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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.

연구 개요

상태

아직 모집하지 않음

정황

개입 / 치료

상세 설명

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.

연구 유형

중재적

등록 (추정된)

200

단계

  • 해당 없음

연락처 및 위치

이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.

연구 연락처

  • 이름: Anmin Hu Shenzhen United Scheme Technology Co., Ltd.
  • 전화번호: +86 17318061949
  • 이메일: anmin@szus.org

연구 연락처 백업

  • 이름: Xiaofeng Chen Shenzhen Baoxing Hospital

연구 장소

    • Guangdong
      • Shenzhen, Guangdong, 중국, 518020
        • Shenzhen Baoxing Hospital
        • 연락하다:
          • Xiaofeng Chen Shenzhen Baoxing Hospital
          • 전화번호: 0755-28746265
          • 이메일: us@szus.org

참여기준

연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.

자격 기준

공부할 수 있는 나이

18년 (성인, 고령자)

건강한 자원 봉사자를 받아들입니다

아니

연구 대상 성별

모두

설명

Inclusion Criteria:

  1. Adults aged 18 years or older.
  2. Diagnosis of disorders of consciousness, including vegetative state/unresponsive wakefulness syndrome (VS/UWS) or minimally conscious state (MCS).
  3. Disease duration of at least 28 days after the onset of brain injury.
  4. Stable medical condition suitable for hyperbaric oxygen therapy.
  5. Baseline consciousness assessment available using the Coma Recovery Scale-Revised (CRS-R).
  6. Ability to undergo standardized hyperbaric oxygen therapy sessions and complete clinical follow-up.
  7. Written informed consent obtained from the legally authorized representative.

Exclusion Criteria:

  1. Contraindications to hyperbaric oxygen therapy, including untreated pneumothorax or other conditions considered unsafe for HBOT.
  2. Severe cardiovascular, respiratory, or systemic instability.
  3. Uncontrolled epilepsy or frequent seizures affecting assessment.
  4. Severe infection or metabolic disorders that may influence consciousness assessment.
  5. Previous participation in another interventional clinical trial that may affect neurological outcomes.
  6. Incomplete baseline clinical data or inability to complete follow-up assessments.

공부 계획

이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.

연구는 어떻게 설계됩니까?

디자인 세부사항

  • 주 목적: 치료
  • 할당: 무작위
  • 중재 모델: 병렬 할당
  • 마스킹: 하나의

무기와 개입

참가자 그룹 / 팔
개입 / 치료
실험적: 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.

활성 비교기: 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.

연구는 무엇을 측정합니까?

주요 결과 측정

결과 측정
측정값 설명
기간
Change From Baseline in Coma Recovery Scale-Revised (CRS-R) Total Score at Week 12
기간: Baseline and 12 weeks after initiation of hyperbaric oxygen therapy

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

2차 결과 측정

결과 측정
측정값 설명
기간
Change From Baseline in Glasgow Coma Scale (GCS) Total Score at Week 12
기간: 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
기간: From the first hyperbaric oxygen therapy session through 7 days after the final treatment session

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

기타 결과 측정

결과 측정
측정값 설명
기간
Discrimination Performance of the AI Model for Predicting Improvement in Consciousness State
기간: Prediction at baseline and during treatment for clinical outcome assessed at Week 12

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

공동 작업자 및 조사자

여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.

스폰서

연구 기록 날짜

이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.

연구 주요 날짜

연구 시작 (추정된)

2026년 12월 1일

기본 완료 (추정된)

2027년 6월 1일

연구 완료 (추정된)

2027년 9월 30일

연구 등록 날짜

최초 제출

2026년 9월 28일

QC 기준을 충족하는 최초 제출

2026년 9월 28일

처음 게시됨 (실제)

2026년 10월 2일

연구 기록 업데이트

마지막 업데이트 게시됨 (실제)

2026년 10월 2일

QC 기준을 충족하는 마지막 업데이트 제출

2026년 9월 28일

마지막으로 확인됨

2026년 9월 1일

추가 정보

이 연구와 관련된 용어

기타 연구 ID 번호

  • WINDO-CT-26001

개별 참가자 데이터(IPD) 계획

개별 참가자 데이터(IPD)를 공유할 계획입니까?

미정

약물 및 장치 정보, 연구 문서

미국 FDA 규제 의약품 연구

아니

미국 FDA 규제 기기 제품 연구

아니

이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .