Bostock, J

Byrne, C

Collins, G

Cooke, M

Goodacre, S

Gwilym, S

Hagan, D

Haywood, K

Hormbrey, P

Keene, D

Lamb, S

Sclussel, M

Thompson, J

Williams, M

Wilson, D

Health Technology Assessment

Background
Ankle sprains are very common injuries. Although recovery can occur within weeks, around
a third of patients have longer-term problems.

Objectives
To develop and externally validate a prognostic model for identifying people at increased risk
of poor outcome after an acute ankle sprain.

Design
Development of a prognostic model in a clinical trial cohort dataset and external validation in
a prospective cohort study.

Setting
Emergency departments in the UK.

Participants
Adults with an acute ankle sprain (within 7 days of injury).

Sample size
There were 584 clinical trial participants in the development dataset and 682 recruited for the
external validation study.

Predictors
Candidate predictor variables were chosen based on availability in the clinical data set, clinical
consensus, face-validity, a systematic review of the literature, data quality and plausibility of
predictiveness of the outcomes.

Main outcome measures
Models were developed to predict two composite outcomes representing poor outcome.
Outcome 1 was the presence of at least one of the following symptoms at 9 months after
injury: persistent pain, functional difficulty or lack of confidence. Outcome 2 included the
same symptoms as outcome 1 with the addition of recurrence of injury. Rates of poor
outcome in the external dataset were lower than in the development dataset, 7 vs. 20% for
outcome 1 and 16 vs. 24% for outcome 2, respectively.

Analysis
Multiple imputation was used to handle missing data. Logistic regression models, together
with multivariable fractional polynomials, were used to select variables and identify
respective transformations of continuous predictors that best predicted the outcome based on
a nominal alpha of 0.157, chosen to minimise over fitting. Predictive accuracy was evaluated
by assessing model discrimination (c-statistic) and calibration (flexible calibration plot).

Results
Performance of the prognostic models in development dataset:
Outcome 1 model combined c-statistic across the 50 imputed data sets was 0.74 (95%CI 0.70
to 0.79), with good model calibration across the imputed data sets. Outcome 2 model
combined c-statistic across the 50 imputed data sets was 0.70 (95%CI 0.65 to 0.74), with
good model calibration across the imputed data sets. Updating these models, which used
baseline data collected at the emergency department, with an additional variable at 4 weeks
after the injury (pain when bearing weight on the ankle) improved the discriminatory ability
(c-statistic 0.77; 95%CI 0.73 to 0.82 for outcome 1 and 0.75; 95%CI 0.71 to 0.80 for outcome
2) and calibration of both models.
Performance of the models in the external dataset:
The outcome 1 model combined c-statistic across the 50 imputed data sets was 0.72 (95%CI
0.66 to 0.79), with a calibration plot intercept of -0.71 (95%CI -0.98 to 0.44) and slope of
1.13 (95% CI 0.76 to 1.50) across the imputed data sets. The outcome 2 model combined cstatistic across the 50 imputed data sets was 0.63 (95%CI 0.58 to 0.69), with calibration plot
intercept of -0.08 (95%CI -0.27 to 0.11) and slope of 1.03 (95%CI 0.65 to 1.42) across the
imputed data sets. The updated models with the additional pain variable at 4 weeks had
improved discriminatory ability over the baseline models but not better calibration.

Conclusions
The SPRAINED prognostic models performed reasonably, and showed benefit when
compared to not using any model, so may assist clinical-decision making when managing and
advising ankle sprain patients in the emergency department setting. The models use
predictors that are simple to obtain.

Limitations
Data used to develop the prognostic models were from a randomised controlled trial so were
not originally intended to fulfil this aim. However, it was the best dataset available, with data
on the symptoms and clinical events of interest.
Future work
Further model refinement, including re-calibration or identifying additional predictors may be
required. Impact of implementing and using either model in clinical practice, in terms of
acceptability and uptake by clinicians, and on patient outcomes should be investigated.

Study registration
Current Controlled Trials ISRCTN12726986

Funding details
NIHR Health Technology Assessment programme

Byrne, Chris

Plymouth Electronic Archive and Research Library

Development and external validation of a prognostic model for predicting poor outcome in people with acute ankle sprains: the SPRAINED study.

https://pearl.plymouth.ac.uk/bitstream/10026.1/12219/1/SPR_HTA_Report_Master_V3.0_29Jan2018.pdf

Development and external validation of a prognostic model for predicting poor outcome in people with acute ankle sprains: the SPRAINED study.

Abstract

Similar works

Full text

Available Versions

Plymouth Electronic Archive and Research Library