Disability and Rehabilitation

ISSN: 0963-8288 (Print) 1464-5165 (Online) Journal homepage: http://www.tandfonline.com/loi/idre20

Prognostic factors for discharge destination after acute stroke: a comprehensive literature review Kelly Van der Cruyssen, Luc Vereeck, Wim Saeys & Roy Remmen To cite this article: Kelly Van der Cruyssen, Luc Vereeck, Wim Saeys & Roy Remmen (2015) Prognostic factors for discharge destination after acute stroke: a comprehensive literature review, Disability and Rehabilitation, 37:14, 1214-1227, DOI: 10.3109/09638288.2014.961655 To link to this article: http://dx.doi.org/10.3109/09638288.2014.961655

Published online: 24 Sep 2014.

Submit your article to this journal

Article views: 161

View related articles

View Crossmark data

Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=idre20 Download by: [University of Prince Edward Island]

Date: 05 November 2015, At: 14:57

http://informahealthcare.com/dre ISSN 0963-8288 print/ISSN 1464-5165 online Disabil Rehabil, 2015; 37(14): 1214–1227 ! 2014 Informa UK Ltd. DOI: 10.3109/09638288.2014.961655

REVIEW

Prognostic factors for discharge destination after acute stroke: a comprehensive literature review Kelly Van der Cruyssen, Luc Vereeck, Wim Saeys, and Roy Remmen Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium

Abstract

Keywords

Purpose: In the future, budget constraints will make efficient care for stroke patients more important. The cost of hospitalization for stroke is high. It is desirable to consider a patient’s discharge destination soon after onset and thereby screen patients for further care. This study aims to review the evidence of factors that determine discharge destinations after acute phase of stroke in adult patients. Methods: The systematic literature search was performed in seven databases. This systematic review was conducted by the preferred reporting items for systematic reviews and meta-analyses (PRISMA statement). Full-text articles were included and assessed for methodological quality by two independent researchers. Results: Eighteen articles were selected that demonstrate factors defining discharge destination. Younger age, good post-stroke admission to a teaching hospital, and a number of medical factors are determinants to a favorable discharge destination. Determinants for unfavorable discharge destinations were a severe stroke, high body mass index, alcohol abuse, statin withdrawal during hospitalization, the presence of comorbidities like respiratory failure and dementia or having a Medicaid insurance. Conclusion: Patient initial medical care, age and sex, neurological and medical complications and environmental/socio-economic factors should be considered in the decisionmaking process for discharge destination.

Cerebrovascular disorders, discharge destination, stroke History Received 30 April 2014 Revised 25 August 2014 Accepted 1 September 2014 Published online 24 September 2014

ä Implications for Rehabilitation  

Systematic screening for prognostic factors may improve discharge planning. Discharge destination to home may be predicted by a number of factors including a young age, being Caucasian, having few medical comorbidities, achieving a physical and cognitive level of independence and being admitted to a teaching hospital, having an insurance may also play a role.

Introduction Stroke is a major cause of disability. In 2010, stroke was the fourth largest cause of death worldwide after cancer, heart and respiratory diseases [1]. Modern medical treatment in the first few hours has considerably lowered morbidity, more specifically in younger adults and in patients with a limited number of comorbidities such as hypertension [2,3]. After the acute critical phase and its medical treatment, a cerebrovascular incident imposes a physical, psychosocial and economic burden on patients, families and societies [4,5]. Worldwide, 15 million people experience stroke each year, of which 5 million remain disabled [6]. In the United States approximately 795 000 people each year endure a new or recurrent stroke [7,8]. In the United Kingdom, 152 000 people experience stroke annually and more

