Abstract
Background
Survivors of aneurysmal subarachnoid haemorrhage (SAH) show heterogeneous profiles
of health-related quality of life (HrQoL). The aim of this study was to characterize
individual differences in the course of HrQoL following SAH using latent growth mixture
modelling (LGMM).
Methods
A longitudinal study with 113 incident cases of aneurysmal SAH was performed in order
to evaluate clinical outcome (Hunt and Hess scale, Barthel-Index, Beck Depression
Inventory) and HrQoL data (EQ-5D) at baseline, 6 and 12 months. The heterogeneity
in HrQoL courses after SAH was analysed using LGMM.
Results
Four subgroups (classes) of different patterns of HrQoL course after SAH were identified.
Two of these classes (1 and 3) comprised patients with considerably reduced initial
HrQoL, which was associated with more severe symptoms of SAH. Class 1 showing the
worst EQ5D-index values during the entire study period. Class 3 experiencing a considerable
improvement in HrQoL values. In comparison to classes 1 and 3, class 2 and 4 were
characterized by less severe SAH and better functional outcome. An important difference
in the disease course between classes 2 and 4 was a temporary increase in depression
scores at the 6-month time point in class 4, which was associated with a considerable
reduction in HrQoL.The specific clinical parameters characterizing differences between
classes, such as severity of SAH, functional outcome, cognitive impairment and post-stroke
depression, were identified and the influence of their potential improvement on HrQoL
was estimated.
Conclusion
By means of LGMM we could classify the course of HrQoL after SAH in four different
patterns, which are relevant for the clinical decisions. Clinical parameters, which
can be modified in order to improve the course of HrQoL were identified and could
help to develop individual therapeutic strategies for the rehabilitation after SAH.
Keywords
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Article info
Publication history
Published online: January 09, 2023
Accepted:
November 26,
2022
Received in revised form:
November 20,
2022
Received:
July 22,
2022
Identification
DOI: https://doi.org/10.1016/j.jstrokecerebrovasdis.2022.106913
Copyright
© 2022 Elsevier Inc. All rights reserved.
