AI-Assisted Precision Hyperbaric Oxygen Therapy Based on Dynamic BIS-EEG Feedback for Patients With Disorders of Consciousness (AI-HBOT-DoC)
A Randomized Controlled Trial of Artificial Intelligence-Assisted Precision Hyperbaric Oxygen Therapy Based on Dynamic BIS-EEG Feedback in Patients With Disorders of Consciousness
Disorders of consciousness (DoC) are severe neurological conditions characterized by impaired awareness and reduced interaction with the environment. Although hyperbaric oxygen therapy (HBOT) may promote neurological recovery, the optimal treatment strategy for individual patients remains unclear.
This study aims to develop and validate an artificial intelligence-assisted precision decision support system for HBOT based on dynamic BIS-EEG brain functional feedback. The system will integrate clinical information, neuroimaging data, physiological parameters, consciousness assessments, and HBOT treatment characteristics.
Continuous BIS-EEG monitoring will be performed during different phases of HBOT, including compression, oxygen exposure, air breaks, decompression, and post-treatment recovery. Artificial intelligence models will analyze these dynamic brain functional responses to predict treatment effectiveness and support personalized HBOT management.
The primary outcome will be improvement in consciousness assessed by the Coma Recovery Scale-Revised (CRS-R). Secondary outcomes include changes in consciousness state, cognitive and functional recovery, and treatment-related adverse events.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
This prospective randomized controlled clinical study will evaluate whether an artificial intelligence-assisted precision hyperbaric oxygen therapy strategy improves clinical outcomes compared with conventional hyperbaric oxygen therapy in patients with disorders of consciousness.
Patients with disorders of consciousness, including vegetative state/unresponsive wakefulness syndrome and minimally conscious state, will receive standardized hyperbaric oxygen therapy. Multimodal clinical data will be collected, including demographic characteristics, disease etiology, disease duration, baseline consciousness assessment, neuroimaging findings, physiological parameters, BIS-EEG signals, and HBOT treatment parameters.
Dynamic BIS-EEG monitoring will be conducted throughout the entire HBOT session. Brain functional responses will be evaluated during the following phases: pre-treatment baseline, compression, hyperbaric oxygen exposure, air-break interval, repeated oxygen exposure, decompression, and post-treatment recovery.
The artificial intelligence system will integrate multimodal information using machine learning approaches to identify predictive biomarkers of neurological recovery and provide individualized decision support regarding HBOT treatment parameters, including treatment pressure, oxygen exposure duration, air-break strategy, treatment frequency, and treatment course.
The effectiveness of the AI-assisted decision support system will be evaluated by comparing predicted treatment responses with clinical outcomes. Clinical outcomes will include changes in Coma Recovery Scale-Revised (CRS-R) scores, consciousness state transitions, cognitive and functional recovery, and adverse events associated with HBOT.
This study is expected to provide an objective and personalized approach for optimizing HBOT management in patients with disorders of consciousness.
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Anmin Hu Shenzhen United Scheme Technology Co., Ltd.
- Phone Number: +86 17318061949
- Email: anmin@szus.org
Study Contact Backup
- Name: Xiaofeng Chen Shenzhen Baoxing Hospital
Study Locations
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Guangdong
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Shenzhen, Guangdong, China, 518020
- Shenzhen Baoxing Hospital
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Contact:
- Xiaofeng Chen Shenzhen Baoxing Hospital
- Phone Number: 0755-28746265
- Email: us@szus.org
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Adults aged 18 years or older.
- Diagnosis of disorders of consciousness, including vegetative state/unresponsive wakefulness syndrome (VS/UWS) or minimally conscious state (MCS).
- Disease duration of at least 28 days after the onset of brain injury.
- Stable medical condition suitable for hyperbaric oxygen therapy.
- Baseline consciousness assessment available using the Coma Recovery Scale-Revised (CRS-R).
- Ability to undergo standardized hyperbaric oxygen therapy sessions and complete clinical follow-up.
- Written informed consent obtained from the legally authorized representative.
Exclusion Criteria:
- Contraindications to hyperbaric oxygen therapy, including untreated pneumothorax or other conditions considered unsafe for HBOT.
- Severe cardiovascular, respiratory, or systemic instability.
- Uncontrolled epilepsy or frequent seizures affecting assessment.
- Severe infection or metabolic disorders that may influence consciousness assessment.
- Previous participation in another interventional clinical trial that may affect neurological outcomes.
