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Construction and evaluation of delirium early warning model for patients with one-lung ventilation after operation based on machine learning

Construction and evaluation of delirium early warning model for patients with one-lung ventilation after operation based on machine learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300068095
Enrollment
Unknown
Registered
2023-02-07
Start date
2023-02-07
Completion date
Unknown
Last updated
2023-05-15

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:Confusion Assessment Method(CAM)score >= 20
Index test:Model based on Logistic and machine learning.

Sponsors

Li Huili Hospital, Ningbo Medical Center
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Inclusion criteria: from November 2020 to December 2023, patients with ASA grade I to II and planned to undergo thoracoscopic pulmonary nodulectomy under general anesthesia.

Exclusion criteria

Exclusion criteria: Serious damage to important organs; Those who have suffered from mental diseases or are taking psychotropic drugs; People with cerebrovascular disease, history of craniocerebral injury and communication impairment such as visual and hearing impairment.

Design outcomes

Primary

MeasureTime frame
Area under ROC curve;—

Secondary

MeasureTime frame
sensitivity;Specificity;Accuracy;Joden index;—

Countries

China

Contacts

Public ContactFang Ping

Li Huili Hospital of Ningbo Medical Center

549934608@qq.com+86 139 8930 9825

Outcome results

None listed

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