Address for correspondence: Kelly Van der Cruyssen, PT, Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Antwerp, 2610 Belgium. E-mail: [email protected]

than 50% of stroke survivors remain dependent on caregivers for daily living activities [9]. Considering the ageing population, an increase in the incidence of stroke is expected. Projections show there will be a 21.9% increase in prevalence between 2013 and 2030 [8]. Furthermore, better medical resources ensure a higher rate of survival [10]. This will lead to a higher demand for multidisciplinary rehabilitation services [11–14]. According to the US Department of Health and Human Services, a relatively small number of older people (3.6%) lived in institutional settings in 2011. However, this percentage increases with age, ranging from 1% for the age category 65–74 years to 11% in those older than 85 years [15,16]. Twenty percent of stroke survivors still need institutional care after 3 months, and although almost 75% of stroke survivors are discharged home, approximately 50% of them still need assistance [12,17]. In the future, budget constraints will make efficient care for stroke patients more important. The cost of hospitalization for stroke and related disorders is high. This is mainly due to the longer hospitalization duration for stroke [18]. In many regions, continuity of care is under stress because of waiting lists for subsequent care.

Discharge destination after acute stroke

Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

DOI: 10.3109/09638288.2014.961655

Length of stay in acute care may increase because capacity of rehabilitation settings is limited. As a consequence, patients may need to be hospitalized longer. This represents an inappropriate use of means and financial resources. An improved prediction of discharge destination could lead to a shorter length of stay in acute care, a better patients’ outcome, reduction of costs and result in better preparation of informal caregivers [19]. Therefore, it is desirable to consider a patient’s discharge destination soon after onset and thereby screen patients for further care [20]. However, there is a wide range of possible discharge destinations, ranging from discharge to home without any further care to discharge to long-term nursing facilities. Discharge to inpatient rehabilitation facilities (IRF) can also be considered and may have the aim to further improve functional status. Discharge destination after sufficient recovery to home can be defined as favorable, while admittance to further medical care can be seen as unfavorable. Discharge destination after acute stroke has been reported to be predicted by many factors such as: age [21–25], race [21], gender [21,26], medical complications/comorbidities [27,28], neurological complications [22,29–31] and environmental and socio-economic factors [32]. However, there are limitations to the generalizability of these studies because of possible small sample sizes, retrospective design, lack of information influencing discharge destination – such as no direct measurement of functional status [21] – or the exclusive focus on single factors [23,33–36]. To assist the process of rapid and appropriate discharge, this study aimed to systematically identify factors which influence discharge destination of acute hospitalized stroke patients to home or chronic facilities.

Methods This review was conducted by the preferred reporting items for systematic reviews and meta-analyses (PRISMA statement) [37]. Information sources and search strategy Seven databases were searched for ‘‘cerebrovascular disorders’’ AND ‘‘patient discharge’’: ‘‘Pubmed’’, ‘‘Web of Science’’, ‘‘Medline’’, ‘‘Cinahl’, ‘‘Biomedical Reference Collection: comprehensive’’ and ‘‘Nursing and Allied Health: Basic’’. In Pubmed, controlled terminology for these keywords was used. In PEDro (Physiotherapy Evidence Database) the strategy was adapted to ‘‘stroke’’ AND ‘‘patient discharge’’. The search was performed July 2014 by two independent researchers. Data collection process Selection was performed in different phases. Initially, studies were screened according to title and abstract with the inclusion and exclusion criteria. Screening was performed independently by two authors (K.V.d.C., R.R.), and when necessary, a third researcher (L.V. or W.S.) was consulted. The second step was screening on a full-text basis. Data were extracted from each included study and encompassed: (1) goal of the study, (2) study sample, (3) timing of assessment and statistical details, including a statistical parameter and confidence interval when possible (Table 1). Eligibility and inclusion criteria Studies were included if they reported prognostic factors for discharge destination in acute adult stroke patients. A study had to report original data and meet following eligibility criteria: (1) human adult stroke patients, (2) patient admitted to an acute hospital ward, (3) stroke defined according to the International

1215

Classification of Diseases, Ninth Revision (clinical modification) and if not defined, diagnosis confirmed by medical imaging (computed tomography or magnetic resonance imaging), (4) discharge destination was determined as an outcome measure and (5) study reports published in English, German, Dutch or French language. Quality of the studies The Scottish Intercollegiate Guidelines Network (SIGN) checklists evaluate different items, in four main topics: selection of subjects, assessment, identification of confounding factors and statistical analysis [38]. Because not all items were relevant for the evaluation of the included studies, the decision was made to include only studies that met the following four criteria: (1) an adequate definition of the included population and the eligibility criteria of the participants, (2) well described and stated outcome measures, (3) main conclusions were not based on secondary outcomes and (4) the possibility of confounders was described. A numerical weight was given to each of these items. Zero counted for not addressed, not reported or not applicable, one for poorly addressed, two for adequately addressed and three for well covered. Only studies scoring two or more on all items were included. Two independent raters, who were blinded to each other, assessed the items. If there was a lack of consensus between the two raters, a third rater was consulted.

