Department of Exercise Sciences

The PREP algorithm predicts potential for upper limb recovery after stroke

Cathy M. Stinear, P. Alan Barber, Matthew Petoe, Samir Anwar and Winston D. Byblow
Published in Brain (2012) 135, 2527-2535


Predicting motor recovery after stroke in individual patients is difficult. Accurate prognosis would enable realistic rehabilitation goal-setting and more efficient allocation of resources.



To test and refine an algorithm for predicting the potential for recovery of upper limb function after stroke.



  • 40 patients were prospectively enrolled within 3 days of ischaemic stroke (Figure 2).
  • Shoulder abduction and finger extension strength were graded 72h after stroke onset to compute a shoulder abduction and finger extension score (SAFE score).
  • Transcranial magnetic stimulation (TMS) was used to assess the functional integrity of descending motor pathways to the affected upper limb.
  • Diffusion-weighted magnetic resonance imaging (Diffusion MRI) was used to assess the structural integrity of the posterior limbs of the internal capsules.
  • Patients were then separated into four predicted outcome categories: Complete, Notable, Limited and None according to the PREP algorithm: their SAFE score; responses to TMS and the diffusion MRI results (Figure 1).
  • A cluster analysis was used to independently group patients according to Action Research Arm Test score at 12 weeks, for comparison with predications from the PREP algorithm.



  • There was excellent correspondence between the cluster analysis of Action Research Arm Test score at 12 weeks and predictions made with PREP algorithm (Figure 4B). Patients A and B had the potential for ‘complete’ recovery, however they achieved a ‘notable’ recovery due to advanced age (Patient A) and shoulder pain (Patient B). Patient C’s predicted potential for ‘notable’ recovery wasn’t realized, probably due to extensive premotor cortex damage.
  • The algorithm had positive predictive power of 88%, negative predictive power of 83% and sensitivity of 73%.



This study provides strong preliminary data in support of the PREP algorithm for the prognosis of upper limb recovery in individual patients. PREP may enable tailored planning of rehabilitation and more accurate stratification of patients in clinical trials (Table 1).




We would like to thank Patricia Bennett, Marie-Clare Smith, Alison Elston and Anne Ronaldson for assistance with participant recruitment and data collection. This research was funded by Health Research Council of New Zealand; Julius Brendel Trust and Stroke Foundation of New Zealand (Northern Region).