AI Article Synopsis

  • * Researchers analyzed data from 226 patients who received a CT scan within 6 hours of their symptoms and used various measurements (hematoma volume, PHE volume, and platelet-to-lymphocyte ratio) to identify predictors of PHE growth.
  • * The findings revealed that a PHE volume increase of 5.5 mL is a critical threshold for predicting poor outcomes, with significant predictors being hematoma surface area, presence of an expansion-prone hematoma, and PLR,

Article Abstract

Background: Perihematomal edema (PHE) is regarded as a potential intervention indicator of secondary injury following intracerebral hemorrhage (ICH). But it still lacks a comprehensive prediction model for early PHE formation.

Methods: The included ICH patients have received an initial Computed Tomography scan within 6 hours of symptom onset. Hematoma volume and PHE volume were computed using semiautomated computer-assisted software. The volume of the hematoma, edema around the hematoma, and surface area of the hematoma were calculated. The platelet-to-lymphocyte ratio (PLR) was calculated by dividing the platelet count by the lymphocyte cell count. All analyses were 2-tailed, and the significance level was determined by P <0.05.

Results: A total of 226 patients were included in the final analysis. The optimal cut-off values for PHE volume increase to predict poor outcomes were determined as 5.5 mL. For clinical applicability, we identified a value of 5.5 mL as the optimal threshold for early PHE growth. In the multivariate logistic regression analyses, we finally found that baseline hematoma surface area (p < 0.001), expansion-prone hematoma (p < 0.001), and PLR (p = 0.033) could independently predict PHE growth. The comprehensive prediction model demonstrated good performance in predicting PHE growth, with an area under the curve of 0.841, sensitivity of 0.807, and specificity of 0.732.

Conclusion: In this study, we found that baseline hematoma surface area, expansion-prone hematoma, and PLR were independently associated with PHE growth. Additionally, a risk nomogram model was established to predict the PHE growth in patients with ICH.

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Source
http://dx.doi.org/10.1016/j.clineuro.2024.108495DOI Listing

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