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Prediction of Poor Outcome in Intracerebral Hemorrhage Based on Computed Tomography Markers
Chaonan Du1, Boxue Liu1, Mingfei Yang2
1Graduate School, Qinghai University, Xining, China.
Insights
Computed tomography (CT) markers can predict poor outcomes in patients with intracerebral hemorrhage (ICH). Specific CT signs like hypodensities, black hole sign, and island sign are key indicators for predicting ICH prognosis.
Area of Science:
- Neurology
- Radiology
- Medical Imaging
Background:
- Intracerebral hemorrhage (ICH) is a severe type of stroke with high mortality.
- Accurate prediction of ICH outcomes is crucial for patient management.
Purpose of the Study:
- To develop and validate a predictive model for poor outcomes in ICH patients using computed tomography (CT) markers.
- To identify specific CT imaging features associated with ICH prognosis.
Main Methods:
- Retrospective observational cohort study across three medical centers.
- Analysis of CT markers including hypodensities, hematoma density, blend sign, black hole sign, island sign, midline shift, and hematoma volume.
- Development and validation of a nomogram using logistic regression and AUC analysis.
Main Results:
- Hypodensities, black hole sign, island sign, midline shift, and baseline hematoma volume were independently associated with poor ICH outcomes.
- The predictive model achieved an AUC of 0.75 in internal validation and 0.74 in external validation.
- The nomogram demonstrated good calibration in both development and validation cohorts.
Conclusions:
- CT markers, specifically hypodensities, black hole sign, and island sign, show potential in predicting poor outcomes for ICH patients within 90 days.
- The developed nomogram provides a validated tool for prognostic assessment in ICH.
Introduction:
Intracerebral hemorrhage (ICH) is the most fatal type of stroke worldwide. Herein, we aim to develop a predictive model based on computed tomography (CT) markers in an ICH cohort and validate it in another cohort.
Methods:
This retrospective observational cohort study was conducted in 3 medical centers in China. The values of CT markers, including hypodensities, hematoma density, blend sign, black hole sign, island sign, midline shift, baseline hematoma volume, and satellite sign, in predicting poor outcome were analyzed by logistic regression analysis. A nomogram was developed based on the results of multivariate logistic regression analysis in development cohort. Area under curve (AUC) and calibration plot were used to assess the accuracy of nomogram in this development cohort and validate in another cohort.
Results:
A total of 1,498 patients were included in this study. Multivariate logistic regression analysis indicated that hypodensities, black hole sign, island sign, midline shift, and baseline hematoma volume were independently associated with poor outcome in development cohort. The AUC was 0.75 (95% confidence interval [CI]: 0.73-0.76) in the internal validation with development cohort and 0.74 (95% CI: 0.72-0.75) in the external validation with validation cohort. The calibration plot in development and validation cohort indicated that the nomogram was well calibrated.
Conclusions:
CT markers of hypodensities, black hole sign, and island sign might predict poor outcome of ICH patients within 90 days.
