Acute Hemorrhagic StrokeNCT06998082
AI-Driven Early Warning System for Perioperative Risks in Acute Hemorrhagic Stroke
An observational study of Acute Hemorrhagic Stroke, run by Beijing Tiantan Hospital at 1 site in China.
Trial summary
Acute hemorrhagic cerebrovascular disease is a life-threatening condition characterized by sudden onset, rapid progression, multiple complications, poor prognosis, and high mortality. It presents a significant public health burden. Read more about this study
- Who is it for?
- Ages 18 to 80 years
- Conditions the study is for
- Acute Hemorrhagic Stroke
- How many people
- 1,533 participants
- Where
- 1 siteChina
- Study dates
- 6 Jul 2025to 31 Dec 2028
- How long will I take part?
- 3 Months
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The investigators plan to recruit patients aged 18-80 years with acute hemorrhagic cerebrovascular disease from a minimum of three tertiary Grade A general hospitals.
Who may be able to join
- Patients aged 18 to 80 years.
- Diagnosis confirmed by preoperative imaging (CT or MRI) of one of the following conditions:
- Intracranial aneurysm
- Arteriovenous malformation (AVM)
- Hemorrhagic moyamoya disease
- Cavernous malformation
- Spontaneous intracerebral hemorrhage
- Undergoing surgery within seven days of symptom onset.
Who cannot join
- Patients who decline to provide informed consent.
- Patients enrolled in conflicting clinical studies.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
About this study
Official title: A Large Language Model-Driven Multimodal Early Warning Platform for Perioperative Complications in Acute Hemorrhagic Cerebrovascular Disease
Acute hemorrhagic cerebrovascular disease is a life-threatening condition characterized by sudden onset, rapid progression, multiple complications, poor prognosis, and high mortality. It presents a significant public health burden. During surgical interventions, precise risk stratification and effective perioperative management are crucial to mitigating intraoperative and postoperative complications, optimizing disease diagnosis, guiding severity assessment, and refining anesthesia strategies. Continuous real-time evaluation and dynamic perioperative adjustments are essential to minimize the influence of institutional variability and individual clinician-dependent decision-making. By harnessing big data-driven, evidence-based medical approaches, clinicians can enhance diagnostic accuracy and therapeutic precision, addressing a critical challenge in reducing morbidity and mortality in this patient population.
This study aims to develop a comprehensive multimodal perioperative database and leverage large language models (LLMs) for the efficient extraction of structured demographic and clinical data throughout the perioperative course. By integrating real-time hemodynamic monitoring parameters, the investigators seek to elucidate the relationship between perioperative hemodynamic patterns and the incidence of postoperative complications affecting major organ systems, including the brain, heart, kidneys, and lungs. The ultimate goal is to construct a multimodal fusion early-warning model capable of real-time, simultaneous prediction of multiple perioperative complications. This AI-driven platform will function as a risk stratification and alert system for organ-specific perioperative complications in patients with acute hemorrhagic cerebrovascular disease. By providing evidence-based insights for optimized perioperative management-encompassing early warning mechanisms, diagnostic support, and individualized therapeutic strategies-the system aims to improve clinical outcomes, reduce perioperative morbidity, and lower overall mortality.
- Conditions
- Acute Hemorrhagic Stroke
- Keywords
- Perioperative Complications, Artificial intelligence in Medicine, Acute hemorrhagic stroke
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Patients with acute hemorrhagic cerebrovascular disease | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
The primary outcome measures were postoperative complications involving the neurological, cardiac, pulmonary, and renal systems in patients with acute hemorrhagic cerebrovascular disease following surgical interventions.
