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Development and Validation of a Machine Learning-Based Prediction Model for Postoperative Delirium Subtypes in Aortic Dissection

Development and Validation of a Machine Learning-Based Prediction Model for Postoperative Delirium Subtypes in Aortic Dissection

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500103403
Enrollment
Unknown
Registered
2025-05-28
Start date
2025-06-06
Completion date
Unknown
Last updated
2025-06-02

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Aortic dissection

Interventions

Data Acquisition Group:None

Sponsors

Su Bei People's Hospital of Jiangsu Province
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 90 Years

Inclusion criteria

Inclusion criteria: (1) Diagnosed with aortic dissection (Stanford type A or B) and undergoing surgical treatment (2) 18 years of age or older, without communication barriers, cognitive impairment, or mental disorders; (3) Transferred to the Cardiac and Vascular ICU for monitoring within 24 hours post-surgery. (4) Willing to participate in the study and sign an informed consent form. (5) The patient has complete pre-operative, intra-operative, and post-operative electronic medical records, including vital signs, laboratory tests, and delirium assessment data. (6) Postoperative survival time: survival for at least 72 hours after surgery to observe the occurrence and subtype classification of delirium.

Exclusion criteria

Exclusion criteria: (1) Pre-existing severe neuropsychiatric disorders. (2) Patients with hearing, intellectual, or expressive impairments that prevent normal communication. (3) Lack of key data (such as intraoperative monitoring records, postoperative biochemical indicators, etc.). (4) Pregnant or breastfeeding patients. (5) Patients with advanced malignant tumors or a short expected lifespan.

Design outcomes

Primary

MeasureTime frame
Delirium;

Countries

China

Contacts

Public ContactWugang

Su Bei People's Hospital of Jiangsu Province

q125346534@163.com+86 180 5106 7631

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026