Adam J Noble1, Thomas Schenk. 1. Institute of Psychiatry, King's College London, London, United Kingdom.
Abstract
OBJECTIVE: Patients with subarachnoid hemorrhage (SAH) are younger than typical stroke patients. Poor psychosocial outcome after SAH therefore leads to a disproportionately high impact on patients, relatives, and society. Addressing this problem requires an understanding of what causes poor psychosocial outcome. Numerous studies have examined potential predictors but produced conflicting results. We aim to resolve this uncertainty about the potential value of individual predictors by conducting a meta-analysis. This approach allows us to quantitatively combine the findings from all relevant studies to identify promising predictors of psychosocial outcome and determine the strength with which those predictors are associated with measures of psychosocial health. METHODS: Psychosocial health was measured by health-related quality of life (HRQOL). We included in our analysis those predictors that were most frequently examined in this context, namely patient age, sex, neurologic state at the time of hospital admission, bleed severity, physical disability, cognitive impairment, and time between ictus and psychosocial assessment. RESULTS: Only 1 of the traditional variables, physical disability, had any notable affect on HRQOL. Therefore, the cause of most HRQOL impairment after SAH remains unknown. The situation is even worse for mental HRQOL, an area that is often significantly affected in SAH patients. Here, 90% of the variance remains unexplained by traditional predictors. CONCLUSION: Studies need to turn to new factors to account for poor patient outcome.
OBJECTIVE:Patients with subarachnoid hemorrhage (SAH) are younger than typical strokepatients. Poor psychosocial outcome after SAH therefore leads to a disproportionately high impact on patients, relatives, and society. Addressing this problem requires an understanding of what causes poor psychosocial outcome. Numerous studies have examined potential predictors but produced conflicting results. We aim to resolve this uncertainty about the potential value of individual predictors by conducting a meta-analysis. This approach allows us to quantitatively combine the findings from all relevant studies to identify promising predictors of psychosocial outcome and determine the strength with which those predictors are associated with measures of psychosocial health. METHODS:Psychosocial health was measured by health-related quality of life (HRQOL). We included in our analysis those predictors that were most frequently examined in this context, namely patient age, sex, neurologic state at the time of hospital admission, bleed severity, physical disability, cognitive impairment, and time between ictus and psychosocial assessment. RESULTS: Only 1 of the traditional variables, physical disability, had any notable affect on HRQOL. Therefore, the cause of most HRQOL impairment after SAH remains unknown. The situation is even worse for mental HRQOL, an area that is often significantly affected in SAHpatients. Here, 90% of the variance remains unexplained by traditional predictors. CONCLUSION: Studies need to turn to new factors to account for poor patient outcome.
Authors: Blessing N R Jaja; Daniel Attalla; R Loch Macdonald; Tom A Schweizer; Michael D Cusimano; Nima Etminan; Daniel Hanggi; David Hasan; S Claiborne Johnston; Peter Le Roux; Benjamin Lo; Ada Louffat-Olivares; Stephan Mayer; Andrew Molyneux; Adam Noble; Audrey Quinn; Thomas Schenk; Julian Spears; Jeffrey Singh; Michael Todd; James Torner; Ming Tseng; William van den Bergh; Mervyn D I Vergouwen; George K C Wong Journal: Neurocrit Care Date: 2014-12 Impact factor: 3.210
Authors: Andrew L A Garton; Jonathan A Sisti; Vivek P Gupta; Brandon R Christophe; E Sander Connolly Journal: Stroke Date: 2016-12-08 Impact factor: 7.914