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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)

28. september 2026 opdateret af: Boston Intelligent Medical Research Center, Shenzhen United Scheme Technology Co., Ltd.

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.

Studieoversigt

Status

Ikke rekrutterer endnu

Betingelser

Intervention / Behandling

Detaljeret beskrivelse

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.

Undersøgelsestype

Interventionel

Tilmelding (Anslået)

200

Fase

  • Ikke anvendelig

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiekontakt

  • Navn: Anmin Hu Shenzhen United Scheme Technology Co., Ltd.
  • Telefonnummer: +86 17318061949
  • E-mail: anmin@szus.org

Undersøgelse Kontakt Backup

  • Navn: Xiaofeng Chen Shenzhen Baoxing Hospital

Studiesteder

  • Kina
    • Guangdong
      • Shenzhen, Guangdong, Kina, 518020
        • Shenzhen Baoxing Hospital
        • Kontakt:
          • Xiaofeng Chen Shenzhen Baoxing Hospital
          • Telefonnummer: 0755-28746265
          • E-mail: us@szus.org

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

18 år til 80 år (Voksen, Ældre voksen)

Tager imod sunde frivillige

Ingen

Køn, der er berettiget til at studere

Alle

Beskrivelse

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.

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

  • Primært formål: Behandling
  • Tildeling: Randomiseret
  • Interventionel model: Parallel tildeling
  • Maskning: Enkelt

Våben og indgreb

Deltagergruppe / Arm
Intervention / Behandling
Eksperimentel: 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.
Andet: AI-Assisted Personalized Hyperbaric Oxygen Therapy

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.
Aktiv komparator: 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.
Andet: 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.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Change From Baseline in Coma Recovery Scale-Revised (CRS-R) Total Score at Week 12
Tidsramme: 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

Sekundære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Change From Baseline in Glasgow Coma Scale (GCS) Total Score at Week 12
Tidsramme: 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
Tidsramme: 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

Andre resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Discrimination Performance of the AI Model for Predicting Improvement in Consciousness State
Tidsramme: 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

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

Boston Intelligent Medical Research Center, Shenzhen United Scheme Technology Co., Ltd.

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Anslået)

1. december 2026

Primær færdiggørelse (Anslået)

1. juni 2027

Studieafslutning (Anslået)

30. september 2027

Datoer for studieregistrering

Først indsendt

28. september 2026

Først indsendt, der opfyldte QC-kriterier

28. september 2026

Først opslået (Faktiske)

2. oktober 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

2. oktober 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

28. september 2026

Sidst verificeret

1. september 2026

Mere information

Begreber relateret til denne undersøgelse

Nøgleord

Yderligere relevante MeSH-vilkår

Andre undersøgelses-id-numre

  • WINDO-CT-26001

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