| | Community-Dwelling Stroke Survivors: Function Is Not the Whole Story With Quality of LifePresented in part to the Stroke It’s Time Conference, July 7, 2006, Sydney, Australia. Abstract White JH, Alston MK, Marquez JL, Sweetapple AL, Pollack MR, Attia J, Levi CR, Sturm J, Whyte S. Community-dwelling stroke survivors: function is not the whole story with quality of life. ObjectiveTo compare function and quality of life in community-dwelling stroke survivors at 1, 3, and 5 years after stroke. DesignA community-based, cross-sectional study of 3 retrospective cohorts. SettingCommunity-dwelling stroke survivors in Australia. ParticipantsThe 3 cohorts comprised 30 participants each at 1, 3, and 5 years poststroke discharge from a tertiary referral hospital. InterventionsNot applicable. Main Outcome MeasuresStroke severity, comorbidity, medications used, and demographic information were recorded. Poststroke function was assessed using the Modified Rankin Scale, Mini-Mental State Examination, Stroke Impact Scale, and Multidimensional Scale of Perceived Social Support. ResultsThis cross-sectional study provides insights into trends in stroke survivors over time. A high proportion of stroke survivors use community services, even those who are independent with activities of daily living. Although there was little attrition in medication use over time except for warfarin, this was from a baseline of suboptimal compliance and adherence with stroke preventive therapies. Stroke survivors report high levels of perceived social support; however, emotional well-being was low overall. The data suggest that those who are independent at 1 year tend to remain independent, although this was an extrapolation from serial cross-sections and needs to be explored in a longitudinal study. ConclusionsStroke survivors’ function does not change significantly over time. A high proportion of survivors require community services. The development of needs-related effective long-term service delivery models is required. STROKE IS AMONG the leading causes of long-term disability in the Australian population and the second leading cause of death.1, 2 Much work has focused on the natural history of poststroke patients with results indicating that by the end of the first year about half of all stroke survivors will remain dependent on others for activities of daily living (ADLs).3, 4 Although most of the work has focused on survival poststroke, there has also been an increase in research exploring functional and emotional states and the experience of health-related quality of life (HRQOL). HRQOL is now viewed as an outcome of health care as well as a consequence of illness or injury.5, 6 In an Australian context, Sturm et al,7 using the North East Melbourne Stroke Incidence Study, identified that many stroke survivors make gains with basic ADLs but report poor HRQOL within 2 years following stroke onset.8 Determinants of HRQOL have consistently included: (1) depression7, 8, 9; (2) functional restrictions7, 9, 10, 11; (3) stroke location and severity of paralysis8, 12; and (4) social support and comorbidity.11, 12, 13 However, more research is needed to further explore long-term changes in physical function, emotional function, cognitive function, communication function, social participation, social support, carer strain, service utilization, and the range of comorbidities and how these influence HRQOL. Such research will delineate areas of need and lay the foundation for the development of future models of long-term care for stroke survivors that enhance HRQOL. This is of great significance with an aging population in which more people are likely to be living with multiple comorbidities, therefore increasing demands on the health system to provide a diverse range of effective services. In this study, we set out to gather pilot data on various determinants of HRQOL poststroke, and in particular to assess these measures at various times poststroke, that is, at 1, 3, and 5 years. Methods  Study Population Newcastle is a typical coastal city situated within the Hunter Region on the coast of New South Wales, Australia; the Hunter population is representative of the general Australian population except in the area of ethnicity.14, 15 The Hunter has a population of 541,74415 and hospital-based stroke services are provided by acute stroke units and stroke rehabilitation units in 2 tertiary referral centers. Sampling Frame and Case Ascertainment The study assembled 3 retrospective cohorts, each comprising 30 participants: (1) cohort 1: people who had had a stroke 1 year ago; (2) cohort 3: people who had had a