Ignite Creation Date:
2024-07-17 @ 11:31 AM
Last Modification Date:
2024-10-26 @ 3:32 PM
Study NCT ID:
NCT06464549
Status:
NOT_YET_RECRUITING
Last Update Posted:
2024-06-20
First Post:
2024-06-13
Brief Title:
Spontaneous Eye Blinking Evaluation for Cognitive Assessment of Individuals With Severe Acquired Brain Injury
Sponsor:
Alfonso Magliacano
Organization:
Fondazione Don Carlo Gnocchi Onlus
Study Overview
Official Title:
Spontaneous Eye Blinking Evaluation for Cognitive Assessment of Individuals With Severe Acquired Brain Injury
Status:
NOT_YET_RECRUITING
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
SEE-ABI
Brief Summary:
Assessment of consciousness and attention in individuals with severe Acquired Brain Injury sABI is crucial for planning rehabilitation but it is often hindered by coexisting sensory-motor andor cognitive-behavioural disorders
This project aims at evaluating the value of spontaneous eye blinking features to assess patients attentional abilities and to distinguish patients with unresponsive wakefulness syndrome UWS from those in minimally conscious state MCS
Patients will undergo an EEG-EOG recording at rest and during an auditory oddball task Eye blinking features on EOG will be analysed and compared to that of healthy individuals A machine-learning-based algorithm using blinking features for the diagnosis of patients with sABI will be studied and validated preliminarily
This project will help to stratify patients with sABI using easy-to-detect clinical markers supporting clinicians decision-making about patients management Additionally blinking patterns related to residual attentional abilities in patients emerged from disorders of consciousness will be investigated
This project aims at evaluating the value of spontaneous eye blinking features to assess patients attentional abilities and to distinguish patients with unresponsive wakefulness syndrome UWS from those in minimally conscious state MCS
Patients will undergo an EEG-EOG recording at rest and during an auditory oddball task Eye blinking features on EOG will be analysed and compared to that of healthy individuals A machine-learning-based algorithm using blinking features for the diagnosis of patients with sABI will be studied and validated preliminarily
This project will help to stratify patients with sABI using easy-to-detect clinical markers supporting clinicians decision-making about patients management Additionally blinking patterns related to residual attentional abilities in patients emerged from disorders of consciousness will be investigated
Detailed Description:
Overall aim to provide preliminary results on the value of spontaneous eye blinking features ie rate amplitude duration and variability in intervals between blinks which do not rely on voluntary behavioural responses for improving the assessment of attentional abilities and consciousness in patients with sABI
Specific aims
1 to confirm the diagnostic value of EBR in pDoC patients as in Magliacano et als 2021 study
2 to improve diagnostic accuracy of patients with prolonged Disorders of Consciousness pDoC by evaluating additional blinking features ie amplitude duration variability in intervals between blinks for discriminating patients in UWS from those in MCS or conscious
3 to explore the usefulness of eye blinking features analysis for assessing residual attentional abilities in full-conscious patients recovering from pDoC
4 prototyping a machine-learning-enabled pipeline for supporting consciousness diagnosis based on Eye Blink Rate EBR and EOG-derived features The interpretability and reliability aspects will be carefully evaluated to obtain a clinically usable solution for supporting diagnostic procedures and planning tailored cognitive rehabilitation
Overall this study is proposing a preliminary investigation with pilot samples of both healthy and test population for the analysis of EBR and EOG-derived biomarkers These results will lay the foundations for the development and validation of multifactorial decisional algorithms for patients diagnostic and prognostic stratification based on easily collectable clinical markers
This project has an observational cross-sectional design All patients with sABI consecutively admitted will be screened We plan to enrol a convenience test sample of 35 patients with sABI including 10 patients with pDoC 5 in UWS 5 in MCS and 25 patients who recovered full consciousness after sABI
A benchmark population of 20 healthy individuals balanced for age and sex with the patient sample will be also enrolled by means of word-of-mouth according to a snowball sampling This population will undergo anamnestic interview and neurological and primary cognitive examination for excluding history or presence of neurological disorders At study entry patients demographic eg age sex anamnestic eg aetiology time post-injury brain lesion location and clinical data will be collected Patients clinical diagnosis and cognitive functioning will be classified according to their best score on the repeated Coma Recovery Scale-Revised CRS-R and on Levels of Cognitive Functioning LCF respectively
Within 2 weeks from study entry each patient will attend an electroencephalogram-electrooculogram EEG-EOG recording session Eye blinking will be examined during a rest condition duration 8 min and during an active auditory oddball task duration 8 min consisting of randomly intermixed tones non-target 500 Hz overall probability 80 n312 target 1000 Hz overall probability 20 n78 presented with a 1-s inter-stimulus interval through headphones To complement clinical assessment the background activity on resting EEG and the presence of the P300 component on event-related potentials following the auditory oddball paradigm will be evaluated Patients consciousness CRS-R and cognitive functioning LCF levels will be gathered on the day of the EEG-EOG recording session and considered for statistical analysis
