Predictive model for diagnosing central lesions in emergency department patients with isolated dizziness who undergo diffusion-weighted magnetic resonance imaging

Risk factors for imaging abnormalities in patients with dizziness complaints: an algorithm for ordering brain imaging

AIM

The diagnostic detection of abnormal findings with head imaging is low for dizziness. This study aimed to investigate the risk factors associated with abnormal computed tomography (CT) or magnetic resonance imaging (MRI) findings for patients with dizziness.

MATERIALS AND METHODS

Medical records of patients who had CT or MRI examinations for dizziness complaints between January 1, 2019, and December 31, 2020, were retrospectively reviewed. Imaging outcomes were grouped as normal or abnormal findings. Risk factors, including demographics, dizziness pattern, symptoms, comorbidities, and medical history were assessed. A Chi-square automatic interaction detection decision tree model was used to classify abnormal imaging findings based on risk factors identified through multivariable analyses.

RESULTS

A total of 2,342 scans were examined. Detection of abnormal findings was 4.8% (n = 96), including acute cerebral infarction (n = 33), acute cranial hemorrhage (n = 15), cancer/tumor-like lesions (n = 27), and inner ear abnormalities (n = 21). The risk factor most indicative of abnormal findings were loss of consciousness and neurologic deficit (Odds Ratio 55.57, p < 0.001). The likelihood of abnormality indicating acute brain lesions was 44.4% for patients with loss of consciousness and neurologic deficits. Loss of consciousness and neurologic deficits, hearing loss, nausea/vomiting, and comorbid malignancy distinguished abnormal findings from negative imaging findings (AUC 0.729; 95%CI 0.672-0.785; p < 0.001). Patients with unspecific dizziness complaints were less likely to have abnormal imaging findings.

CONCLUSION

These findings highlighted the significance of specific risk factors in recognizing individuals with dizziness complaints who may have abnormal imaging findings indicative of serious diseases. Further studies are warranted to verify the findings.

Blood biomarkers for the differentiation between central and peripheral vertigo in the emergency department: a systematic review and meta-analysis

BACKGROUND/INTRODUCTION

In patients with acute vestibular syndrome (AVS), differentiating between stroke and nonstroke causes is challenging in the emergency department (ED). Correct diagnosis of vertigo etiology is essential for early optimum treatment and disposition.

OBJECTIVES

The aim of this systematic review and meta-analysis was to summarize the published evidence on the potential of blood biomarkers in the diagnosis and differentiation of peripheral from central causes of AVS.

METHODS

A literature search was conducted for studies published until January 1, 2023, in PubMed, Ovid Medline, and EMBASE databases analyzing biomarkers for the differentiation between central and peripheral AVS. The Quality Assessment of Diagnostic Accuracy Studies questionnaire 2 was used for quality assessment. Pooled standardized mean difference and 95% confidence intervals were calculated if a biomarker was reported in two or more studies. Heterogeneity among included studies was investigated using the I2 metric.

RESULTS

A total of 17 studies with 859 central and 4844 peripheral causes of acute dizziness or vertigo, and analysis of 61 biomarkers were included. The general laboratory markers creatinine, blood urea nitrogen, albumin, C-reactive protein, glucose, HbA1c, leukocyte counts, and neutrophil counts and the brain-derived biomarkers copeptin, S100 calcium-binding protein β (S100β), and neuron-specific enolase (NSE) significantly differentiated central from peripheral causes of AVS.

CONCLUSIONS

This systematic review and meta-analysis highlights the potential of generalized inflammatory markers and brain-specific blood protein markers of NSE and S100β as diagnostic biomarkers for central from peripheral differentiation in AVS. These results, as a complement to clinical characteristics, provide guidance for future large-scale diagnostic research, in this challenging ED patient population.