stroke 3 years ago; and (3) cohort 5: people who had had a stroke 5 years ago. We identified stroke survivors from hospital records and discharges from the John Hunter Hospital (JHH), the largest tertiary referral hospital and the main hospital servicing Hunter residents. The cases were defined by: admission to JHH, alive at discharge, history, and examination consistent with stroke as determined by a stroke physician. Brain imaging was available in all cases. Patients with hemorrhagic stroke were included. Mortality status was determined by linkage of data with data from the New South Wales Registry of Births, Deaths and Marriages. Starting from health records in January, consecutive participants were contacted via mail-out, until 30 participants were recruited in each cohort. This number of participants was essentially selected to fit within the budget and time frame of existing resources, and was meant as a pilot study. Exclusion criteria consisted of severe cognitive impairment (Mini-Mental State Examination [MMSE] score ≤16),16 inability to give informed consent, and current residence in a nursing home, that is, only community-dwelling stroke survivors (including hostels) were contacted. Consenting participants were subsequently phoned by the researchers to arrange an interview time with an experienced allied health clinician. All participants opted to be interviewed in their own homes. Interviews were undertaken within 3 months of consent. If dysphasia was present then the participant was interviewed by the speech pathologist on the research team, and proxy assessments were used where appropriate. Baseline Data We collected baseline data from hospital records. This included date of stroke, comorbidities, and admission and discharge medications. Ischemic stroke subtype was classified using the Oxfordshire Community Stroke Project (OCSP) classification17, 18 into the following syndromes: total anterior circulation infarction (TACI), partial anterior circulation infarction (PACI), posterior circulation infarction (POCI), and lacunar circulation infarction (LACI). This classification system identifies patients with potentially different outcomes (prognosis) as well as assisting with identification and prioritization of appropriate therapies.18 Instruments The study team assessed consenting participants on physical and psychosocial functioning using a range of validated measures. The OCSP is a widely used system established to assist in defining ischemic stroke. Disability was assessed using the Modified Rankin Scale (MRS), which has been widely used within international stroke research to assess disability after stroke.19, 20 Cognition was assessed using the MMSE,16 a widely used and well validated tool that can be used to systematically assess mental status. It involves an 11-question measure that tests 5 areas of cognitive function (orientation, registration, attention and calculation, recall, language) and is scored out of 30. Health outcomes specific to a stroke population were assessed using the Stroke Impact Scale (SIS 3.0).21 The SIS provides a comprehensive measure of function and HRQOL based on self-report in the domains of strength, memory, emotion, communication, ADLs, mobility, and handicap. The SIS has undergone extensive psychometric testing.21 Social support was measured using the Multidimensional Scale of Perceived Social Support (MSPSS),22 which is a brief instrument used for assessing the hierarchical structure of perceived social support. It has been well validated in a range of populations, including cardiovascular disease populations and the elderly.23, 24 Patient medications at baseline were obtained from hospital records and medications at follow-up were obtained by self-report. Participants were asked if and how often they had accessed support services for assistance over the past year. Assistance could be provided either formally by an established organization or informally by a member of the community. Statistical Analysis We compared the characteristics of participants and nonrespondents by using the parametric t test for continuous variables and the Fisher exact test for categorical variables. Statistical analyses were undertaken using SPSS.a The MRS was categorized as independent (MRS score ≤2) or dependent (MRS score between ≥3 and ≤5). The categorization of the MRS follows a similar method employed by Sulter et al.20 Descriptive analysis was undertaken for all other results. Statistical analysis of the SIS 3.0 was limited by the small sample size and the fact that analysis typically involves a comparison of scores before and after