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A Novel 10-Point Score System to Predict Early Hematoma Growth in Patients With Spontaneous Intracerebral Hemorrhage

Jing-Jing Fu, Sheng Hu, Mi Yang, Zhao-Sheng Li, Xiuhua Song, Zi-Wen Wang, M. I. Lloret-Villas, A. D’Souza et al.

Frontiers in Neurology, 2020

216 participants · 9 citations

Abstract

Background: A rapid and reliable method to predict significant early hematoma growth in the acute setting is of great important to better inform clinicians and researchers in their efforts to improve outcomes for patients. Methods: We established a 10-point score system to predict hematoma growth including four parameters: baseline intracerebral hemorrhage (ICH) volume > 30 mL, time to initial CT scan ≤ 3 h, island sign and black hole sign. Then, we reviewed our ICH database and assessed the predict value of the score system. Results: A total of 216 ICH patients were included. Patients with hematoma growth at 24 h had higher score than those without hematoma growth (7.6 ± 3.0 vs. 2.0 ± 2.4, p < 0.001). The optimal cut-off value of the score for predicting hematoma growth was 3 (area under curve, 0.937; 95% CI, 0.899–0.975, p < 0.001), with 95% CI of 0.896–0.965 in bootstrapping analysis. The sensitivity, specificity, positive predictive and negative predictive value of the score ≥ 3 for predicting hematoma growth were 97.8, 92.7, 90.9, and 98.3%. Conclusion: The 10-point score system could predict hematoma growth with high accuracy.

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