SUMMARY Seven clinical tests have been used to study the recovery of arm function in 92 patients over 2 years following their stroke. These tests are simple and quick, and can be used by any interested observer. They form a hierarchical scale that measures recovery. Statistically significant improvement is only seen in the first 3 months. Fifty-six patients initially had nonfunctional arms; eight made a "complete recovery" and 14 a partial recovery. The tests described are inadequate on their own because they are not sufficiently sensitive at the upper range of ability. While recovery of lost function does relate to the degree of initial neurological loss in the arm, it seems to be largely independent of the overall severity of the stroke.Recovery after stroke dan be measured in many ways, and the method chosen will depend upon the information wanted. Survival apart, the simplest ways can include the length of stay in hospital and final "placement" (type of accommodation), but these depend upon social factors as much as upon the degree of physical recovery. "Activities of Daily Living" (ADL) scales (for example the Barthel') relate much more to the patient alone, and have practical and prognostic value. However, using these scales it is difficult to separate the recovery of specific lost neurological function from a more generalised adaptive response.The study of isolated arm function might allow measurement of the recovery of lost neurological ability separate from the adaptive response adopted using preserved functions (for example, learning to eat and dress one-handed). If so, one could assess the effect of therapeutic intervention (for example, physiotherapy) upon recovery itself. In addition, it could help provide a prognosis for recovery.Arm function after stroke has been measured previously,2-' but no single technique has become generally used. Previous methods have either depended upon special equipment,2 or required time consuming assessments3-5 to be made. Therefore these techniques cannot easily be used in large scale follow-up studies. There is a need for a simple method of measuring arm function that can be used upon a wide range of patients by any interested observer using the minimum of equipment. This paper reports upon a method that has been used in a long-term follow-up study on all patients referred to the Frenchay Stroke Unit over the 2 years 1976-78. PatientsOne hundred and sixty two patients were accepted by the Unit, a specialist rehabilitation department; all referrals were accepted provided that the patient lived in or near the district, and were fit enough to attend. The total includes not only patients admitted to the hospital but also 44 acute strokes who were never admitted to hospital but received all their treatment as out-patients.Ninety two of the 101 patients who survived to their final follow-up were assessed, and they form the basis for the results, except where stated otherwise. There were 45 men and 47 women; 49 had a right hemiplegia, 41 a left hemiplegia, and two had "brai...

Patients and methodsUsing data from our recent study of 42 motor neuron disease patients we reviewed our records of those with persistent pain of more than trivial severity. We sought details of the pain duration, timing in the course of the disease, pain quality, site and efficacy of treatment measures.

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Background: A third of carers of people who have had a stroke experience poor psychological health. Early prediction of carers' later well-being would allow interventions to be targeted at carers most at risk of a poor outcome. Aim: To develop a predictive model for the identification of stroke carers at risk of developing poor psychological well-being in the first year post stroke. Method: Fifty consecutive one-year survivors of a stroke and their carers were assessed on a range of demographic, environmental and psychosocial variables at three months post stroke. The carers' psychological well-being at 12 months post stroke was assessed using the General Well-Being Index (GWBI). Multiple regression analysis was performed to identify the best early predictors of carers' later well-being. Results: The regression analysis identified three significant predictors of carers' well-being: carers' appraisal of caregiving stress; carers' physical health; and carers' satisfaction with service provision ( r 2 = 0.53). Using this model, 72% of carers' predicted well-being scores fell within nine points of their actual 12-month GWBI score.Conclusion: Findings from this preliminary study indicate that it may be possible to identify carers most likely to experience poor psychological wellbeing. In order to develop a clinically usable 'carer risk prediction instrument' further research to test this model is essential.

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