any given intervention.25 Being a stroke-specific measure, it was difficult to judge whether the MSPSS score was high or low compared with other chronic diseases. To create this clinical context, the physical component of the SIS score was converted to Short-Form 36-Item Health Survey (SF-36) scores. This method of conversion was based on a previous study whereby the SIS 3.0 was converted to an SIS 16 score,26 and then to an SF-36 physical function score.27 The SF-3628 is widely used as a generic HRQOL instrument assessing physical, psychologic, and social functions.29 Although this method has the drawback of only using the functional activity domain rather than the entire set of variables in the SIS, it was the only method of placing the SIS scores in some clinical context (appendix 1). Ethics Ethics committee approval for this project was obtained from Hunter New England Human Ethics Research Committee and all patients enrolled in the study gave written, informed consent. Results A total of 336 stroke patients discharged from the JHH were assessed and 139 met the inclusion criteria. Forty-one declined to participate and a further 7 were nonrespondents. Informed consent was obtained for 91 cases (65% consent rate). An inclusion matrix is outlined in figure 1. There was no statistical difference in sex, age, or stroke subtype between participants and nonrespondents (data not shown). Table 1 compares the key demographics of participants between each cohort. There was no statistical difference for sex, presence of a caregiver, living situation, marital status, first ever stroke, ethnicity, and dysphasia. The statistical difference for employment status (P=.036) is significant but should be interpreted with caution in the setting of multiple comparisons. The majority of participants showed minimal cognitive impairments, scoring between 24 and 30 on the MMSE (83%, 90%, 93%, respectively). | | |  | Characteristics | Cohort 1 (n=30) | Cohort 3 (n=31) | Cohort 5 (n=30) | P | |
|---|
| Sex | | | | .128 | | |  Female | 19(63) | 11(37) | 14(47) | | | | Male | 11(37) | 20(63) | 16(53) | | | | Mean age (y) | 70.7 | 72.5 | 69.3 | | | | Living style | | | | .914 | | | Live alone | 8(27) | 7(23) | 8(27) | | | | Not alone | 22(73) | 24(77) | 22(73) | | | | Marital status | | | | .095 | | | Married | 15(50) | 18(58) | 16(53) | | | | Other | 15(50) | 13(42) | 14(47) | | | | First ever stroke | | | | .295 | | | Yes | 26(87) | 24(77) | 21(70) | | | | No | 4(13) | 7(23) | 9(30) | | | | Employment history | | | | .036 | | | Employed | 4(13) | 5(16) | 3(10) | | | | Retired | 26(87) | 26(84) | 27(90) | | | | Carer | | | | .543 | | | Yes | 8(27) | 12(39) | 11(37) | | | | No | 22(73) | 19(61) | 19(63) | | | | Ethnicity | | | | .479 | | | Australian | 27(90) | 24(77) | 27(90) | | | | Other | 3(10) | 7(23) | 3(10) | | | | Dysphasia | | | | .960 | | | Yes | 6(20) | 7(23) | 6(20) | | | | No | 24(80) | 24(77) | 24(80) | | | | OCSP classification | | | | .183 | | | TACI | 2(7) | 3(10) | 0(0) | | | | LACI | 12(40) | 9(29) | 6(20) | | | | PACI | 10(33) | 12(39) | 13(43) | | | | POCI | 5(17) | 2(6) | 8(27) | | | | SAH | 1(3) | 2(6) | 0(0) | | | | ICH | 0(0) | 3(10) | 3(10) | | | | MMSE score between 24−30 | 83 | 90 | 93 | .085 | | | | |
Comorbidities Baseline comorbidity data were collected from the participants’ medical file and follow-up comorbidity data were based on self-report. At baseline, 90% of participants had 1 or more risk factors for stroke (97%, 97%, and 87% for cohorts 1, 3, and 5, respectively) and 63% had 2 or more risk factors for stroke (73%, 58%, 57%, respectively). A comparison between cohorts 1, 3, and 5 indicated that hypertension (70%, 57%, 47%, respectively), cardiac conditions (57%, 33%, 37%, respectively), and hypercholesterolemia (33%, 20%, 33%, respectively) were the most common risk factor comorbidities at baseline. Medications Medication profile was similar across the cohorts with the most prevalent medications being antiplatelet medication (73%, 63%, 58%, respectively) and antihypertensive medication (80%, 80%, 61%, respectively) at discharge. There was a consistent proportion of participants being discharged on warfarin across the 3 cohorts (30%, 37%, 39%, respectively). Cohort 5 had the highest rate of attrition from warfarin following discharge (33%, 10%, 11%, respectively). More participants were discharged on antiplatelet medication than on warfarin. At discharge the percentage of participants taking lipid-lowering medication was 50%, 27%, and 32% for each respective cohort. This had increased to 53%, 53%, and 61%, respectively, for each cohort at follow-up. Antidepressant