Quality of Life and Quality adjusted Life Years after stroke in Sierra Leone

Abstract

BackgroundStroke is a leading cause of mortality and negatively affects health related quality of life (HRQoL). HRQoL after stroke is understudied in Africa and there are no reports of quality-adjusted life years after stroke (QALYs) in African countries. We determined the impact of stroke on HRQoL after stroke in Sierra Leone. We calculated QALYs at one year post stroke, and determined sociodemographic and clinical variables associated with HRQoL and QALYs in this population.MethodsA prospective stroke register was established at the two principal adult tertiary government hospitals in Freetown, Sierra Leone. Participants were followed up at seven days, 90 days and one year post stroke to capture all-cause mortality and EQ-5D-3L data. QALYs were calculated at the patient level using EQ-5D-3L utility values and survival data from the register, following the area under the curve method. Utilities were based on the United Kingdom and Zimbabwean (as a sensitivity analysis) EQ-5D value sets, as there is no Sierra Leonean or West African value set. Explanatory models were developed based on previous literature to assess variables associated with HRQoL and QALYs at one year after stroke. To address missing values, Multiple Imputation by Chained Equations (MICE), with linear and logistic regression models for continuous and binary variables respectively, was used.ResultsEQ-5D-3L data was available for 373/460 (81.1%), 360/367 (98.1%) and 299/308 (97.1%) participants at 7 days, 90 days and one year after stroke. For stroke survivors, median EQ-5D-3L utility increased from 0.20 (95% CI:-0.16-0.59) at seven days post stroke, to 0.76 (0.47-1.0) at 90 days and remained stable at one year 0.76 (0.49-1.0). Mean QALYs at one year after stroke were 0.28 (SD: 0.35) and closely associated with stroke severity. Older age, lower educational attainment, patients with subarachnoid haemorrhage and undetermined stroke types all had lower QALYs and lower HRQoL, whilst being the primary breadwinner was associated with higher HRQoL. Sensitivity analysis with the Zimbabwe value set did not significantly change regression results but did influence the absolute values with Zimbabwe utility values being higher, with fewer utility values less than 0.ConclusionsWe generated QALYs after stroke for the first time in an African country. QALYS were significantly lower than studies from outside Africa, partially explained by the high mortality rate in our cohort. Further research is needed to develop appropriate value sets for West African countries and to examine QALYs lost due to stroke over longer time periods.Data AvailabilityThe SISLE anonymised dataset is available upon request to researchers, see data access section.