Background: Identification of intracerebral hemorrhage (ICH) patients at risk of substantial hematoma expansion (SHE) could facilitate the selection of candidates likely to benefit from therapies aiming to minimize ICH growth. We aimed to develop a grading tool that can be quickly used during the hyperacute phase to predict the risk of SHE.
Methods: We reviewed data from 237 spontaneous ICH patients who had baseline head CT scan within 12 h of symptom onset and follow-up CT during the following 72 h. We performed logistic regression analyses to determine the predictors of SHE (defined as an absolute increase in ICH volume >6 ml or an increase >33% on follow-up CT). We identified 6 predictors; each was assigned a point in the graphic interface of a nomogram which was used to construct a scoring system-The Hematoma Expansion Prediction (HEP) Score, varying from 0 to 18 points. We evaluated the ability of the model to predict the probability of SHE using c-statistics.
Results: SHE occurred in 74 patients (31.2%). The final model to predict SHE included 6 variables: time from onset to baseline CT (<3 vs. 3-12 h), history of dementia, current smoking, antiplatelet use, Glasgow Comma Scale score, and the presence of subarachnoid hemorrhage on baseline scan. The model had satisfactory discrimination ability with a bootstrap corrected c-index of 0.76 (95% CI 0.69-0.83) and good calibration. Patients with a total HEP score >3 were at greatest risk for SHE.
Conclusions: We developed and internally validated a novel nomogram and an easy to use score which accurately predict the probability of SHE based on six easily obtainable parameters. This could be useful for treatment decision and stratification. External prospective validation of the HEP score is warranted before its application to other populations.