OBJECTIVES: To determine factors that independently predict health-related quality of life (HRQOL) 1 and 3 years after stroke. METHODS: Subjects numbering 397, from a population-based register of first-ever strokes were assessed for HRQOL using the Short Form 36 (SF36) 1 year after stroke. Physical (PHSS) and mental health (MHSS) summary scores were derived from the eight domains of HRQOL in the SF36. Multivariate stepwise regression analyses were conducted to determine independent predictors of these scores; beta coefficients with 95% CI were obtained.beta coefficient is the difference between average value of the variable (e.g. male) and average value under consideration (e.g. female). Demographic and stroke risk factors, neurological impairments and cognitive impairment (MMSE <24) were included in the models. Similar analyses were undertaken on 150 subjects 3 years post-stroke. RESULTS: A year after stroke, independent predictors of the worst PHSS were of females (beta coefficient -3.3: 95% CI -5.7 to -0.8), manual workers (-3.2: -5.9 to -0.4), diabetes (-4.2: -7.7 to -0.8), right hemispheric lesions (-4.9: -8.7 to -1.2), urinary incontinence (-7.8: -11.6 to -4.1) and cognitive impairment (-2.7: -5.5 to -0.1); the worst MHSS were associated with being Asian (-11.8: -20.6 to -3.0), ischaemic heart disease (-2.7: -5.4 to -0.03), cognitive impairment (-3.04: -5.8 to -0.3). Subjects aged 65-75 years (5.4: 2.5 to -8.4) had better MHSS than those <65 years. Three years post-stroke, independent predictors of worse PHSS were hypertension (-8.7: -13.5 to -3.9), urinary incontinence (-8.1: -15 to -1.1) and cognitive impairment (-8.3: -13.2 to -3.5). CONCLUSIONS: Determinants of HRQOL vary both over time after stroke and whether physical or psychosocial aspects of HRQOL are being considered. This study provides valuable information on factors predicting long-term HRQOL, which can be taken into consideration in audits of clinical practice or in future interventional studies aiming to improve HRQOL after stroke.
OBJECTIVES: To determine factors that independently predict health-related quality of life (HRQOL) 1 and 3 years after stroke. METHODS: Subjects numbering 397, from a population-based register of first-ever strokes were assessed for HRQOL using the Short Form 36 (SF36) 1 year after stroke. Physical (PHSS) and mental health (MHSS) summary scores were derived from the eight domains of HRQOL in the SF36. Multivariate stepwise regression analyses were conducted to determine independent predictors of these scores; beta coefficients with 95% CI were obtained.beta coefficient is the difference between average value of the variable (e.g. male) and average value under consideration (e.g. female). Demographic and stroke risk factors, neurological impairments and cognitive impairment (MMSE <24) were included in the models. Similar analyses were undertaken on 150 subjects 3 years post-stroke. RESULTS: A year after stroke, independent predictors of the worst PHSS were of females (beta coefficient -3.3: 95% CI -5.7 to -0.8), manual workers (-3.2: -5.9 to -0.4), diabetes (-4.2: -7.7 to -0.8), right hemispheric lesions (-4.9: -8.7 to -1.2), urinary incontinence (-7.8: -11.6 to -4.1) and cognitive impairment (-2.7: -5.5 to -0.1); the worst MHSS were associated with being Asian (-11.8: -20.6 to -3.0), ischaemic heart disease (-2.7: -5.4 to -0.03), cognitive impairment (-3.04: -5.8 to -0.3). Subjects aged 65-75 years (5.4: 2.5 to -8.4) had better MHSS than those <65 years. Three years post-stroke, independent predictors of worse PHSS were hypertension (-8.7: -13.5 to -3.9), urinary incontinence (-8.1: -15 to -1.1) and cognitive impairment (-8.3: -13.2 to -3.5). CONCLUSIONS: Determinants of HRQOL vary both over time after stroke and whether physical or psychosocial aspects of HRQOL are being considered. This study provides valuable information on factors predicting long-term HRQOL, which can be taken into consideration in audits of clinical practice or in future interventional studies aiming to improve HRQOL after stroke.
Authors: Elen B Pinto; Iara Maso; Julio L B Pereira; Thiago G Fukuda; Jamile C Seixas; Daniela F Menezes; Carolina Cincura; Iuri S Neville; Pedro A P Jesus; Jamary Oliveira-Filho Journal: Health Qual Life Outcomes Date: 2011-08-10 Impact factor: 3.186
Authors: Mandip S Dhamoon; Leslie A McClure; Carole L White; Helena Lau; Oscar Benavente; Mitchell S V Elkind Journal: J Stroke Cerebrovasc Dis Date: 2013-10-28 Impact factor: 2.136
Authors: W K Tang; Y K Chen; J Lu; A T Ahuja; W C W Chu; V C T Mok; G S Ungvari; Y T Xiang; K S Wong Journal: Neurol Sci Date: 2011-04-09 Impact factor: 3.307
Authors: Tanzila Shams; Alexander P Auchus; Suzanne Oparil; Clinton B Wright; Jackson Wright; Anthony J Furlan; Cathy A Sila; Barry R Davis; Sara Pressel; Jose-Miguel Yamal; Paula T Einhorn; Alan J Lerner Journal: Stroke Date: 2017-09-27 Impact factor: 7.914
Authors: W K Tang; H J Liang; Y K Chen; A T Ahuja; Winnie C W Chu; V C T Mok; Gabor S Ungvari; K S Wong Journal: Neurol Sci Date: 2012-12-18 Impact factor: 3.307
Authors: Binith Cheeran; Leonardo Cohen; Bruce Dobkin; Gary Ford; Richard Greenwood; David Howard; Masud Husain; Malcolm Macleod; Randolph Nudo; John Rothwell; Anthony Rudd; James Teo; Nicholas Ward; Steven Wolf Journal: Neurorehabil Neural Repair Date: 2009-02 Impact factor: 3.919