usage across the cohorts at discharge was 10%, 7%, and 13%, respectively, and at follow-up 10%, 20%, and 10%, respectively. Service Utilization Sixty percent of cohort 1, who were 1 year poststroke, had accessed at least 1 service in the year since their stroke. Service utilization was marginally lower for cohorts 3 (45%) and 5 (50%). The most frequently accessed services across all cohorts were housework (21%), gardening and mowing (24%), and meals on wheels (19%). Therapy services were less frequently accessed than maintenance type or respite services. Similar numbers of participants in cohorts 1, 3, and 5 were accessing allied health services (15%, 13%, 14%, respectively). The most frequently accessed therapy services across all cohorts were physiotherapy (15%) and podiatry (21%). In each cohort there were 1 to 2 participants using a surprisingly high number of community services (8 to 9) which may skew results (data not shown). Participant Function Dependency was determined by the MRS. Sixty-four of the 91 participants were independent at the time of interview (70%). This trend was consistent across the 3 cohorts (63%, 74%, 73%, respectively). TACI participants were the least independent (40%) with LACI (92%) participants and PACI (63%) participants being the most independent. Use of SIS 3.0 provided more detailed information regarding the functional levels of the participants. The combined functioning of the cohorts as determined by the SIS is outlined in figure 2. Results showed that the participants were scoring lowest in the emotion domain. In each cohort there was a subset of participants doing significantly worse than other participants (data not shown). The next lowest scoring domains were strength and mobility. To obtain some clinical context for what the SIS scores meant, the SIS scores of physical function (SIS 16) results were “converted” to SF-36 scores, in order to compare these with normative data in the Australian population.29 The results showed that, at least from a physical function viewpoint, both men and women in our study sample were functioning at lower levels than the average Australian of the same age and sex and within the lowest 50th percentile (fig 3).29 Multidimensional Scale of Perceived Social Support The MSPSS measured the perceived sources of social support received by the participants. High levels of perceived social support were maintained across the 3 cohorts (82%, 79%, 70%, respectively). Highest levels of perceived support were received from family (75%, 80%, 81%, respectively) and significant others (77%, 83%, 86%, respectively). This is shown in figure 4. Discussion This study has generated unique data on the HRQOL outcome of Australian stroke survivors and provides baseline data for ongoing measurement of outcomes following stroke in this region. A major strength of the study lies in the ability to obtain details of the participants’ current levels of stroke-specific functioning using a wide range of reliable outcome measures. The demographics of the 3 cohorts were similar, therefore, assisting comparison of poststroke functioning over time. Due to the study design, the cohorts are likely to be most representative of community-dwelling stroke survivors with relatively milder levels of impairment. An objective sampling frame was used which allowed for the inclusion of participants with dysphasia, who are often excluded from research studies. The proportion of dysphasic patients in this study was consistent with the prevalence of dysphasia in stroke survivors generally (between 21% and 38% in the broader population).30 The hypothesized decline in function over time between the 3 time cohorts was not seen. Instead, results suggest that those who are alive and managing in the community at 1 year poststroke are likely to remain so at 3 and 5 years, that is, the group of stroke survivors included in this study remain relatively stable following discharge. In favor of this interpretation is the fact that, although the proportion deceased at 1, 3, and 5 years increases, as expected in an aging population (20%, 31%, 34%, respectively), the proportion in nursing homes remains the same (14%, 15%, 12%, respectively). However, it is problematic to extrapolate across multiple cross-sectional measures, and given the number of stroke survivors who declined to participate, we also cannot exclude sampling bias; that is, the survivors with poorer function do not participate. There was appropriate prescription of preventive medication during acute hospital admission; in each cohort there was almost 100% prescription of either