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Constructing machine learning algorithm models to predict postoperative sleep disorders based on demographic characteristics and perioperative factors

Constructing machine learning algorithm models to predict postoperative sleep disorders based on demographic characteristics and perioperative factors

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300071807
Enrollment
Unknown
Registered
2023-05-25
Start date
2023-06-01
Completion date
Unknown
Last updated
2023-06-12

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

Conditions

Sleep Disorders

Interventions

sleep disorder group and non-sleep disorder group:None

Sponsors

The First Affiliated Hospital of Nanjing Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 75 Years

Inclusion criteria

Inclusion criteria: 1. ASA Grade I~III; 2. Age >= 18 years old; 3. Informed consent to this study.

Exclusion criteria

Exclusion criteria: 1. Those who refuse to cooperate with the survey or are delirious and unable to cooperate with the completion of PSQI questionnaire and ISI questionnaire; 2. During the investigation, there were intervention measures affecting sleep such as taking sleeping pills; 3. Patients with the severe respiratory system, cardiovascular system diseases or neuropsychiatric disorders; 4. Patients who were sent to ICU for continuous close monitoring after surgery.

Design outcomes

Primary

MeasureTime frame
ISI score;sleep quality;—

Countries

China

Contacts

Public ContactCunming Liu

Department of Anesthesia and Perioperative Medicine, The First Affiliated Hospital of Nanjing Medical University

cunmingliu@njmu.edu.cn+86 139 5189 0866

Outcome results

None listed

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