Results Search strategy After consulting the databases, the initial search resulted in 1520 papers. Title and abstract were screened for eligibility and 122 studies were deemed relevant for further screening. Twelve articles were added by hand-screening the reference lists of included studies. Rejection was mainly based on participants in the study not meeting the inclusion criteria or the study not reporting prognostic factors for discharge destination. Finally, 18 studies were included in the qualitative synthesis of this review. The selection process is shown in the flow chart in Figure 1. Study characteristics The 18 studies included 10 cohort studies, seven cross-sectional studies and one case series report. Each study tried to identify factors that might be predictive for discharge destination for stroke patients after acute hospitalization. Eight studies only included ischemic stroke patients, two studies also included hemorrhagic stroke, three studies only hemorrhagic stroke and five studies described their population as stroke patients. Study sample sizes varied from 84 [39] to 720 287 patients [28], involving a total of 1 484 765 patients. Thirteen studies were performed in the United States of America, one in Australia, three in Canada and one in Europe (Table 1). Results of individual studies The prognostic factors for discharge destination are classified into five domains: initial medical care, neurological complications, medical comorbidities, physiological characteristic and environmental and socio-economic characteristics. In Appendix, the main results of the included studies are summarized, including a statistical parameter and confidence interval when possible. Three studies described potential prognostic factors of discharge destination, but did not report odds ratios nor levels of significance or other statistical values [25,27,40].

1216

K. Van der Cruyssen et al.

Disabil Rehabil, 2015; 37(14): 1214–1227

Table 1. Characteristics of the studies.

Authors Bohannon et al. [44] USA Diamond et al. [27] USA Flint et al. [49] USA Frontera et al. [28] USA

Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

Gregory and Han [51] USA Gregory et al. [52] USA Hakkeness et al. [46] Australia Hoh et al. [42] USA

Howrey et al. [43] USA

Goal of study Predictive variables of acute hospital outcome Relationship hematocrit levelDD-resource utilization Association statin use before and during stroke hospitalization and DD To assess the trends in hospitalizations for subdural Hemorrhage, its management, cost and DD To evaluate the rehabilitation disposition, comparison of factors associated with discharge To determine what factors are related with discharge to IRF Variables associated with discharge to IRF after acute severe stroke Weekend effect on thrombolytic use, in hospital mortality, DD, hospital charges and length of stay The association between hospitalists and outcome

Jaja et al. [41] Canada Mayo et al. [40] Canada

To determine ethnic differences in the use of post-acute care Predictive factors of DD

Onukwugha and Mullins [53] USA

To assess the evidence for racial differences in discharge disposition Association of guideline-recommended indices of renal insufficiency with DD Can this score predict DD

Ovbiagele et al. [39] USA Ovbiagele et al. Framingham [48] USA Razinia et al. [50] USA Saposnik et al. [25] Canada Stineman et al. [47] USA Van der Zwaluw et al. [45] the Netherlands

The impact of Body Mass Index on DD To evaluate in-hospital care, length of stay, complication rate, DD and case fatality To develop an index for establishing probability of discharge home Can cognitive functioning predict DD?