warfarin or antiplatelet during the acute admission, which is integral in stroke prevention. Warfarin adherence showed the greatest range of attrition; however, rates at follow-up (33%, 10%, 11%, respectively) were still in keeping with the national figure of 10.3%.31 There was some attrition with regard to antihypertensive adherence; however, the proportions of each cohort taking antihypertensives were 50%, 80%, and 87%, respectively, which compared favorably with the national figure of 68.9%.31 Statin adherence showed some gain following hospital discharge (50%, 27%, 32%, respectively), which is better than the national average of 21%.31 Increased use of lipid lowering medication at follow-up is consistent with recent, evidence-based trends regarding the use of cholesterol-lowering agents for protective benefits.32 Although they may be encouraging overall from a practical point of view, these numbers still indicate room for improvement. Patterns of antidepressant usage are low given that an estimated 33% of all stroke survivors experience depression.33 This suggests that stroke survivors are not readily being prescribed antidepressants during acute admission or in the community. This is consistent with evidence suggesting that depression is under-recognized in the stroke population. It may also result from the lack of clear evidence supporting the benefit of prescribing antidepressants after stroke.34 Due to the small sample size, it was difficult to identify trends with regard to stroke-specific function as measured by the SIS 3.0, because large standard deviations made it difficult to compare between cohorts. However, when numbers were combined, the emotion domain had the lowest score, suggesting that low mood was sustained over time. This result is supported by a qualitative study undertaken with a subgroup of participants from each cohort.35 We initially chose the SIS because it was a stroke specific scale; however, the disease specificity of this measure made it difficult to put the scores in the context of other chronic diseases. For this reason, the SIS score was “converted” to an SF-36 “equivalent.” Although it was only possible for the physical component of the score, this conversion enabled some comparison with the Australian norms and indicated that even on the physical function aspect, which was one of the highest scoring domains on the SIS, stroke survivors were on a par with the lowest half of the general population. Information gained with regard to service utilization provides novel, descriptive local data. Service utilization across all cohorts was consistent; that is, service use did not appear to increase with time. More surprising was that, despite the high levels of independence in this community-dwelling sample, over 50% of stroke survivors still require support with instrumental ADLs. This was surprising given that one would expect that rationing of available services, lack of stroke survivor knowledge about available services, or refusal of some stroke survivors to accept services would underestimate this proportion. However, this is similar to data from the Australian Institute of Health and Welfare31 stating that approximately 50% of stroke survivors require assistance with health care, household chores, home maintenance, and mobility. A further 1 in 4 require assistance with self-care, cognitive and emotional tasks, and meal preparation. Ongoing therapy has the potential to address the difficulties highlighted by this study in the areas of emotion and physical functioning. Future research would be of benefit to elucidate this issue by comparing available services, client knowledge of available services, clients’ perception of their service needs, and their willingness to engage with services and assistance. It would also be beneficial in future research to separate formal and informal service and assistance to help define gaps in formal services in the community. The high levels of perceived social support, as measured by the MSPSS across all groups, was also surprising. From clinical experience it was expected that stroke survivors would experience reduced social support over time. Future research would benefit from the use of an outcome measure that reflects both the quantity and the quality of social support. This may help to further define any changes that occur in social support over time. If one or a very limited number of people are providing support this may also contribute to increased carer burden and strain. Study Limitations There were several study limitations as indicated above. The use of a retrospective, cross-sectional cohort