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Development and Validation of a Machine Learning-Based Model for Predicting the Risk of Delirium in Mechanically Ventilated ICU Patients

Development and Validation of a Machine Learning-Based Model for Predicting the Risk of Delirium in Mechanically Ventilated ICU Patients

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500113510
Enrollment
Unknown
Registered
2025-12-01
Start date
2025-12-01
Completion date
Unknown
Last updated
2025-12-08

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

Conditions

ICU delirium

Interventions

Delirium observation group:None

Sponsors

Jiangning Hospital Affiliated with Nanjing Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: (1) age >=18 years old; (2) The length of ICU stay >=24 hours; (3) receiving mechanical ventilation >=24 hours; (4) Informed consent was obtained from the family members.

Exclusion criteria

Exclusion criteria: (1) History of mental illness or psychiatric disorders; (2) Pre-existing delirium prior to ICU admission; (3) Persistent coma or deep sedation following ICU admission, defined as RASS score = -3; (4) Patients receiving palliative care.

Design outcomes

Primary

MeasureTime frame
Assessment method for confusion in ICU patients;Acute Physiology and Chronic Health Status Score II;Richmond Agitation and Sedation Scale score;—

Countries

China

Contacts

Public ContactLv Silu

Jiangning Hospital Affiliated with Nanjing Medical University

lvsilu0915@163.com+86 138 1412 3510

Outcome results

None listed

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