Study sample

Timing of assessments

Statistical analyses

92 ischemic stroke

Admission

1012 ischemic stroke

Retrospective

Pearson correlation, multiple regression Logistic regression

12 689 ischemic stroke

Retrospective

Logistic regression

720 287 subdural hematoma patie¨nts

Retrospective

Logistic regression

7810 patients with primary diagnosis of stroke

Retrospective

2, t-test, binary logit model

12 208 patients with acute stroke

Retrospective

2, t-test, logistic regression

108 patients with ischemic or hemorrhagic stroke

Admission

Logistic regression

599 087 patients with ischemic stroke

Retrospective

Generalized linear models

10 884 patients with ischemic stroke

Retrospective

31 631 patients with subarachnoid hemorrhage 3045 patients with hemorrhagic, infarction, ill-defined CVA 51 564 stroke patients

Retrospective

2, t-test, Kaplan–Meier tests, multi nominal logit models 2, ANOVA, multinominal logistic regression Cox’s proportional hazard models

Retrospective

Different models

84 patients with intracerebral hemorrhage

Within 24 h of ictus

2, logistic regression

434 ischemic stroke patients

At admission and discharge

logistic regression, multivariable regression

451 ischemic stroke patients 26 676 acute ischemic stroke patients

At admission and discharge Retrospective

2, logistic regression

6515 patients with acute stroke

Admission and discharge

188 patients with first ever cerebral stroke of any type

Within 8 days after admission, Barthel Index within 24 h

Retrospective

2 Pairwise statistical test, logistic regression, C-statistic Logistic regression, Pearson correlations

DD, discharge destination; IRF, inpatient rehabilitation facilities.

Initial medical care Patients admitted to academic teaching hospitals are sooner discharged home or to an IRF [40]. They have a lower odd of discharge to institutional care (short-term hospital) (OR: 0.64, 95% CI: 0.56–0.72) [41]. Hoh et al. studied whether there was a difference in discharge destination for weekday admissions to hospital versus weekend admissions (OR: 1.003, 95%CI: 0.981–1.025, p ¼ 0.802). They concluded that there was no difference [42]. Being cared for by doctors working full time in the hospital such as a general practitioner, an internist, a geriatrician or a

family medicine physician increases the odds of discharge to IRF (OR: 1.25, CI: 1.07–1.43, p50.001) [43]. Neurological complications When post-stroke functionality increases, the odd of discharge home increased (Barthel Index (BI) (Pearson’s correlation ¼ 0.535, p50.001) [44]. Moreover, a higher post-stroke functionality also shows that these patients are less likely to be admitted to further care (OR: 0.74, 95% CI: 0.67–0.82, p50.001) [45]. Indeed, the level of functionality both pre-stroke (modified Rankin Scale) (risk difference (95% CI) ¼ 0.28 (0.45, 0.12))

Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

DOI: 10.3109/09638288.2014.961655

Discharge destination after acute stroke

1217

Figure 1. Flow chart study selection. Adapted from Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group. Perferred reporting items for systematic reviews and meta.analayses:the prisma Statement. PLoSMed 2009;6:e1000097.doi:10.1371/journalpmed1000097. *Study not predicting prognostic factors discharge destination. **Study not performed in acute setting.

and post-stroke (Mobility Scale for Acute Stroke) (risk difference (95% CI) ¼ 2 (1.3)) is related with discharge to an inpatient rehabilitation unit [46]. A lower level of current mobility, as measured by the Mobility Scale for Acute Stroke, increases the odd of a dependent discharge destination (OR: 1.33, 95% CI: 1.04–1.71, p ¼ 0.023) [46]. The achievement of level IV (minimal assistance required for functioning) – V (supervision needed) (OR: 2.35, 95% CI: 1.74–3.17) and VI (functioning at modified independence except in bathing and climbing stairs) – VII (complete independence) (OR: 5.45, 95% CI: 3.52–8.45) in physical medicine and rehabilitation assessment at discharge was a strong predictor of home discharge [47]. Patients suffering severe stroke, measured by the National Institutes of Health Stroke Scale (NIHSS) had lower odds of returning home (Pearson’s correlation NIHSS score ¼ 0.355, p50.01; NIHSS score 5, 6 ¼ 0.344, p50.001) [40] and are more likely to be discharged to a less favorable destination, such as IRF (multivariate analyses: p50.0001) [48]. The presence of hemiplegia is associated with less favorable discharge outcome such as IRF or long-term nursing facility (logistic regression analysis, p50.001) [27]. Patients with a high score on the Cognitive Screening Test are less likely to be discharged to an IRF (OR: 0.72, 95% CI: 0.55–0.94, p50.05) [45]. In addition, it can