Measured: Within 30 days after surgery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 May 2025
- Study start6 Jul 2025 (estimated)
- Primary completion31 Dec 2027 (estimated)
- Study completion31 Dec 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Acute Hemorrhagic StrokeStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,533 participants (estimated)
- Target duration
- 3 Months
Sponsor and investigators
- Lead sponsor
- Beijing Tiantan Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yuming Peng, Beijing Tiantan Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06998082
- Sponsor's protocol ID
- 20250401
- Status last verified
- Apr 2025
- First submitted
- 9 May 2025
- Last updated
- 31 May 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 31 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Large Language Model-Driven Multimodal Early Warning Platform for Perioperative Complications in Acute Hemorrhagic Cerebrovascular Disease
- ClinicalTrials.gov ID
- NCT06998082
- Acronym / sponsor ID
- 20250401
- Conditions
- Acute Hemorrhagic Stroke
- Keywords
- Perioperative Complications, Artificial intelligence in Medicine, Acute hemorrhagic stroke
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 1,533 participants (estimated)
- Lead sponsor
- Beijing Tiantan HospitalUniversity, hospital or other
- Study start
- 6 Jul 2025 (estimated)
- Primary completion
- 31 Dec 2027 (estimated)
- Study completion
- 31 Dec 2028 (estimated)
- First posted
- 31 May 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Acute hemorrhagic cerebrovascular disease is a life-threatening condition characterized by sudden onset, rapid progression, multiple complications, poor prognosis, and high mortality. It presents a significant public health burden. During surgical interventions, precise risk stratification and effective perioperative management are crucial to mitigating intraoperative and postoperative complications, optimizing disease diagnosis, guiding severity assessment, and refining anesthesia strategies. Continuous real-time evaluation and dynamic perioperative adjustments are essential to minimize the influence of institutional variability and individual clinician-dependent decision-making. By harnessing big data-driven, evidence-based medical approaches, clinicians can enhance diagnostic accuracy and therapeutic precision, addressing a critical challenge in reducing morbidity and mortality in this patient population.
This study aims to develop a comprehensive multimodal perioperative database and leverage large language models (LLMs) for the efficient extraction of structured demographic and clinical data throughout the perioperative course. By integrating real-time hemodynamic monitoring parameters, the investigators seek to elucidate the relationship between perioperative hemodynamic patterns and the incidence of postoperative complications affecting major organ systems, including the brain, heart, kidneys, and lungs. The ultimate goal is to construct a multimodal fusion early-warning model capable of real-time, simultaneous prediction of multiple perioperative complications. This AI-driven platform will function as a risk stratification and alert system for organ-specific perioperative complications in patients with acute hemorrhagic cerebrovascular disease. By providing evidence-based insights for optimized perioperative management-encompassing early warning mechanisms, diagnostic support, and individualized therapeutic strategies-the system aims to improve clinical outcomes, reduce perioperative morbidity, and lower overall mortality.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 3 Months
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patients with acute hemorrhagic cerebrovascular disease | – | – |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The investigators plan to recruit patients aged 18-80 years with acute hemorrhagic cerebrovascular disease from a minimum of three tertiary Grade A general hospitals.
Key inclusion criteria (8 listed)
- Patients aged 18 to 80 years.
- Diagnosis confirmed by preoperative imaging (CT or MRI) of one of the following conditions:
- Intracranial aneurysm
- Arteriovenous malformation (AVM)
- Hemorrhagic moyamoya disease
Key exclusion criteria (2 listed)
- Patients who decline to provide informed consent.
- Patients enrolled in conflicting clinical studies.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
The primary outcome measures were postoperative complications involving the neurological, cardiac, pulmonary, and renal systems in patients with acute hemorrhagic cerebrovascular disease following surgical interventions.
Time frame: Within 30 days after surgery
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 31 May 2025.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Acute Hemorrhagic Stroke, run by Beijing Tiantan Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 8 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 31 May 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact ming yu Peng, M.D, Ph.D (86-010-59976658, florapym766@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The primary outcome measures were postoperative complications involving the neurological, cardiac, pulmonary, and renal systems in patients with acute hemorrhagic cerebrovascular disease following surgical interventions. (time frame: Within 30 days after surgery). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 31 May 2025.