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.
調査の概要
状態
詳細な説明
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.
研究の種類
入学 (推定)
段階
- 適用できない
連絡先と場所
研究連絡先
- 名前：Anmin Hu Shenzhen United Scheme Technology Co., Ltd.
- 電話番号：+86 17318061949
- メール：anmin@szus.org
研究連絡先のバックアップ
- 名前：Xiaofeng Chen Shenzhen Baoxing Hospital
研究場所
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Guangdong
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Shenzhen、Guangdong、中国、518020
- Shenzhen Baoxing Hospital
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コンタクト：
- Xiaofeng Chen Shenzhen Baoxing Hospital
- 電話番号：0755-28746265
- メール：us@szus.org
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参加基準
適格基準
就学可能な年齢
健康ボランティアの受け入れ
受講資格のある性別
説明
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.
研究計画
研究はどのように設計されていますか？
デザインの詳細
- 主な目的：処理
- 割り当て：ランダム化
- 介入モデル：並列代入
- マスキング：独身
武器と介入
参加者グループ / アーム |
介入・治療 |
|---|---|
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実験的：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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アクティブコンパレータ：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. |
この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Change From Baseline in Coma Recovery Scale-Revised (CRS-R) Total Score at Week 12
時間枠：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
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二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Change From Baseline in Glasgow Coma Scale (GCS) Total Score at Week 12
時間枠：Baseline and 12 weeks after initiation of hyperbaric oxygen therapy
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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
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Number of Participants With Hyperbaric Oxygen Therapy-Related Adverse Events
時間枠：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
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その他の成果指標
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Discrimination Performance of the AI Model for Predicting Improvement in Consciousness State
時間枠：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
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協力者と研究者
研究記録日
主要日程の研究
研究開始 (推定)
一次修了 (推定)
研究の完了 (推定)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
追加の関連 MeSH 用語
その他の研究ID番号
- WINDO-CT-26001
個々の参加者データ (IPD) の計画
個々の参加者データ (IPD) を共有する予定はありますか?
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