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Predictors of survival after haemorrhagic stroke in a multi-ethnic population: the South London Stroke Register (SLSR)

¹ King’s College London, Division of Health and Social Care Research, London, UK
² Department of Health and Ageing, Guy’s & St. Thomas’ NHS Foundation Trust, St. Thomas’ Hospital, London, UK

Correspondence to:
Shah Jalal Sarker, King’s College London, Division of Health and Social Care Research, Capital House, 42 Weston Street, London SE1 3QD, UK; shah_jalal.sarker{at}kcl.ac.uk

Methods: Data were collected within the population-based South London Stroke Register covering a multiethnic source population of 271 817 inhabitants (2001) in South London. Death data were collected at post-stroke follow-up. The impact of patients’ demographic and clinical characteristics, ethnic origin, pre-stroke risk factors and acute treatment on long-term survival were investigated. Survival methods included Kaplan–Meier curves and Cox’s proportional hazards model.

Results: Between January 1995 and December 2004, a total of 566 patients with first-ever haemorrhagic stroke (395 primary intracerebral haemorrhage; 171 subarachnoid haemorrhage) were registered. Mean age was 62.3 years; 365 (64.5%) were white, 132 (23.3%) were black and 69 (12.2%) were other or unknown ethnic origin; there were 1340 person-years of follow-up. After multivariable adjustment, age (p<0.001) and having diabetes (hazard ratio (HR), 1.69; 95% CI 1.06–2.70) were associated with increased risk of death. Patients with severe stroke (Glasgow Coma Scale (GCS) <9) had an increased risk of death (HR 6.5; 95% CI 4.68 to 8.90) compared with those with mild stroke (GCS >12). Treatment on a stroke unit reduced the long-term risk of death (HR 0.70; 95% CI 0.50 to 0.98). Black patients had a reduced risk of death (HR 0.62; 95% CI 0.42 to 0.92) compared with white patients.

Conclusions: Age, diabetes, stroke severity and stroke unit care influenced the long-term risk of death after haemorrhagic stroke. An independent survival advantage was observed in black patients. These factors can be utilised for clinical predictions but the cause of the observations in black patients remains unclear.