Abstract
Objective
To develop and internally validate the PROgnosis of functional recovery after Trauma (PRO-Trauma) prediction model.
Design
A prospective single-center longitudinal cohort study. Patients were assessed at 6 weeks and 12 months post-injury.
Methods
Patients that presented at the emergency department with an acute traumatic injury, were prompted for participation. Patients that completed the assessments at 6 weeks and 12 months post injury were included. Exclusion criteria: age <18, age > 65, pathologic fractures, injuries that resulted in severe neurologic deficits. The predicted outcome, functional recovery, was defined as a Short Musculoskeletal Function Assessment (SMFA-NL) Problems with Daily Activities (PDA) subscale
Results
A total of 246 patients were included, of which 104 (44%) showed functional recovery. The predictors in the final PRO-Trauma model were: living with partner, the number of chronic health conditions, SMFA-NL PDA subscale score at 6 weeks post-injury and length of stay in hospital. The apparent R-2 was 0.33 [0.33;0.34], the c-statistic was 0.79 [0.79;0.80]. Hosmer-Lemeshow test indicated good calibration (p = 0.92). Optimism-corrected R-2 was 0.28 [0.27;0.29] and the optimism-corrected Area Under the Curve was 0.77 [0.77;0.77].
Conclusion
The PRO-Trauma prediction model can be used to obtain valid predictions of attaining functional recovery after trauma at 12 months post-injury. The PRO-Trauma prediction model showed acceptable calibration and discrimination.
Original language | English |
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Article number | 0213510 |
Number of pages | 16 |
Journal | PLoS ONE |
Volume | 14 |
Issue number | 3 |
DOIs | |
Publication status | Published - 14-Mar-2019 |
Keywords
- FUNCTION ASSESSMENT QUESTIONNAIRE
- HEALTH LITERACY
- POPULATION
- VALIDITY
- INJURY
- IMPUTATION
- OUTCOMES
- DISEASE
- EUROPE
- SCORE
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Dataset: The development and internal validation of a model to predict functional recovery after trauma
Graaf, de, M. (Creator), Reininga, I. (Creator), Heineman, E. (Creator) & El Moumni, M. (Creator), University of Groningen, 3-Mar-2019
DOI: 10.6084/m9.figshare.6945719, https://doi.org/10.6084/m9.figshare.6945728
Dataset