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Construction of a machine learning model-based algorithm for perioperative sleep monitoring: a prospective cohort study

Construction of a machine learning model-based algorithm for perioperative sleep monitoring: a prospective cohort study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400089243
Enrollment
Unknown
Registered
2024-09-04
Start date
2024-09-10
Completion date
Unknown
Last updated
2024-09-09

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

Conditions

Perioperative sleep disorder

Interventions

Case series:None

Sponsors

Peking University First Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1. = 18 years old; 2. Patients who are to undergo elective surgery; 3. Consent to participate in the study.

Exclusion criteria

Exclusion criteria: 1. The expected duration of hospital stay is less than 48 hours; 2. The expected ending of anaesthesia is later than 20:00 on the day of surgery; 3. Taking sleep therapy medication such as benzodiazepines, melatonin, etc. within the last month; 4. Proposed cardiac surgery or neurosurgery; 5. Arrhythmias that may affect HRV analysis, such as persistent atrial fibrillation, frequent premature ventricular beats, sick sinus node syndrome, atrioventricular block; 6. Participating in other research projects.

Design outcomes

Primary

MeasureTime frame
Sensitivity and specificity of the sleep-wake state;

Secondary

MeasureTime frame
Sensitivity and specificity of wake stage in sleep architecture;Sensitivity and specificity of REM sleep stage in sleep architecture;Sensitivity and specificity of N1 sleep stage in sleep architecture;Sensitivity and specificity of N2 sleep stage in sleep architecture;Sensitivity and specificity of N3 sleep stage in sleep architecture;

Countries

China

Contacts

Public ContactDongliang Mu

Peking University First Hospital

mudongliang@bjmu.edu.cn+86 10 8357 5138

Outcome results

None listed

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