Accuracy of spot sign in predicting hematoma expansion and clinical outcome: A meta-analysis

Medicine (Baltimore). 2018 Aug;97(34):e11945. doi: 10.1097/MD.0000000000011945.

Abstract

Background: Spot sign on computed tomography angiography (CTA) has been reported as a risk factor for hematoma expansion (HE) and poor outcome after intracerebral hemorrhage (ICH). We performed a meta-analysis to investigate the predictive accuracy of spot sign for HE, mortality risk, and poor outcome.

Methods: We searched PubMed, Embase, and the Cochrane Library for relevant studies. Studies were incorporated if they reported data on relationship between CTA spot sign and HE, mortality or poor outcome.

Results: Twenty-nine studies were pooled in this meta-analysis. The spot sign occurred in 23.4% patients with spontaneous ICH undergoing CTA scans. It showed a sensitivity of 62% (95% confidence interval [CI] 54-69), with a specificity of 88% (95% CI 85-91). Spot sign was related with increased risk of HE (odds ratios [OR] 8.49, 95% CI 7.28-9.90). In the analysis of association between spot sign and outcome, patients with spot sign had a significant higher risk of in-hospital death (OR 5.08, 95% CI 3.16-8.18) and 3-month death (OR 3.80, 95% CI 2.62-5.52). The spot sign was also a predictor of poor outcome at discharge (OR 6.40, 95% CI 3.41-12.03) and at 3 months (OR 4.44, 95% CI 2.33-8.46).

Conclusions: The overall incidence of CTA spot sign in spontaneous ICH patients is substantial. Spot sign demonstrated a good diagnostic performance in predicting HE and was closely associated with increased risk of death and poor outcome.

Publication types

  • Meta-Analysis
  • Review

MeSH terms

  • Adult
  • Aged
  • Cerebral Angiography / methods*
  • Cerebral Hemorrhage / diagnostic imaging*
  • Cerebral Hemorrhage / mortality
  • Computed Tomography Angiography / methods*
  • Female
  • Hematoma / diagnostic imaging*
  • Hematoma / mortality
  • Humans
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Risk Assessment / methods
  • Risk Factors
  • Sensitivity and Specificity