Weekly pain trajectories among people with knee or hip osteoarthritis participating in a digitally delivered first-line exercise and education treatment
Kiadaliri, Ali LU
; Hörder, Helena
LU
; Lohmander, L Stefan
LU
and Dahlberg, Leif E
LU
(2024)
In Pain Medicine
25(4).
p.291-299
- Abstract
OBJECTIVE: Digital self-management programs are increasingly used in the management of osteoarthritis (OA). Little is known about heterogeneous patterns in response to these programs. We describe weekly pain trajectories of people with knee or hip OA over up to 52-week participation in a digital self-management program.
METHODS: Observational cohort study among participants enrolled between January 2019 and September 2021 who participated at least 4 and up to 52 weeks in the program (n = 16,274). We measured pain using Numeric Rating Scale (NRS 0-10) and applied latent class growth analysis to identify classes with similar trajectories. Associations between baseline characteristics and trajectory classes were examined using... (More)
OBJECTIVE: Digital self-management programs are increasingly used in the management of osteoarthritis (OA). Little is known about heterogeneous patterns in response to these programs. We describe weekly pain trajectories of people with knee or hip OA over up to 52-week participation in a digital self-management program.
METHODS: Observational cohort study among participants enrolled between January 2019 and September 2021 who participated at least 4 and up to 52 weeks in the program (n = 16,274). We measured pain using Numeric Rating Scale (NRS 0-10) and applied latent class growth analysis to identify classes with similar trajectories. Associations between baseline characteristics and trajectory classes were examined using multinomial logistic regression and dominance analysis.
RESULTS: We identified four pain trajectory classes: "mild-largely improved" (30%), "low moderate-largely improved" (34%), "upper moderate-improved" (24%), and "severe-persistent" (12%). For classes with decreasing pain, the most pain reduction occurred during first 20 weeks and was stable thereafter. Male sex, older age, lower BMI, better physical function, lower activity impairment, less anxiety/depression, higher education, knee OA, no walking difficulties, no wish for surgery and higher physical activity, all measured at enrolment, were associated with greater probabilities of membership in "mild-largely improved" class than other classes. Dominance analysis suggested that activity impairment followed by wish for surgery and walking difficulties were the most important predictors of trajectory class membership.
CONCLUSIONS: Our results highlight the importance of reaching people with OA for first-line treatment prior to developing severe pain, poor health status and a wish for surgery.
(Less)
- author
- Kiadaliri, Ali
LU
; Hörder, Helena
LU
; Lohmander, L Stefan
LU
and Dahlberg, Leif E
LU
- organization
- publishing date
- 2024-04
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Digital treatment, First-line treatment, Osteoarthritis, Pain, Trajectory, Sweden
- in
- Pain Medicine
- volume
- 25
- issue
- 4
- pages
- 9 pages
- publisher
- Oxford University Press
- external identifiers
-
- scopus:85189659399
- pmid:38127991
- ISSN
- 1526-2375
- DOI
- 10.1093/pm/pnad167
- language
- English
- LU publication?
- yes
- id
- 94dbbc46-97e8-4674-8499-a0d499d54a24
- date added to LUP
- 2024-01-04 11:36:01
- date last changed
- 2024-10-22 05:13:06
@article{94dbbc46-97e8-4674-8499-a0d499d54a24,
abstract = {{<p>OBJECTIVE: Digital self-management programs are increasingly used in the management of osteoarthritis (OA). Little is known about heterogeneous patterns in response to these programs. We describe weekly pain trajectories of people with knee or hip OA over up to 52-week participation in a digital self-management program.</p><p>METHODS: Observational cohort study among participants enrolled between January 2019 and September 2021 who participated at least 4 and up to 52 weeks in the program (n = 16,274). We measured pain using Numeric Rating Scale (NRS 0-10) and applied latent class growth analysis to identify classes with similar trajectories. Associations between baseline characteristics and trajectory classes were examined using multinomial logistic regression and dominance analysis.</p><p>RESULTS: We identified four pain trajectory classes: "mild-largely improved" (30%), "low moderate-largely improved" (34%), "upper moderate-improved" (24%), and "severe-persistent" (12%). For classes with decreasing pain, the most pain reduction occurred during first 20 weeks and was stable thereafter. Male sex, older age, lower BMI, better physical function, lower activity impairment, less anxiety/depression, higher education, knee OA, no walking difficulties, no wish for surgery and higher physical activity, all measured at enrolment, were associated with greater probabilities of membership in "mild-largely improved" class than other classes. Dominance analysis suggested that activity impairment followed by wish for surgery and walking difficulties were the most important predictors of trajectory class membership.</p><p>CONCLUSIONS: Our results highlight the importance of reaching people with OA for first-line treatment prior to developing severe pain, poor health status and a wish for surgery.</p>}},
author = {{Kiadaliri, Ali and Hörder, Helena and Lohmander, L Stefan and Dahlberg, Leif E}},
issn = {{1526-2375}},
keywords = {{Digital treatment; First-line treatment; Osteoarthritis; Pain; Trajectory; Sweden}},
language = {{eng}},
number = {{4}},
pages = {{291--299}},
publisher = {{Oxford University Press}},
series = {{Pain Medicine}},
title = {{Weekly pain trajectories among people with knee or hip osteoarthritis participating in a digitally delivered first-line exercise and education treatment}},
url = {{http://dx.doi.org/10.1093/pm/pnad167}},
doi = {{10.1093/pm/pnad167}},
volume = {{25}},
year = {{2024}},
}