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NCT06998082
AI-Driven Early Warning System for Perioperative Risks in Acute Hemorrhagic Stroke
trial in Acute Hemorrhagic Stroke in 1,533 participants. Not yet recruiting.
31 December 2027
Quick facts
| Lead sponsor | Beijing Tiantan Hospital |
|---|---|
| Status | Not yet recruiting |
| Study type | OBSERVATIONAL |
| Enrollment | 1,533 |
| Start date | 6 July 2025 |
| Primary completion | 31 December 2027 |
| Estimated completion | 31 December 2028 |
| Sites | 1 location across China |
Conditions studied
- Acute Hemorrhagic Stroke — all drugs for Acute Hemorrhagic Stroke →
Sponsor
Beijing Tiantan Hospital
Who can join
Adults 18 to 80, any sex, with Acute Hemorrhagic Stroke. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
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.
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
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Related trials
Other recruiting trials for Acute Hemorrhagic Stroke
Currently open trials in the same condition.
- NCT06061185 — Multimodal Computed Tomography in Patients With Acute Hemorrhagic Stroke · recruiting
Other Beijing Tiantan Hospital trials
Trials by the same sponsor.
- NCT07341854 — Dexamethasone Palmitate for Postoperative Pain · NA · not yet recruiting
- NCT07527013 — Stratified Blood Pressure Management Strategy After Endovascular Treatment for Acute Ischemic Stroke · Phase 3 · not yet recruiting
- NCT07520370 — Effect of Perioperative Ulinastatin on Postoperative Stroke in Patients With Brain Tumor · NA · not yet recruiting
- NCT07526987 — Efficacy and Safety of Minocycline in Patients With Acute Ischaemic Stroke Receiving Intravenous Thrombolysis · Phase 3 · not yet recruiting
- NCT07591207 — The Efficacy and Safety of Loxoprofen Sodium Patch in Relieving Postoperative Pain After Laparoscopic Surgery · NA · not yet recruiting
Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT06998082 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by Beijing Tiantan Hospital
- Last refreshed: 31 May 2025
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