design limits the ability to make interpretations regarding changes in poststroke functioning over time. Sampling bias was present in that the study excluded people in residential care facilities; this may have not included more severe strokes with higher levels of impairment. People who have had another stroke or who died in the community have also not been captured in this study. Therefore this sample source will not entirely be representative of the wider stroke population. This limits knowledge about the true proportion of patients who improve or deteriorate. Conclusions Overall the results of this study suggest that the functioning of stroke survivors following discharge to the community does not change significantly over time. Data highlights that stroke survivors continue to use community services, even in a group that is community-dwelling and independent, and stroke survivors continue to use medications with little attrition, except for warfarin, although there is room to increase compliance and adherence. Importantly, stroke survivors report high levels of perceive social support although emotional well-being remains a significant concern. These data support the need for a more extensive prospective study with a view to further exploration of changes in physical and psychosocial changes over time. Supplier Appendix 1. Conversion of SIS 16 Scores to an SF-36 Physical Functioning Score SIS 16 scores were calculated from the SIS total based on Lai et al.27 SIS 16 scores were then “converted” to an SF-36 physical functioning score using the data in Ware.28 In summary, we simulated 2 sets of individual data for the SIS 16 and SF-36 physical functioning scores with means, standard deviations, and correlation coefficient given in Ware.28 A linear regression equation was fitted to the simulated data using Stata, which yielded the following approximate conversion rule: References 1. 1Australian Institute of Health and Welfare. Heart, stroke and vascular diseases: Australian facts. Canberra: AIHW; 2004;. 2. 2National Stroke Foundation. National Stroke Foundation website. Available at: http://www.strokefoundation.com.au. Accessed on August 31, 2006. 3. 3Hankey GJ, Jamrozik KJ, Broadhurst RJ, Forbes S, Anderson CS. Long-term disability after first ever stroke and related prognostic factors in the Perth Community Stroke Study. Stroke. 2002;33:1034–1040.
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28. 28Ware JE. SF-36 Health Survey: manual and interpretation guide. Boston: Health Institute, New England Medical Center; 1993;. 29. 29Australian Bureau of Statistics. National Health Survey: SF-36 population norms. Canberra: ABS; 1995;. 30. 30Lalor L, Cranfield E. Aphasia: a description of the incidence and management in the acute hospital setting. Asia Pac J Speech Lang Hear. 2004;9:129–136. 31. 31Senes S. How we manage stroke in Australia. Canberra: Australian Institute of Health and Welfare; 2006;. 32. 32Amarenco P, Bogousslavsky J, Callahan A, et al. Stroke Prevention by Aggressive Reduction in Cholesterol Levels (SPARCL) Investigators (High dose atorvastatin after stroke or transient ischemic attack). N Engl J Med. 2006;355:549–559.
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34. 34Anderson CS, Hackett ML, House AO. Interventions for preventing depression after stroke. Cochrane Database Syst Rev. 2004;. 35. 35White J, Mackenzie L, Parker M, Pollack M. Assessing the long-term functional support needs of stroke survivors. In: Presented to: Stroke It’s Time Conference; July 6-7; Sydney (Aust). 2006;. a Hunter Stroke Service, Hunter New England Area Health Service, New South Wales, Australia b Community Stroke Team, Hunter New England Area Health Service, New South Wales, Australia c Rankin Park Centre, Hunter New England Area Health Service, New South Wales, Australia d John Hunter Hospital, Hunter New England Area Health Service, New South Wales, Australia e Centre for Clinical Epidemiology and Biostatistics, University of Newcastle, New South Wales, Australia f Gosford Hospital, Northern Sydney Central Coast Area Health Service, New South Wales, Australia.  Reprint requests to Jennifer H. White, BAppSc, Locked Bag No. 1, Hunter Region Mail Centre, NSW 2310, Australia
Supported by the Hunter Stroke Service, Hunter New England Area Health. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the authors or upon any organization with which the authors are associated. PII: S0003-9993(07)00405-4 doi:10.1016/j.apmr.2007.06.003 © 2007 American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved. | |
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