be detected that patients who achieve modified or complete cognitive independence on physical medicine and rehabilitation assessment at discharge have higher odds of being discharged home (OR: 4.65, 95% CI: 3.41–6.34) [47] (Figure 2). Medical comorbidities Frontera et al. noted an association between the score on the Charlson Comorbidity Index (CCI), which is a validated method of estimating risk of death from comorbid disease for use in longitudinal studies, and discharge destination (CCI 3–4 OR: 0.6, 95% CI: 0.6–0.6, p50.0001/CCI  5 OR: 0.5, 95% CI: 0.4–0.5, p50.0001) [28]. So, a higher score (indicating comorbidity is present) lowers the odds of discharge to more favorable discharge disposition, e.g. home or IRF and increases admittance to inpatient long-term nursing facilities (CCI  4: OR: 2.59, 95% CI: 2.26–2.97) [41]. Statin withdrawal during hospitalization (OR: 0.77, 95% CI: 0.63–0.94, p ¼ 0.012) [49], having encephalopathy (OR: 0.6, 95% CI: 0.5–0.6, p50.0001) [28], respiratory failure (OR: 0.2, 95% CI: 0.2–0.2, p50.0001) [28], brain herniation (OR: 0.2, 95% CI: 0.2–0.2, p50.0001) [28], pre-stroke dementia (OR: 0.6, 95% CI: 0.5–0.6, p50.0001) [27,28], acquired abnormality of platelet function (OR: 0.7, 95% CI: 0.6–0.7, p50.0001) [28] and coagulation factor (OR: 0.6, 95%

Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

1218

K. Van der Cruyssen et al.

Disabil Rehabil, 2015; 37(14): 1214–1227

Figure 2. Odds ratios of neurological comorbidities related to discharge destination. OR, odds ratios; CI, confidence interval; MSAS, Mobility Scale for Acute Stroke; mRS, modified Rankin Scale.

CI: 0.6–0.7, p50.0001) [28] and higher white blood cell counts at admission [39], all decrease the odds of being discharged to a favorable destination. A less favorable discharge destination like IRF or long-term nursing facility is related to numerous items: dementia, rheumatologic disease, peptic ulcer disease, liver disease or renal disease (logistic regression p ¼ 0.030) [27], diabetes (Spearman rank correlation statistic p ¼ 0.0004) [48] or a presumed hypertensive stroke mechanism (2 test p ¼ 0.005) [39]. Other factors increase the odds of discharge home: pre-stroke statin use (OR:1.21, 95% CI: 1.11–1.32, p50.001) [49], use of statins before and during hospitalization (OR:1.38, 95% CI: 1.25– 1.52, p50.001) [49] and higher admission hematocrit level (p ¼ 0.32) [39]. In contrast, Diamond et al. concluded that the probability of a less favorable (not home) discharge outcome increased at both high and low hematocrit levels (p ¼ 0.009) [27]. Elevated body mass index (BMI435) is associated with decreased odds of discharge home (OR: 0.42, 95% CI: 0.13–1.37; p value not presented) [50]. Alcohol abuse seems to relate with a lower chance of being referred to a favorable discharge destination like home or IRF (OR: 0.8, 95% CI: 0.8–0.9, p50.0001) [28] (Figure 3). Physiological characteristics Older patients are more likely to be discharged to a less favorable discharge destination such as IRF (Spearman rank correlation statistic: p ¼ 0.002) [27,40,48]. According to Gregory and Han [51], patients hospitalized in IRF are significantly older (60 y) than patients discharged home (560 y) (OR: 1.63, 95% CI: 1.31– 2.03, p ¼ 0.01) [51] Younger patients are more likely to be discharged home (Pearson correlation: 0.226, p50.05) [25,28,40,44,46]. Gregory and Han [51], even stated that patients younger than 60 years are more likely to be discharged home [51] (Figure 4). There is conflicting evidence about the role of gender. Men are more likely to be discharged home [40]. On the other hand, other

