Search

Diagnostic and prognostic decision-making in patients with Disorders of Consciousness (DoC) is challenging. It has been suggested that spontaneous eye blink rate is an index of patients’ level of consciousness easy to detect in clinical practice. Further blinking features (i.e., amplitude, duration, variability in intervals between blinks) may change as a function of cognitive load, but have not been investigated in patients with DoC.This multicentre, longitudinal study aims at exploring the diagnostic and prognostic value of spontaneous eye blinking features in DoC.Eight European medical institutions will enrol consecutively admitted adult patients with DoC. Within two weeks from study entry demographic, anamnestic and clinical data will be collected. Moreover, patients will undergo two 20-minute EEG-EOG recordings at rest, to collect blinking features and EEG activity. A clinical follow-up will be performed after 6 months. A group of healthy individuals will be enrolled for reference.Possible differences in blink features between patients and the reference group, differences across diagnostic sub-groups, and correlations between blinking features and clinical outcome will be investigated.The results of this study might help clinicians to reduce misdiagnosis rate in DoC and provide useful information for prognostication and care pathway plan. [ABSTRACT FROM AUTHOR]

Background and purpose: The prognosis of prolonged (28 days to 3 months post‐onset) disorders of consciousness (pDoC) due to anoxic brain injury is uncertain. The present study aimed to evaluate the long‐term outcome of post‐anoxic pDoC and identify the possible predictive value of demographic and clinical information. Method: This is a systematic review and meta‐analysis. The rates of mortality, any improvement in clinical diagnosis, and recovery of full consciousness at least 6 months after severe anoxic brain injury were evaluated. A cross‐sectional approach searched for differences in baseline demographic and clinical characteristics between survivors and non‐survivors, patients improved versus not improved, and patients who recovered full consciousness versus not recovered. Results: Twenty‐seven studies were identified. The pooled rates of mortality, any clinical improvement and recovery of full consciousness were 26%, 26% and 17%, respectively. Younger age, baseline diagnosis of minimally conscious state versus vegetative state/unresponsive wakefulness syndrome, higher Coma Recovery Scale Revised total score, and earlier admission to intensive rehabilitation units were associated with a significantly higher likelihood of survival and clinical improvement. These same variables, except time of admission to rehabilitation, were also associated with recovery of full consciousness. Conclusions: Patients with anoxic pDoC might improve over time up to full recovery of consciousness and some clinical characteristics can help predict clinical improvement. These new insights could support clinicians and caregivers in the decision‐making on patient management. [ABSTRACT FROM AUTHOR]

Prognosis of prolonged Disorders of Consciousness (pDoC) is influenced by patients' clinical diagnosis and Coma Recovery Scale-Revised (CRS-R) total score. We compared the prognostic accuracy of a novel Consciousness Domain Index (CDI) with that of clinical diagnosis and CRS-R total score, for recovery of full consciousness at 6-, 12-, and 24-months post-injury. The CDI was obtained by a combination of the six CRS-R subscales via an unsupervised machine learning technique. We retrospectively analyzed data on 143 patients with pDoC (75 in Minimally Conscious State; 102 males; median age = 53 years; IQR = 35; time post-injury = 1–3 months) due to different etiologies enrolled in an International Brain Injury Association Disorders of Consciousness Special Interest Group (IBIA DoC-SIG) multicenter longitudinal study. Univariate and multivariate analyses were utilized to assess the association between outcomes and the CDI, compared to clinical diagnosis and CRS-R. The CDI, the clinical diagnosis, and the CRS-R total score were significantly associated with a good outcome at 6, 12 and 24 months. The CDI showed the highest univariate prediction accuracy and sensitivity, and regression models including the CDI provided the highest values of explained variance. A combined scoring system of the CRS-R subscales by unsupervised machine learning may improve clinical ability to predict recovery of consciousness in patients with pDoC. [ABSTRACT FROM AUTHOR]