AIMS: To investigate the ability of 30-min electroencephalogram (EEG), short-latency somatosensory evoked potentials (SEPs) and brain computed tomography (CT) to predict poor neurological outcome (persistent vegetative state or death) at 6 months in comatose survivors of cardiac arrest within 24 h from the event.
METHODS: Prospective multicentre prognostication study in seven hospitals. SEPs were graded according to the presence and amplitude of their cortical responses, EEG patterns were classified according to the American Clinical Neurophysiology Society terminology and brain oedema on brain CT was measured as grey/white matter (GM/WM) density ratio. Sensitivity for poor outcome prediction at 100% specificity was calculated for the three tests individually and in combination. None of the patients underwent withdrawal of life-sustaining treatments before the index event occurred.
RESULTS: A total of 346/396 patients were included in the analysis. At 6 months, 223(64%) had poor neurological outcome; of these, 68 were alive in PVS. Bilaterally absent/absent-pathological amplitude cortical SEP patterns, a GM/WM ratio<1.21 on brain CT and isoelectric/burst-suppression EEG patterns predicted poor outcome with 100% specificity and sensitivities of 57.4%, 48.8% and 34.5%, respectively. At least one of these unfavourable patterns was present in 166/223 patients (74.4% sensitivity). Two unfavourable patterns were simultaneously present in 111/223 patients (49.7% sensitivity), and three patterns in 38/223 patients (17% sensitivity).
CONCLUSIONS: In comatose resuscitated patients, a multimodal approach based on results of SEPs, EEG and brain CT accurately predicts poor neurological outcome at 6 months within the first 24 h after cardiac arrest.
The authors have prospectively developed a prognostic model integrating neuro-imaging and neuro-functional tests to early (within 24 hours) predict outcomes in survivors of cardiac arrest. However, the prognostic model permits poor neurological outcomes (death or persistent vegetative state) but does not to discriminate among lower levels of neurological disability.
After cardiac arrest, the recovery of neurological function is of utmost importance to the family. This paper provides important evidence for clinicians that EEG and brain CT can help predict these patient outcomes.
This is relevant for hospitalist who practice in open ICU, comanage ICU patients or who work with long term care facilities where those patients ultimately end up discharged to. While this is not a common scenario, it would be useful and helpful for the practicing internist given the high specificity. If able to predict early on, this would be a high value care tool as it would save money given the high cost of institutionalizing those patients, as well as it would alleviate the emotional burden of family members as they anxiously wait the uncertainty of outcome of their loved ones.
This essentially shows what we already know - if you have a finding that predicts a bad outcome, you will likely have a bad outcome. If you are a patient without a predictor of poor outcome, we can’t prognosticate very well.