studies found that gender is not related to the discharge outcome (Pearson’s correlation, r: 0.022, p ¼ N/S) [44,52]. Race and ethnicity were a significant predictor of discharge to institutional care (short-term hospital) (p  0.001) [41]. Black people are more likely to be discharged to institutional care compared with Caucasian (OR: 1.27, 95% CI: 1.14–1.40) [41]. Onukwugha et al. specifically looked at black men who had significantly higher odds of being discharged to less desirable discharge locations (acute care general hospitals, rehabilitation facilities, nursing facilities, on-site psychiatric wards, sub-acute care facilities, hospice, other health care facilities) as compared to Caucasian males (OR: 1.66, 95% CI: 1.55–1.77) [53]. Similarly, black and Caucasian women are more likely to be discharged to less favorable discharge destinations, such as to an IRF or a longterm nursing facility compared to Caucasian males (OR: 1.38, 95% CI: 1.24–1.54) [53]. Patients of other minorities (American Indians, Asian/Pacific Islanders and other races) had significantly higher odds of being discharged to an acute inpatient rehabilitation unit (OR: 2.10, 95% CI: 1.15–3.83, p50.05 [51]; OR: 1.17, 95% CI: 0.99–1.37) [41]. In contrast, Jaja et al. concluded that Hispanic patients have even odds of discharge to institutional care than Caucasian (OR: 0.98, 95% CI: 0.87–1.09) [41]. According to Gregory et al. [52], hemorrhagic stroke decreases the odd of discharge to an IRF (OR: 0.60, 95% CI: 0.42–0.86, p50.05) [52]. Black patients with a hemorrhagic stroke have a higher likelihood of discharge to an IRF (OR hemorrhagic stroke  black race (stroke subtype combined with race): 1.71, 95% CI: 1.39–2.10, p50.05) [52]. However, Mayo et al. concluded that non-hemorrhagic stroke patients are more likely to be discharged to an IRF (no statistical values given) [40] (Figure 5). In comparison to Caucasian patients, black people were less often discharged home or to rehabilitation in a long-term nursing facility. The odds of discharge to an IRF increases when patients were living in a high socio-economic neighborhood (based on median household incomes) 40,51]. In rural populations there is no difference is rate of discharge between black and Caucasian patients [52].

Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

DOI: 10.3109/09638288.2014.961655

Discharge destination after acute stroke

1219

Figure 3. Odds rations of medical comorbidities related to discharge destination. OR, odds ratio; CI, confidence interval; CCI, Charlson Comorbidity Index.

Figure 4. Odds rations of physiological characteristics (age) related to discharge destination. OR, Odds rario; CI, confidence interval.

Environmental and socio-economic factors Being uninsured is associated with lower probability for further medical care (OR: 0.41, 95% CI: 0.33–0.51, no p-value presented) [53] and may also be associated with higher odds of discharge home (OR: 1.4, 95% CI: 1.2–1.5, p50.0001 [28]; OR: 0.48, 95% CI: 0.41–0.56 [41]). The type of insurance matters: patients with

health insurance (Medicare) are more likely to be discharged to an IRF (OR: 1.38, 95% CI: 1.15–1.66, p50.05/OR: 1.3, 95% CI: 1.2–1.4, p50.0001) [28,52], having a private insurance is associated with discharge to a range of more favorable discharge destinations such as an acute care general hospital, rehabilitation facilities, nursing and psychiatric facilities, sub-acute care

Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

1220

K. Van der Cruyssen et al.

Disabil Rehabil, 2015; 37(14): 1214–1227

Figure 5. Odds rations of physiological characteristics related to discharge destination. OR, odds rarios; CI, confidence interval.

