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Dynamic Prediction of Pain Catastrophizing Risk in Older Chronic Pain Patients

Development of a Dynamic Nomogram Prediction Model for Pain Catastrophizing in Elderly Patients with Chronic Pain Based on Machine Learning

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500105716
Enrollment
Unknown
Registered
2025-07-09
Start date
2024-05-14
Completion date
Unknown
Last updated
2025-07-14

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

Conditions

Elderly Patients with Chronic Pain

Interventions

Observation group:None

Sponsors

Fifth Affiliated Hospital, Sun Yat-Sen University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
60 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1.Meeting the diagnostic criteria of the Clinical Guidelines for Chronic Pain Management: Pain persisting or recurring for =3 months, with a minimum frequency of once per week, accompanied by an unpleasant sensory and emotional experience. 2.age>=60 years; 3.Normal vision and hearing, can cooperate with research; 4.Be clear in consciousness and be able to communicate normally; 5.Informed consent and voluntary participation in this study;

Exclusion criteria

Exclusion criteria: 1.Patients with cancer pain; 2.People with severe brain organic diseases may have a history of various mental illnesses; 3.Pain caused by traumatic events such as car accidents and amputations; 4.Patients participating in psychological intervention programs;

Design outcomes

Primary

MeasureTime frame
Area Under the Curve (AUC) of the Prediction Model;

Secondary

MeasureTime frame
Influencing Factors of Pain Catastrophizing;Social Support Scale Rating;Positive and Negative Emotion Scale Rating;Pain Catastrophic Scale Score;

Countries

China

Contacts

Public ContactZhang Jiali

Fifth Affiliated Hospital, Sun Yat-Sen University

zhjli@mail.sysu.edu.cn+86 756 2528756

Outcome results

None listed

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