Abstract
Prognostication following hypoxic ischemic encephalopathy (brain injury) is important for clinical management. The aim of this exploratory study is to use a decision tree model to find clinical and MRI associates of severe disability and death in this condition. We evaluate clinical model and then the added value of MRI data. The inclusion criteria were as follows: age ≥17 years, cardio-respiratory arrest, and coma on admission (2003-2011). Decision tree analysis was used to find clinical [Glasgow Coma Score (GCS), features about cardiac arrest, therapeutic hypothermia, age, and sex] and MRI (infarct volume) associates of severe disability and death. We used the area under the ROC (auROC) to determine accuracy of model. There were 41 (63.7% males) patients having MRI imaging with the average age 51.5 ± 18.9 years old. The decision trees showed that infarct volume and age were important factors for discrimination between mild to moderate disability and severe disability and death at day 0 and day 2. The auROC for this model was 0.94 (95% CI 0.82-1.00). At day 7, GCS value was the only predictor; the auROC was 0.96 (95% CI 0.86-1.00). Our findings provide proof of concept for further exploration of the role of MR imaging and decision tree analysis in the early prognostication of hypoxic ischemic brain injury.
Highlights
Hypoxic coma carries the highest mortality rate among the different causes of coma with only around 30% of patients admitted to ICU ever regaining awareness [1]
There are very few publications in the literature that address the role of MR imaging in the prediction of coma outcome [6, 7]
We evaluated the potential of MR imaging to improve outcome prediction in the era of therapeutic hypothermia in cardiac arrest patients, using the framework of decision tree analysis
Summary
Hypoxic coma carries the highest mortality rate among the different causes of coma with only around 30% of patients admitted to ICU ever regaining awareness [1]. There is increasing interest in this condition given the changing landscape of hypoxic ischemic brain injury in the context of therapeutic hypothermia [2,3,4]. A recent meta-analysis from our group reported that the clinical examination at day 2 was the best predictor of outcome following coma above that provided by sensory evoked potential and electroencephalography [5]. Prognostication following hypoxic ischemic encephalopathy (brain injury) is important for clinical management. The aim of this exploratory study is to use a decision tree model to find clinical and MRI associates of severe disability and death in this condition. We evaluate clinical model and the added value of MRI data
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