| Coma & Chronic Disorders of Consciousness | Rare Neurological Diseases  

Multimodal Prediction of 3- and 12-Month Outcomes in ICU Patients with Acute Disorders of Consciousness

In this, to our knowledge, first prospective multimodal cohort study including 123 ICU patients with acute DoC from various underlying conditions, we show that machine learning algorithms applied to EEG and fMRI features obtained soon after ICU admission can assist in the prediction of 3-month functional outcome, whereas 12-month outcome can only be predicted by EEG features. We also show that the model based on clinical features can predict both outcomes, with highest accuracy for predicting 12-month functional outcome. Thus, we have confirmed readily available independent predictive clinical variables of time to favorable recovery, with the clinical model performing overall as good as EEG models in predicting both outcomes.

In intensive care unit (ICU) patients with coma and other disorders of consciousness (DoC), outcome prediction is key to decision-making regarding prognostication, neurorehabilitation, and management of family expectations. Therefore, the Consciousness in Neurocritical Care Cohort Study Using Electroencephalography and Functional Magnetic Resonance Imaging investigates ICU patients with acute DoC due to traumatic and nontraumatic brain injuries, using electroencephalography (EEG) (resting-state and passive paradigms), functional magnetic resonance imaging (fMRI) (resting-state) and systematic clinical examinations.
We previously presented results for a subset of patients (n = 87) concerning prediction of consciousness levels in the ICU. Now we report 3- and 12-month outcomes in an extended cohort (n = 123).
Between April 2016 and July 2021, we enrolled 123 patients (mean age 51 years, 42% women). Of 82 (66%) ICU survivors, 3- and 12-month outcomes were available for 79 (96%) and 77 (94%), respectively. EEG features predicted both 3-month (AUC 0.79 [95% confidence interval (CI) 0.77–0.82]) and 12-month (AUC 0.74 [95% CI 0.71–0.77]) outcomes. fMRI features appeared to predict 3-month outcome (accuracy 0.69–0.78) both alone and when combined with some EEG features (accuracies 0.73–0.84) but not 12-month outcome (larger sample sizes needed). Independent clinical predictors of time to favorable outcome were younger age (hazard ratio [HR] 1.04 [95% CI 1.02–1.06]), traumatic brain injury (HR 1.94 [95% CI 1.04–3.61]), command-following abilities at admission (HR 2.70 [95% CI 1.40–5.23]), initial brain imaging without severe pathological findings (HR 2.42 [95% CI 1.12–5.22]), improving consciousness in the ICU (HR 5.76 [95% CI 2.41–15.51]), and favorable visual-graded EEG (HR 2.47 [95% CI 1.46–4.19])

Key Points:

  • EEG features in combination, as well as the EEG Synek score as an individual model, predicted both 3-and 12-month functional outcomes,whereas all models based on fMRI FC measures could only predict 3-month outcome
  • initial brain imaging without severe pathological findings, ability to follow commands during ICU admission, improving consciousness level during the ICU stay, and favorable visual EEG grading all independently predicted shorter time to favorable functional outcome

References:

Amiri, M., Raimondo, F., Fisher, P.M. et al. Multimodal Prediction of 3- and 12-Month Outcomes in ICU Patients with Acute Disorders of Consciousness. Neurocrit Care 40, 718–733 (2024). https://doi.org/10.1007/s12028-023-01816-z

Co-author:
Nicolas Lejeune, Coma Science Group, GIGA-Consciousness, University of Liège
Anna Estraneo, IRCCS, Don Gnocchi Foundation, Florence and Sant’Angelo dei Lombardi

Publish on behalf of the Scientific Panel on Coma and chronic disorders of consciousness

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