Residual Language Abilities Correlate With Diagnosis and Prognosis in Patients With Disorders of Consciousness

Evaluating residual consciousness and predicting outcomes in unresponsive patients pose significant clinical challenges. Language assessment is crucial for these patients, and language-based EEG paradigms have shown promise in aiding diagnosis and prognosis in patients with disorders of consciousness (DoC). However, current language-based EEG paradigms either require higher-order cognitive functions, thereby misidentifying some conscious patients as unconscious, or rely on automatic processing, which fails to capture residual consciousness in DoC.

Newly developed, simple phrase sequences combined with neural frequency tagging were used to explore a language paradigm tailored to a critical processing threshold. This paradigm was designed to reflect the dynamic process of consciousness in DoC, while requiring minimal cognitive load.

Our results showed that significant phrase-level EEG responses were observed in healthy subjects, MCS patients, and UWS patients in three conditions. Neural tracking of phrase structure showed a progressive decrease across three groups (healthy > MCS > UWS). Among the UWS patients, 52.38% (11 out of 21) and among the MCS patients, 45.83% (11 out of 24) exhibited significant ITPC at the syllable rate in at least one of the three conditions. Additionally, 38.10% (8 out of 21) of UWS patients and 33.33% (8 out of 24) of MCS patients demonstrated significant ITPC at the phrase rate. The language paradigm performance in this study was superior to that of other paradigms in detecting the proportion of residual language ability in DoC patients. Furthermore, cortical tracking at the phrase rate significantly correlated with 12-month outcomes and effectively classified patients according to their 12-month prognosis.

The simplified language assessment demonstrates strong potential to detect residual language ability in DoC patients and could potentially be used to detect residual consciousness and determine prognosis in unresponsive patients.