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Original Articles

The trajectories of overall disability in the first 5 years after moderate and severe traumatic brain injury

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Pages 329-335 | Received 03 Nov 2015, Accepted 28 Oct 2016, Published online: 17 Jan 2017
 

ABSTRACT

Primary objectives: To assess longitudinal trajectories of overall disability after moderate-to-severe traumatic brain injury (TBI) and to examine whether those trajectories could be predicted by socio-demographic and injury characteristics.

Methods: Demographics and injury characteristics of 105 individuals with moderate-to-severe TBI were extracted from medical records. At the 1-, 2-, and 5-year follow-ups, TBI-related disability was assessed by the GOSE. A hierarchical linear model (HLM) was used to examine functional outcomes up to 5 years following injury and whether those outcomes could be predicted by: time, gender, age, relationship, education, employment pre-injury, occupation, GCS, cause of injury, length of post-traumatic amnesia (PTA), CT findings and injury severity score, as well as the interactions between each of these predictors and time.

Results: Higher GOSE trajectories (lower disability) were predicted by younger age at injury and shorter PTA, as well as by the interaction terms of time*PTA and time*employment. Those who had been employed at injury decreased in disability over time, while those who had been unemployed increased in disability.

Conclusion: The study results support the view that individual factors generally outweigh injury-related factors as predictors of disability after TBI, except for PTA.

Acknowledgements

The authors would like to thank all the patients for their participation. Special thanks to Nini Hammergren for assistance with patient registrations during the first 2 years post-injury and Tone Jerstad, neuroradiologist, for the CT assessments.

Declaration of interest

The authors report no conflicts of interest. This study was funded by grant from The Institute of Health and Society, CHARM (Research Centre for Habilitation and Rehabilitation Models and Services), Faculty of Medicine, University of Oslo.

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