Keene DJ1, Vadher K1, Willett K1, Mistry D2, Costa M1, Collins GS1, Lamb SE1
1University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Oxford, United Kingdom, 2University of Warwick, Warwick Clinical Trials Unit, Coventry, United Kingdom
Background: Prognosis after ankle fracture in older people is worse than for younger adults but there is limited evidence about which combination of factors predict functional outcome. A prognostic model has the potential to inform anticipated recovery, and identify people who may benefit from additional monitoring or rehabilitation.
Purpose: We aimed to develop a prognostic model to predict functional outcomes 6 months after ankle fracture in people aged ≥60 years using post-treatment and 6-week follow-up data.
Methods:
Study design: Prognostic model development and internal validation.
Participants: 618 AIM clinical trial participants (ISRCTN04180738), aged 60-96 years, 459/618 (74%) female, treated surgically or conservatively for unstable ankle fracture.
Predictors: Injury and socio-demographic variables collected at baseline (acute hospital setting) and 6-week follow-up (clinic).
Outcome measures: 6-month post-injury (primary) self-reported ankle function, using the Olerud and Molander Ankle Score (OMAS), and (secondary) Timed Up and Go (TUG) test by blinded assessor.
Missing data: Single imputation.
Statistical analysis: Multivariable linear regression models were built using backwards (stepwise) elimination to predict OMAS or TUG, using baseline variables or baseline and 6-week follow-up variables.
Internal validation: Bootstrapping.
Results: The OMAS baseline data model included: alcohol per week (units), post-injury EQ-5D-3L VAS, sex, pre-injury walking distance and walking aid use, smoking status, and perceived health status. The baseline/6-week data model included the same baseline variables, minus EQ-5D-3L VAS, plus five 6-week predictors: radiological malalignment, injured ankle dorsiflexion and plantarflexion range of motion, and 6-week OMAS and EQ-5D-3L. The models explained approximately 23% and 26% of the outcome variation, respectively. Similar baseline and baseline/6-week data models to predict TUG explained around 30% and 32% of the outcome variation, respectively.
Conclusion(s): Prognostic models using commonly recorded clinical data did not accurately predict self-reported or objectively measured ankle function.
Implications: These findings question the value of these clinical data to inform prognostic decision-making. Further research into potential predictors (e.g. psychosocial factors) is recommended.
Keywords: Ankle fracture, Prognosis, Fragility fracture
Funding acknowledgements: This report is independent research supported by the National Institute for Health Research (NIHR Post Doctoral Fellowship, PDF-2016-09-056).
Purpose: We aimed to develop a prognostic model to predict functional outcomes 6 months after ankle fracture in people aged ≥60 years using post-treatment and 6-week follow-up data.
Methods:
Study design: Prognostic model development and internal validation.
Participants: 618 AIM clinical trial participants (ISRCTN04180738), aged 60-96 years, 459/618 (74%) female, treated surgically or conservatively for unstable ankle fracture.
Predictors: Injury and socio-demographic variables collected at baseline (acute hospital setting) and 6-week follow-up (clinic).
Outcome measures: 6-month post-injury (primary) self-reported ankle function, using the Olerud and Molander Ankle Score (OMAS), and (secondary) Timed Up and Go (TUG) test by blinded assessor.
Missing data: Single imputation.
Statistical analysis: Multivariable linear regression models were built using backwards (stepwise) elimination to predict OMAS or TUG, using baseline variables or baseline and 6-week follow-up variables.
Internal validation: Bootstrapping.
Results: The OMAS baseline data model included: alcohol per week (units), post-injury EQ-5D-3L VAS, sex, pre-injury walking distance and walking aid use, smoking status, and perceived health status. The baseline/6-week data model included the same baseline variables, minus EQ-5D-3L VAS, plus five 6-week predictors: radiological malalignment, injured ankle dorsiflexion and plantarflexion range of motion, and 6-week OMAS and EQ-5D-3L. The models explained approximately 23% and 26% of the outcome variation, respectively. Similar baseline and baseline/6-week data models to predict TUG explained around 30% and 32% of the outcome variation, respectively.
Conclusion(s): Prognostic models using commonly recorded clinical data did not accurately predict self-reported or objectively measured ankle function.
Implications: These findings question the value of these clinical data to inform prognostic decision-making. Further research into potential predictors (e.g. psychosocial factors) is recommended.
Keywords: Ankle fracture, Prognosis, Fragility fracture
Funding acknowledgements: This report is independent research supported by the National Institute for Health Research (NIHR Post Doctoral Fellowship, PDF-2016-09-056).
Topic: Orthopaedics; Orthopaedics; Older people
Ethics approval required: No
Institution: National Research Ethics Service
Ethics committee: National Research Ethics Service Oxfordshire Committee
Reason not required: The original clinical trial approvals included use of data for further studies. All participants gave written informed consent for data to be used.
All authors, affiliations and abstracts have been published as submitted.
