To explore the contribution that individual characteristics (including stroke and aphasia profiles) and intervention components make to the natural history of recovery and rehabilitation of people with aphasia following stroke and to inform future research design by utilising pre-existing IPD aphasia data to explore:
- What is the natural history of language recovery following stroke related aphasia?
- What are the predictors of language recovery outcomes?
- What are the components of effective aphasia rehabilitation interventions?
- Are some interventions (or intervention components) more beneficial for some patient subgroups (individual, stroke or aphasia characteristics) than others?
Patients that receive speech and language therapy (SLT) recover better than those that receive no SLT. However, most continue to experience significant communication impairment and much uncertainty remains around the delivery of SLT interventions in relation to, for example, the optimum timing after stroke onset, intensity, frequency, duration, therapy tasks (or mechanisms) and theoretical approach. In addition, conflicting evidence relating to the impact of patients’ age, sex, handedness and educational background and other variables on language recovery outcomes creates uncertainty about which patients will spontaneously recover, not recover well and those that are most likely to benefit from therapy. Interaction between the language impairment (modalities affected, severity), individual patient characteristics (age, sex, educational background, languages used), stroke (severity, lesion location and time since onset) and therapeutic options is poorly understood. Clinically effective and affordable approaches, based on an informed prognosis of recovery profile for people with aphasia after stroke are urgently required.
However, rather than moving forward with multiple, large, costly, logistically challenging, prospective randomised controlled trials we believe that much understanding can be gained from coordinated analyses of the rich aphasia datasets already in existence prior to progression towards definitive trails evaluating defined interventions amongst patient groups most likely to demonstrate benefit. Thorough exploration of pooled individual patient data (from pre-existing aphasia research datasets would quickly, and cost effectively, address some of the uncertainties highlighted above.