Application of Artificial Intelligence to Predict Postoperative Delirium Based on Bayesian Neural Network

Status

Active, not recruiting

Phases

Early Phase 1

Study type

Observational

Source

ChiCTR

Registry ID

ChiCTR2200056234

Enrollment

Unknown

Registered

2022-02-02

Start date

2022-03-03

Completion date

Unknown

Last updated

2024-08-26

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

Conditions

Postoperative Delirium

Interventions

Gold Standard:Clinical outcome

Index test:A risk prediction model for postoperative delirium in elderly orthopedic surgery based on Bayesian neural network algorithm

Eligibility

Sex/Gender

All

Age

65 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Patients who underwent major orthopedic surgery in Ningbo Sixth Hospital from 2022 to 2023; 2. Agree to participate in this research; 3. ASA grade = 65 years old.

Exclusion criteria

Exclusion criteria: 1. Emergency surgery patients; 2. Patients with severe visual and hearing disorders can not complete the delirium assessment; 3. Patients with preoperative mental illness or personal history of mental illness.

Design outcomes

Primary

Measure	Time frame
Interleukin- 6;C-reaction protein;Procalcitonin;Neutrophil-lymphocyte ratio;Neuron-specific enolase;s-100ß protein;Serumamyloid A;Apolipoprotein E;Plasma hydrocortisone;Sensitivity, positive predictive value, negative predictive value;	—

Countries

China

Contacts

Public ContactGe Yeying

Ningbo Sixth Hospital

geyeying59198@163.com+86 18906627716

Outcome results

None listed

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