Prognostic value of the Island sign for hematoma expansion and functional outcome after intracerebral hemorrhage: a systematic review and meta-analysis.

PURPOSE: The Island Sign (IS) is a radiological finding observed in patients with intracerebral hemorrhage (ICH). This meta-analysis aimed to evaluate the association between IS and both hematoma expansion (HE) and functional outcomes by comparing ICH patients with and without IS.

METHODS

We searched PubMed, Embase and Cochrane Library for studies of intracerebral hemorrhage reporting the IS. The primary outcomes were functional status and hematoma expansion, secondary outcome was mortality. Statistical analysis was performed using RStudio, effect sizes were calculated as odds ratios (ORs) with 95% confidence interval (95% CIs), and heterogeneity was assessed with I2 statistics. In addition, meta-regression and sensitivity analyses were performed, and publication bias was assessed through funnel plots and Egger's regression test.

RESULTS

We included 21 observational studies with a total of 9,459 patients with spontaneous ICH, 1,769 of them had IS, while 7,690 did not. The mean age was 63.5 ± 13.2 and 5,835 (61.7%) were male. Poor functional outcomes (OR 2.77, 95% CI: 2.14-3.58, p < 0.0001, I2 = 4.9%) and hematoma expansion (OR 2.75, 95% CI: 1.87-4.03, p < 0.0001, I2 = 77.4%) were substantially higher in patients with IS, as well as the overall mortality rate (OR 2.54, 95% CI: 1.55-4.17, p = 0.0002, I2 = 0%). Meta-regression analysis showed no statistically significant association between imaging-related timing variables and hematoma expansion. Furthermore, the leave-one-out sensitivity analyses showed that no single study exerted a disproportionate influence on the overall effect for the examined outcomes, and Egger's linear regression tests were not statistically significant for both outcomes.

CONCLUSION

Patients with the Island Sign are associated with higher rates of poor functional outcomes and hematoma expansion. Thus, IS is a relevant radiological finding with potential to support early risk stratification and optimize patient management and treatment selection.