Factors associated with early hematoma expansion in intracerebral hemorrhage and the value of non-contrast computed tomography imaging features combined with clinical data for early identification.

内容摘要

Early hematoma expansion (HE) after intracerebral hemorrhage (ICH) critically affects patient outcomes. Identifying HE risk using emergency non-contrast computed tomography (NCCT) features and clinical data is important for early risk stratification and evaluation. This study analyzed factors associated with early HE and evaluated the value of NCCT features combined with clinical data for HE identification. A total of 571 patients with spontaneous supratentorial ICH admitted between January 2022 and December 2025 were enrolled. Five NCCT signs were evaluated at baseline. Four signs significantly associated with HE (black hole, swirl, blend, and satellite signs) were summed to construct a primary comprehensive sign score (0-4); a 5-sign score additionally including the island sign was examined in a sensitivity analysis. Patients were stratified by HE status, sign score quantiles, sex, and hematoma morphology, then randomly assigned to training (n = 391) and validation (n = 180) sets. Univariate and multivariate logistic regression identified independent HE factors and constructed a combined prediction model. Model performance was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). HE was defined as an absolute volume increase > 6 mL or a relative increase > 33% on follow-up CT compared with baseline CT. Among 571 patients, 292 (51.1%) experienced early HE. Multivariate analysis showed that the 4-sign score [odds ratio (OR): 1.850, 95% confidence interval (CI): 1.505-2.274, P < 0.001], irregular hematoma morphology (OR: 2.071, 95% CI: 1.262-3.399, P = 0.004), time from onset to initial CT (OR: 0.845, 95% CI: 0.750-0.953, P = 0.006), male sex (OR: 1.500, 95% CI: 1.028-2.189, P = 0.036), and baseline CT attenuation (OR: 0.964, 95% CI: 0.934-0.995, P = 0.024) were independently associated with HE. The primary combined model achieved an area under the curve (AUC) of 0.731 (95% CI: 0.682-0.781) in the training set and 0.716 (95% CI: 0.641-0.791) in the validation set. The 5-sign sensitivity model showed similar discrimination (AUC: 0.722 and 0.704, respectively), with no significant difference (P = 0.188 and P = 0.283). Calibration and DCA were broadly comparable between models. A 4-sign comprehensive imaging score, irregular hematoma morphology, time from onset to initial CT, male sex, and baseline CT attenuation were independently associated with early HE in patients with ICH. A model based on NCCT features combined with clinical data may provide a practical adjunct for early HE risk stratification in patients with ICH.