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Construction and Validation of a risk prediction Model for chronic pain in ICU Transferred Patients Based on Machine Learning

Construction and Validation of a risk prediction Model for chronic pain in ICU Transferred Patients Based on Machine Learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500113931
Enrollment
Unknown
Registered
2025-12-04
Start date
2025-12-04
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

Chronic ICU-related pain (CIRP)

Interventions

Modeling Group:None

Sponsors

The first affiliated hostipal of nanchang 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 stay in the ICU is >= 48 hours; 3.Patients whose conditions are stable and have been transferred to general wards, rehabilitation departments or transferred to other hospitals for treatment; 4.They can communicate normally, and family members or patients will use the wechat function on their mobile phones; 5.Sign the informed consent form and voluntarily participate in this study;

Exclusion criteria

Exclusion criteria: 1.Patients with cognitive impairment; 2.Patients with neurological diseases such as craniocerebral injury and brain tumors; 3.Patients with terminal malignant tumors or other major diseases whose life expectancy is no more than 6 months;

Design outcomes

Primary

MeasureTime frame
Numerical Rating Scale,NRS;

Secondary

MeasureTime frame
Tampa Scale of Kinesiophobia,TSK-11;Pain Catastrophizing Scale,PCS;Hospital Anxiety and Depression Scale,HADS;Fatigue-14,FS-14;

Countries

China

Contacts

Public ContactZhang Baozhen

The first affiliated hostipal of nanchang university

784243416@qq.com+86 138 7085 7392

Outcome results

None listed

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