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Development of a Machine Learning Model to Predict Perioperative Blood Transfusion in Patients With Aneurysmal Subarachnoid Hemorrhage

Development of a Machine Learning Model to Predict Perioperative Blood Transfusion in Patients With Aneurysmal Subarachnoid Hemorrhage

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600120632
Enrollment
Unknown
Registered
2026-03-17
Start date
2026-04-01
Completion date
Unknown
Last updated
2026-03-23

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

Conditions

Aneurysmal subarachnoid hemorrhage (aSAH)

Interventions

Observation group:NA

Sponsors

The Affiliated Hospital of Southwest Medical University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1.The diagnosis of aSAH was confirmed by Computed Tomography Angiography (CTA) or Digital Subtraction Angiography (DSA).

Exclusion criteria

Exclusion criteria: 1. Refusal of blood transfusion or receipt of only non-red blood cell transfusions; 2. SAH caused by other diseases such as cerebral vascular malformations, moyamoya disease, or trauma; 3. History of other neurological diseases such as intracranial tumors or stroke; 4. Admission more than 48 hours after the onset of initial symptoms; 5. Transfer from other medical centers; 6. Incomplete records of the included variables; 7. Death within three days after admission.

Design outcomes

Primary

MeasureTime frame
Perioperative allogeneic red blood cell transfusion situation;—

Countries

China

Contacts

Public ContactZhi Cai

The Affiliated Hospital of Southwest Medical University

1065128659@qq.com+86 830 316 5741

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Apr 3, 2026