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Functional isolation within the cerebral cortex in the vegetative state: a nonlinear method to predict clinical
Marco Sarà1, Francesca Pistoia, Patrizio Pasqualetti
1Post Coma and Rehabilitation Care Unit, San Raffaele Cassino, Cassino, Italy. marco.sara@sanraffaele.it
Neurorehabilitation and Neural Repair
|October 19, 2010
Summary
Predicting outcomes for patients in a vegetative state (VS) is challenging. Lower neural complexity, measured by approximate entropy (ApEn) in EEG, indicates poorer prognosis, while higher complexity suggests potential recovery.
Area of Science:
- Neuroscience
- Complexity Science
- Clinical Neurology
Background:
- Prognosis determination for patients in a persistent vegetative state (VS) remains a significant clinical challenge.
- Consciousness relies on complex neural networks; their dysfunction may lead to reduced complexity and predictability in neural outputs.
- Approximate entropy (ApEn) quantifies the unpredictability of time series data, reflecting system complexity.
Purpose of the Study:
- To test the hypothesis that reduced neural complexity, indicated by lower ApEn, is associated with poor outcomes in VS patients.
- To investigate the utility of nonlinear dynamics methods, specifically ApEn analysis of EEG, for predicting patient outcomes.
- To explore the relationship between neural network derangement, functional isolation, and altered brain output predictability in VS.
Main Methods:
- Electroencephalography (EEG) recordings and approximate entropy (ApEn) computation were performed on 38 VS patients and 40 healthy controls.
- Patients underwent clinical assessments using the Extended Glasgow Outcomes Coma Scale (E-GOS) and Coma Recovery Scale-Revised (CRS-R) at admission.
- Clinical reassessment occurred at 6 months post-initial evaluation to determine patient outcomes.
Main Results:
- Mean ApEn values were significantly lower in VS patients (0.73 ± 0.12) compared to healthy controls (0.97 ± 0.02; P < .001).
- Patients with the lowest ApEn values predominantly experienced mortality (n=14) or remained in VS (n=12).
- Patients exhibiting higher ApEn values showed better outcomes, including minimally conscious state (n=5), partial recovery (n=4), or full recovery (n=3).
Conclusions:
- Lower dynamic correlates of neural residual complexity, as measured by ApEn, are associated with unfavorable outcomes in vegetative patients.
- ApEn analysis of EEG signals shows promise as a tool for predicting prognosis in patients with disorders of consciousness.
- These findings support the link between neural complexity and the potential for recovery from a vegetative state.