- Incomplete baseline clinical data or inability to complete follow-up assessments.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Single
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Experimental: AI-Assisted Personalized Hyperbaric Oxygen Therapy
Participants will receive artificial intelligence-assisted precision hyperbaric oxygen therapy. The AI decision support system will integrate dynamic BIS-EEG brain functional feedback, clinical characteristics, neuroimaging findings, physiological parameters, and previous treatment responses to provide individualized recommendations for hyperbaric oxygen therapy parameters, including treatment pressure, oxygen exposure duration, air-break strategy, treatment frequency, and treatment course. |
Participants will receive hyperbaric oxygen therapy optimized by an artificial intelligence-assisted clinical decision support system. The system integrates dynamic BIS-EEG brain functional feedback, clinical characteristics, neuroimaging findings, physiological parameters, and previous treatment responses to provide individualized recommendations for hyperbaric oxygen therapy parameters, including treatment pressure, oxygen exposure duration, air-break strategy, treatment frequency, and treatment course. Final treatment decisions will be made by qualified physicians. |
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Active Comparator: Conventional Hyperbaric Oxygen Therapy
Participants will receive conventional hyperbaric oxygen therapy according to standard clinical protocols determined by treating physicians. Treatment parameters will be selected based on routine clinical practice without artificial intelligence-assisted recommendations. |
Participants will receive conventional hyperbaric oxygen therapy according to standard clinical protocols determined by treating physicians. Treatment parameters will be selected based on routine clinical practice without artificial intelligence-assisted recommendations. |
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Change From Baseline in Coma Recovery Scale-Revised (CRS-R) Total Score at Week 12
Time Frame: Baseline and 12 weeks after initiation of hyperbaric oxygen therapy
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The Coma Recovery Scale-Revised (CRS-R) will be used to assess the level of consciousness. The CRS-R total score ranges from 0 to 23, with higher scores indicating better neurobehavioral function and a higher level of consciousness. The change in CRS-R total score from baseline to Week 12 will be calculated for each participant and compared between the AI-assisted precision hyperbaric oxygen therapy group and the conventional hyperbaric oxygen therapy group. |
Baseline and 12 weeks after initiation of hyperbaric oxygen therapy
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Change From Baseline in Glasgow Coma Scale (GCS) Total Score at Week 12
Time Frame: Baseline and 12 weeks after initiation of hyperbaric oxygen therapy
|
The Glasgow Coma Scale (GCS) will be used to assess neurological responsiveness. The total score ranges from 3 to 15, with higher scores indicating better neurological responsiveness. Change from baseline to Week 12 will be compared between the AI-assisted precision hyperbaric oxygen therapy group and the conventional hyperbaric oxygen therapy group. |
Baseline and 12 weeks after initiation of hyperbaric oxygen therapy
|
|
Number of Participants With Hyperbaric Oxygen Therapy-Related Adverse Events
Time Frame: From the first hyperbaric oxygen therapy session through 7 days after the final treatment session
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The number and proportion of participants experiencing adverse events considered related to hyperbaric oxygen therapy will be recorded and compared between groups. Events of interest include middle-ear or sinus barotrauma, oxygen toxicity, seizures, pulmonary symptoms, hemodynamic instability, and other clinically significant treatment-related adverse events. |
From the first hyperbaric oxygen therapy session through 7 days after the final treatment session
|
Other Outcome Measures
Other Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Discrimination Performance of the AI Model for Predicting Improvement in Consciousness State
Time Frame: Prediction at baseline and during treatment for clinical outcome assessed at Week 12
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The predictive performance of the artificial intelligence model will be evaluated for predicting improvement to a higher consciousness state at Week 12. Discrimination will be assessed using the area under the receiver operating characteristic curve (AUROC). An AUROC of 0.5 indicates no discrimination, whereas values closer to 1.0 indicate better discrimination. |
Prediction at baseline and during treatment for clinical outcome assessed at Week 12
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
- Neurologic Manifestations
- Brain Diseases
- Central Nervous System Diseases
- Nervous System Diseases
- Mental Disorders
- Neurobehavioral Manifestations
- Neurocognitive Disorders
- Brain Damage, Chronic
- Unconsciousness
- Pathological Conditions, Signs and Symptoms
- Signs and Symptoms
- Consciousness Disorders
- Persistent Vegetative State
Other Study ID Numbers
Other Study ID Numbers
- WINDO-CT-26001
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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