Predictive Modelling - SCI
As many of you will know I am a member of the American Congress of Rehabilitation Medicine. My membership includes access to the Archives of Physical Medicine and Rehabilitation.
With the caveat that this is only my interpretation of research undertaken by persons far more intelligent than I, it was interesting to read newly published research from the University of Pittsburgh:
Longitudinal Prediction of Quality-of-Life Scores and Locomotion in Individuals with Traumatic Spinal Cord Injury [Shivayogi V. Hiremath PhD et al – 2017;98:2385-92].
The US has a National Spinal Cord Injury Database co-ordinated by the NSCISC which collects data on @ 15% of the spinal cord injuries that occur annually within that country. It is a phenomenal bank of data which has been collected since 1973. I know that some medico-legal experts express reticence over the applicability of US data but, nevertheless, it seems to me that if we were ever truly serious about trying to build a robust system of predictive modelling for SCI then the US Database would be an ideal place to start.
In this research the authors filtered the Database to identify individuals who had FIM data for the mode of locomotion at discharge and at least one of three time points: 1, 5 or 10 years post discharge.
Changes in the method of locomotion were compared amongst over 10,000 participants. Individuals who transitioned from ambulatory (A) to wheelchair (W) reported consistently lower quality of life and higher depression scores than individuals who were consistent at WW.
It was speculated that marginal ambulators [at discharge] may see it as a failure if they could not progress and that transitioning [to a wheelchair] in the years after injury made it more difficult to psychologically adjust to wheelchair use. There was a recommendation that prior to discharge marginal ambulators should receive a focus on wheelchair skills / use in order minimise any feelings of regression.
There is perhaps nothing surprising in this? In many ways it strikes me that the research confirms what we would instinctively believe to be the case in any event (if we had thought about the problem).
For more information, please contact Ian Slater, Partner on 0161 603 5066 or email Ian.email@example.com.
This information is intended as a general discussion surrounding the topics covered and is for guidance purposes only. It does not constitute legal advice and should not be regarded as a substitute for taking legal advice. DWF is not responsible for any activity undertaken based on this information.