Assessment of Brain Computed Tomography as a Practical Way to Predict Neurological Outcomes in Post-Cardiac Arrest Survivors

Abstract

Objective: To evaluate whether a visual inspection of ischemic changes in brain computed tomography (CT) images, which is very practical in clinical settings, could predict neurological outcomes in post-cardiac arrest survivors. Materials and Methods: The authors retrospectively reviewed medical records and brain CT images of 62 patients who remained comatose after surviving cardiac arrest and had undergone a CT scan within 24 hours to seven days. Neurological outcomes at one month were assessed using the Cerebral Performance Category (CPC). The CPC scores of 1-2 and 3-5 referred to good and poor neurological outcomes, respectively. Findings from the inspection of the images were graded into grade 1 for absence of acute ischemic change, grade 2 for decreased attenuation of the grey matter in some brain region(s), and grade 3 for diffused loss of grey-white matter differentiation or apparent brain swelling. An experienced neurologist and a consensus group of four pre-clerkship medical students, blinded to the neurological outcomes, evaluated the grade of ischemic changes in CT images. Results: Positive correlations were observed between CPC and CT grading by both the neurologist (ρ=0.76, 95% CI 0.63 to 0.90, p<0.001) and medical students (ρ=0.57, 95% CI 0.38 to 0.77, p<0.001). The CT grading of 2 or more by the neurologist could predict poor neurological outcomes with specificity of 1.00, sensitivity of 0.89, and receiver operating characteristic (ROC) AUC of 0.94 (95% CI 0.89 to 1.00). The evaluation by medical students showed an ROC AUC of 0.80 (95% CI 0.64 to 0.96). Conclusion: The simple visual inspection of ischemic changes in brain CT images showed a high diagnostic accuracy and could be a practical method for predicting neurological outcomes in post-cardiac arrest survivors. Keywords: Cardiac arrest; Post-cardiac arrest ischemic brain injury; Neurological outcomes; Computerized tomography