Neuropsychiatric disease and treatment · 2024
Predicting Intracerebral Hemorrhage Expansion with Inflammation Indices, Non-Contrast Computed Tomography Signs and Computed Tomography Angiography Spot Sign.
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Ji Zeqiang, Ye Wanxing, Wen Xinyu, Zhao Xingquan, Li Na
Аннотация
AIM: We aimed to investigate whether a combination of inflammatory and radiological biomarkers can improve intracerebral hemorrhage (ICH) hematoma expansion (HE) prediction.
METHODS: A retrospective analysis was conducted on patients with primary supratentorial ICH within 6 h of symptom onset between September 2021 and April 2022. Predictors were explored using univariate and logistic regression analysis. We compared the discrimination of inflammatory indice-based model 1 with models 2 and 3, which included image biomarkers, using the receiver operating characteristic curve and De Long test for area under the curve comparison.
RESULTS: A total of 205 eligible participants were included, 56 (27.3%) of whom experienced HE. The neutrophil-to-lymphocyte ratio (NLR), black hole sign, BAT score, and computed tomography angiography (CTA) spot sign were independently associated with HE in the logistic regression (P<0.05). The addition of non-contrast computed tomography (NCCT) signs did not provide significant discrimination improvement (AUC, Model 2 0.875 [95% CI, 0.822-0.929] versus Model 1. 0.811 [95% CI, 0.747-0.875], p=0.089), whereas the added value of the CTA spot sign remained statistically significant (AUC, Model 3 0.922 [95% CI, 0.878-0.966] versus Model 2; p=0.030; Model 3 versus Model 1, p=0.005).
CONCLUSION: The combination of inflammatory and radiological biomarkers can predict HE with a satisfactory performance.
METHODS: A retrospective analysis was conducted on patients with primary supratentorial ICH within 6 h of symptom onset between September 2021 and April 2022. Predictors were explored using univariate and logistic regression analysis. We compared the discrimination of inflammatory indice-based model 1 with models 2 and 3, which included image biomarkers, using the receiver operating characteristic curve and De Long test for area under the curve comparison.
RESULTS: A total of 205 eligible participants were included, 56 (27.3%) of whom experienced HE. The neutrophil-to-lymphocyte ratio (NLR), black hole sign, BAT score, and computed tomography angiography (CTA) spot sign were independently associated with HE in the logistic regression (P<0.05). The addition of non-contrast computed tomography (NCCT) signs did not provide significant discrimination improvement (AUC, Model 2 0.875 [95% CI, 0.822-0.929] versus Model 1. 0.811 [95% CI, 0.747-0.875], p=0.089), whereas the added value of the CTA spot sign remained statistically significant (AUC, Model 3 0.922 [95% CI, 0.878-0.966] versus Model 2; p=0.030; Model 3 versus Model 1, p=0.005).
CONCLUSION: The combination of inflammatory and radiological biomarkers can predict HE with a satisfactory performance.