians who have not undergone adequate training, other approaches are needed. These other approaches (e.g., ABCD2 score, PCI score, and TriAGe+ score) rely on vascular risk factors, clinical symptoms, and focal neurologic findings. While these other scores are easier for frontline providers to use, their diagnostic accuracy is far lower than HINTS+ or STANDING. Therefore, a focus on providing dedicated training in HINTS+ or STANDING techniques to frontline clinicians will be key to improving diagnostic accuracy and avoiding unnecessary brain imaging.