Control participants will undergo the same EEG-EOG recording as the patients For both participant groups blinks will be defined as a sharp positive peak followed by a shallow negative deflection in a time window of 400 ms on the EOG Moreover to prevent awareness of blink recording affects blink features throughout recording sessions participants will be never informed of the blinking recording but they will be encouraged to stay relaxed with their eyes open This procedure will be conducted regardless of the participant patient or control group
Biostatistical analyses will be exploited for the investigation of associations between EOG-derived biomarkers and residual attentional abilities in conscious sABI patients under different acquisition paradigms in response to Objective 3 Objective 4 will be addressed through the development of Machine Learning-based prototypes for the diagnosis of patients with pDoC using information derived from EOG signals complemented by EEG and clinical data The interpretability and error analyses will pose the premises for the identification of eventual covert patterns contained in EOG data
Specific aims
1 to confirm the diagnostic value of EBR in pDoC patients as in Magliacano et als 2021 study
2 to improve diagnostic accuracy of patients with prolonged Disorders of Consciousness pDoC by evaluating additional blinking features ie amplitude duration variability in intervals between blinks for discriminating patients in UWS from those in MCS or conscious
3 to explore the usefulness of eye blinking features analysis for assessing residual attentional abilities in full-conscious patients recovering from pDoC
4 prototyping a machine-learning-enabled pipeline for supporting consciousness diagnosis based on Eye Blink Rate EBR and EOG-derived features The interpretability and reliability aspects will be carefully evaluated to obtain a clinically usable solution for supporting diagnostic procedures and planning tailored cognitive rehabilitation
Overall this study is proposing a preliminary investigation with pilot samples of both healthy and test population for the analysis of EBR and EOG-derived biomarkers These results will lay the foundations for the development and validation of multifactorial decisional algorithms for patients diagnostic and prognostic stratification based on easily collectable clinical markers
This project has an observational cross-sectional design All patients with sABI consecutively admitted will be screened We plan to enrol a convenience test sample of 35 patients with sABI including 10 patients with pDoC 5 in UWS 5 in MCS and 25 patients who recovered full consciousness after sABI
A benchmark population of 20 healthy individuals balanced for age and sex with the patient sample will be also enrolled by means of word-of-mouth according to a snowball sampling This population will undergo anamnestic interview and neurological and primary cognitive examination for excluding history or presence of neurological disorders At study entry patients demographic eg age sex anamnestic eg aetiology time post-injury brain lesion location and clinical data will be collected Patients clinical diagnosis and cognitive functioning will be classified according to their best score on the repeated Coma Recovery Scale-Revised CRS-R and on Levels of Cognitive Functioning LCF respectively
Within 2 weeks from study entry each patient will attend an electroencephalogram-electrooculogram EEG-EOG recording session Eye blinking will be examined during a rest condition duration 8 min and during an active auditory oddball task duration 8 min consisting of randomly intermixed tones non-target 500 Hz overall probability 80 n312 target 1000 Hz overall probability 20 n78 presented with a 1-s inter-stimulus interval through headphones To complement clinical assessment the background activity on resting EEG and the presence of the P300 component on event-related potentials following the auditory oddball paradigm will be evaluated Patients consciousness CRS-R and cognitive functioning LCF levels will be gathered on the day of the EEG-EOG recording session and considered for statistical analysis
Control participants will undergo the same EEG-EOG recording as the patients For both participant groups blinks will be defined as a sharp positive peak followed by a shallow negative deflection in a time window of 400 ms on the EOG Moreover to prevent awareness of blink recording affects blink features throughout recording sessions participants will be never informed of the blinking recording but they will be encouraged to stay relaxed with their eyes open This procedure will be conducted regardless of the participant patient or control group
Biostatistical analyses will be exploited for the investigation of associations between EOG-derived biomarkers and residual attentional abilities in conscious sABI patients under different acquisition paradigms in response to Objective 3 Objective 4 will be addressed through the development of Machine Learning-based prototypes for the diagnosis of patients with pDoC using information derived from EOG signals complemented by EEG and clinical data The interpretability and error analyses will pose the premises for the identification of eventual covert patterns contained in EOG data
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None