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Predicting perioperative risks via machine learning

Predicting perioperative risks via machine learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR1900021522
Enrollment
Unknown
Registered
2019-02-25
Start date
2019-02-28
Completion date
Unknown
Last updated
2019-03-04

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

Conditions

Surgical Emergency

Interventions

Case series:Nil

Sponsors

Huashan Hospital, Fudan University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Aged more than 16 years; 2. Spontaneous intracerebral hemorrhage; 3. Systolic blood pressure not lower than 140 mmHg, diastolic blood pressure not lower than 90 mmHg; 4. Admission less than 8 hours after the onset of symptoms and signs.

Exclusion criteria

Exclusion criteria: 1. Hemorrhage due to vascular malformation, intracranial aneurysm or brain tumor apoplexy; 2. Patients with brain herniation; 3. Patients with the requirement of emergency operation to evacuate the intracerebral hematoma; 4. Pregnant women.

Design outcomes

Primary

MeasureTime frame
coagulation abnormalities;hypokalemia;acute renal failure;cardiovascular complications;cardiovascular complications;—

Contacts

Public ContactPengfei Fu

Huashan Hospital, Fudan University

yirui.sun@live.cn+86 021 52887732

Outcome results

None listed

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