Published in

BMJ Publishing Group, BMJ Open, 11(8), p. e022802, 2018

DOI: 10.1136/bmjopen-2018-022802

Links

Tools

Export citation

Search in Google Scholar

Development and prospective external validation of a tool to predict poor recovery at 9 months after acute ankle sprain in UK emergency departments: the SPRAINED prognostic model

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

ObjectivesTo develop and externally validate a prognostic model for poor recovery after ankle sprain.Setting and participantsModel development used secondary data analysis of 584 participants from a UK multicentre randomised clinical trial. External validation used data from 682 participants recruited in 10 UK emergency departments for a prospective observational cohort.Outcome and analysisPoor recovery was defined as presence of pain, functional difficulty or lack of confidence in the ankle at 9 months after injury. Twenty-three baseline candidate predictors were included together in a multivariable logistic regression model to identify the best predictors of poor recovery. Relationships between continuous variables and the outcome were modelled using fractional polynomials. Regression parameters were combined over 50 imputed data sets using Rubin’s rule. To minimise overfitting, regression coefficients were multiplied by a heuristic shrinkage factor and the intercept re-estimated. Incremental value of candidate predictors assessed at 4 weeks after injury was explored using decision curve analysis and the baseline model updated. The final models included predictors selected based on the Akaike information criterion (p<0.157). Model performance was assessed by calibration and discrimination.ResultsOutcome rate was lower in the development (6.7%) than in the external validation data set (19.9%). Mean age (29.9 and 33.6 years), body mass index (BMI; 26.3 and 27.1 kg/m2), pain when resting (37.8 and 38.5 points) or bearing weight on the ankle (75.4 and 71.3 points) were similar in both data sets. Age, BMI, pain when resting, pain bearing weight, ability to bear weight, days from injury until assessment and injury recurrence were the selected predictors. The baseline model had fair discriminatory ability (C-statistic 0.72; 95% CI 0.66 to 0.79) but poor calibration. The updated model presented better discrimination (C-statistic 0.78; 95% CI 0.72 to 0.84), but equivalent calibration.ConclusionsThe models include predictors easy to assess clinically and show benefit when compared with not using any model.Trial registration numberISRCTN12726986; Results.