Skip to content

Classifying and Predicting Long-term Pain and Function in Older Adults

A New Approach to Classifying and Predicting Long-term Bothersome Pain and Functional Decline in Older Adults

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04864223
Enrollment
6783
Registered
2021-04-28
Start date
2018-08-01
Completion date
2020-07-31
Last updated
2021-04-28

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

Conditions

Chronic Pain, Pain

Keywords

older adults, chronic pain, function, physical performance

Brief summary

This project will use novel methods to detect clinically meaningful subgroups of older adults based on long-term trajectories of bothersome pain and function. It will then identify older adults at high risk of experiencing poor long-term pain and function. Anticipated results will provide new insights into long-term patterns of pain and function across the aging process and identify potential predictors of each trajectory.

Detailed description

The long-term goal of this planned line of research is to reduce the burden of pain and maximize function in older adults as they age. This line of research will begin by completing the following Aims: Aim 1) Identify and describe clinically meaningful long-term trajectories of bothersome pain and functional decline in a population-based sample of older adults and Aim 2) Estimate the association between candidate prognostic factors typically available in electronic health records and long-term bothersome pain and function trajectories to inform the development of eventual risk prediction models. This will be a retrospective cohort study using longitudinal data from the population-based National Health and Aging Trends Study (NHATS). This project will use novel methods to identify clinically meaningful subgroups of older adults based on long-term trajectories of bothersome pain and function. Group-based trajectory modeling (GBTM) is a novel method to model dynamic phenomena such as pain and function. Older adults at high risk of experiencing poor long-term pain and function outcomes will be identified by leveraging potential prognostic factors typically available in electronic health records or administrative data. It is anticipated that our results will provide new insights into long-term patterns of pain and function across the aging process and identify potential predictors of each trajectory.

Interventions

None listed

Sponsors

University of Pittsburgh
CollaboratorOTHER
University of Washington
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
65 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* community-dwelling older adults from Round 1 of the NHATS cohort

Exclusion criteria

* participants who are non-ambulatory (require a wheelchair or scooter for mobility) at Round 1

Design outcomes

Primary

MeasureTime frameDescription
Bothersome Pain6 yearsQuestion: In the last month, have you been bothered by pain? Dichotomous response of yes or no
Physical Performance6 yearsShort Physical Performance Battery (SPPB). Scored from 0=worst to 12=best based on 3 performance tests: walking, chairs stands, and balance tasks

Secondary

MeasureTime frameDescription
Activity Limitations Due to Pain6 yearsQuestion: In the last month, has pain ever limited your activities? Dichotomous response of yes or no
Functional Capacity6 yearsSelf-reported physical capacity. A composite score of self-reported ability to do six pairs of activities: walking 3 or 6 blocks independently, climbing 10 or 20 stairs, lifting and carrying 10 or 20 pounds, bending over or kneeling down, reaching overhead or placing a heavy object overhead, and grasping small objects or opening a jar. Scores range 0-12 with higher scores indicating greater capacity to perform these activities.

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026