Quality of life and quality-adjusted life years after stroke in Sierra Leone

 So not 100% recovery! And the quality of life was not measured to that standard.

Quality of life and quality-adjusted life years after stroke in Sierra Leone

Daniel Youkee https://orcid.org/0000-0002-2383-4425 daniel.youkee@kcl.ac.uk, Gibrilla F Deen, […], and Marina Soley-Bori+3View all authors and affiliations

OnlineFirst

https://doi.org/10.1177/17474930241249589

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• • Abstract
  • Introduction
  • Methods
  • Results
  • Discussion
  • Acknowledgments
  • Declaration of conflicting interests
  • Funding
  • ORCID iD
  • Data availability statement
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Abstract

Background:

Stroke 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 1 year post-stroke and determined sociodemographic and clinical variables associated with HRQoL and QALYs in this population.

Methods:

A prospective stroke register was established at the two-principal adult tertiary government hospitals in Freetown, Sierra Leone. Participants were followed up at 7, 90 days, and 1 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 UK and Zimbabwe (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 1 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, were used.

Results:

EQ-5D-3L data were available for 373/460 (81.1%), 360/367 (98.1%), and 299/308 (97.1%) participants at 7, 90 days, and 1 year after stroke. For stroke survivors, median EQ-5D-3L utility increased from 0.20 (95% CI: −0.16 to 0.59) at 7 days post-stroke to 0.76 (0.47 to 1.0) at 90 days and remained stable at 1 year 0.76 (0.49 to 1.0). Mean QALYs at 1 year after stroke were 0.28 (SD: 0.35) and closely associated with stroke severity. Older age, lower educational attainment, patients with subarachnoid hemorrhage and undetermined stroke types all had lower QALYs and lower HRQoL, while 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.

Conclusion:

We 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 availability:

The Stroke in Sierra Leone anonymized dataset is available on request to researchers, see data access section.