Prospective validity of a clinical prediction rule for response to non-surgical multidisciplinary management of knee osteoarthritis in tertiary care: a multisite prospective longitudinal study.

Bone diseases Chronic Pain Knee Observational Study

Journal

BMJ open
ISSN: 2044-6055
Titre abrégé: BMJ Open
Pays: England
ID NLM: 101552874

Informations de publication

Date de publication:
23 Mar 2024
Historique:
medline: 24 3 2024
pubmed: 24 3 2024
entrez: 23 3 2024
Statut: epublish

Résumé

We tested a previously developed clinical prediction tool-a nomogram consisting of four patient measures (lower patient-expected benefit, lower patient-reported knee function, greater knee varus angle and severe medial knee radiological degeneration) that were related to poor response to non-surgical management of knee osteoarthritis. This study sought to prospectively evaluate the predictive validity of this nomogram to identify patients most likely to respond poorly to non-surgical management of knee osteoarthritis. Multisite prospective longitudinal study. Advanced practice physiotherapist-led multidisciplinary service across six tertiary hospitals. Participants with knee osteoarthritis deemed appropriate for trial of non-surgical management following an initial assessment from an advanced practice physiotherapist were eligible for inclusion. Baseline clinical nomogram scores were collected before a trial of individualised non-surgical management commenced. Clinical outcome (Global Rating of Change) was collected 6 months following commencement of non-surgical management and dichotomised to responder (a little better to a very great deal better) or poor responder (almost the same to a very great deal worse). Clinical nomogram accuracy was evaluated from receiver operating characteristics curve analysis and area under the curve, and sensitivity/specificity and positive/negative likelihood ratios were calculated. A total of 242 participants enrolled. Follow-up scores were obtained from 210 participants (87% response rate). The clinical nomogram demonstrated an area under the curve of 0.70 (p<0.001), with greatest combined sensitivity 0.65 and specificity 0.64. The positive likelihood ratio was 1.81 (95% CI 1.32 to 2.36) and negative likelihood ratio 0.55 (95% CI 0.41 to 0.75). The knee osteoarthritis clinical nomogram prediction tool may have capacity to identify patients at risk of poor response to non-surgical management. Further work is required to determine the implications for service delivery, feasibility and impact of implementing the nomogram in clinical practice.

Identifiants

pubmed: 38521532
pii: bmjopen-2023-078531
doi: 10.1136/bmjopen-2023-078531
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e078531

Informations de copyright

© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

Auteurs

Peter Window (P)

Physiotherapy Department, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia Peter.Window@health.qld.gov.au.
STARS Education and Research Alliance, Surgical Treatment and Rehabilitation Service, Metro North Health and University of Queensland, Brisbane, Queensland, Australia.

Maree Raymer (M)

Physiotherapy Department, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.

Steven M McPhail (SM)

Australian Centre for Health Services Innovation (AusHSI), Centre for Healthcare Transformation and School of Public Health & Social Work, Faculty of Health, QUT, Brisbane, Queensland, Australia.

Bill Vicenzino (B)

The University of Queensland School of Health and Rehabilitation Sciences, Saint Lucia, Queensland, Australia.

Andrew Hislop (A)

The University of Queensland School of Health and Rehabilitation Sciences, Saint Lucia, Queensland, Australia.
Physiotherapy Department, The Prince Charles Hospital, Chermside, Queensland, Australia.

Alex Vallini (A)

Physiotherapy Department, The Prince Charles Hospital, Chermside, Queensland, Australia.

Bula Elwell (B)

Physiotherapy Department, Ipswich Hospital, Ipswich, Queensland, Australia.

Helen O'Gorman (H)

Physiotherapy Department, Mater Hospital, South Brisbane, Queensland, Australia.

Ben Phillips (B)

Physiotherapy Department, Townsville Hospital, Townsville, Queensland, Australia.

Anneke Wake (A)

Physiotherapy Department, Townsville Hospital, Townsville, Queensland, Australia.

Adrian Cush (A)

Physiotherapy Department, Queen Elizabeth II Hospital, Coopers Plains, Queensland, Australia.

Stuart McCaskill (S)

Physiotherapy Department, Queen Elizabeth II Hospital, Coopers Plains, Queensland, Australia.

Linda Garsden (L)

Physiotherapy Department, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.

Miriam Dillon (M)

Physiotherapy Department, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.

Andrew McLennan (A)

Physiotherapy Department, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.

Shaun O'Leary (S)

Physiotherapy Department, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.
The University of Queensland School of Health and Rehabilitation Sciences, Saint Lucia, Queensland, Australia.

Classifications MeSH