Figure 6. Odds ratios of environmental and socio-economic factors related to discharge distionation. OR, odds ratio; CI, confidence interval; ICU, intense care unit.

facilities, hospice and other health care facilities (OR: 1.2, 95% CI: 1.2–1.3, p50.0001) [28]. Longer length of stay lowers the chance to discharge home and increases the probability to admittance to a dependent discharge destination, e.g. home with outpatient rehabilitation facility, a rehabilitation center or a nursing home (p50.001) [45]. Hakkeness et al. argued that length of stay is significantly shorter for those discharged to an IRF [46]. Contrast to Gregory et al. [52], who found no association between length of stay and discharge to IRF [52].

The role of marriage is conflicting as Onukwugha et al. detected lower odds of a less favorable discharge destination like a medical care facility when being married (OR: 0.76, 95% CI: 0.7– 0.82)[53], while Gregory et al. [52], showed no correlation (OR: 0.94, 95% CI: 0.83–1.07, p ¼ N/S) [52]. Several studies highlight the importance of the geographical living area [43,51,52]. Living in a rural or poor county – the latter defined as using the US Census Bureau Small Area Income And Poverty Estimates and designated at more than 15% percent

Discharge destination after acute stroke

DOI: 10.3109/09638288.2014.961655

poverty – was associated with a decrease in discharge to an IRF (OR: 0.45, 95% CI: 0.32–0.63, p50.01) [51] (Figure 6).

Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

Discussion Post-stroke discharge destination is influenced by a variety of factors. After initial medical care the neurological complications, medical comorbidities, physiological characteristics, environmental factors and socio-economic characteristics should be considered in the decision-making process for discharge destination. The evidence analyzed shows that younger age, good post-stroke functionality (as measured by the BI or the Mobility Scale for Acute Stroke), admission to a teaching hospital, and a number of medical factors are determinants to a favorable discharge destination. Determinants for unfavorable discharge destinations were a severe stroke, high BMI, alcohol abuse, statin withdrawal during hospitalization, the presence of comorbidities such as respiratory failure and dementia or having a Medicaid insurance. Different authors used different operationalization of the concept favorable versus unfavorable destinations. For some authors IRF are defined as favorable, while for others it was not. Return home was often determined as favorable, but returning home because of being uninsured may not be the most favorable outcome in the rehabilitation process after acute stroke. Almost all included studies were performed in the United States. In this country, initial treatment will not often be denied to these patients, but it is less likely that they will be discharged to rehabilitation facilities [53]. These financial issues may be less important in some European and Asian countries as all patients in these countries are entitled to rely on a national insurance scheme. This may influence the rate of discharge to inpatient rehabilitation. Intuitively one could think that stroke patients with rich social networks and adequate health insurance have higher odds of return home with targeted professional home care. However, this review does not highlight the importance of marital status. It has been argued that marital status protects men against institutionalization [54]. Female caregivers are more frequent and more willing to care for their husbands, while men often do not have enough experience in providing care. Being an inexperienced caregiver can lead to abstention of male caregivers to care for their spouses [55]. Therefore, it may not be surprising that women have doubled odds of being institutionalized [54]. The level of functional status can also be considered as the determining factor of discharge destination. One can assume that severe motor impairment will lower the odds of return home. Frank et al. reported, however, that preserved cognitive abilities increased the odd of returning home, despite the presence of a severe motor impairment. It appears that a combination of different factors like functionality, cognition, marital status is more important than one isolated factor. In this review, the hypothesized importance of the level of post-stroke functional status is not revealed. A possible explanation therefore is that the level of functionality is defined with different outcome measures (the modified Rankin Scale [46,50] and the BI [45,46]) and the fact that only three of the 18 articles evaluated this factor. Limitations of the study By only including original studies that were published in English, German, French or Dutch language, relevant studies may have been missed. However, the search was performed in seven digital databases and included all studies published until July 2014. We may also have missed some relevant information as we excluded many studies because of insufficient quality as scored by our criteria based on SIGN.

1221

This review aimed to identify prognostic factors for discharge destination after acute stroke. Because of the widespread variation of these factors that were researched in quite different contexts, this review remains largely descriptive. Suggestions for further research We would welcome more European based studies, as the health and insurance system seem to play such a prominent role. Because of the complex interaction in their living conditions, research could be directed to proactively look for factors related to the informal caregivers who play a role in the homes of the patients.

Conclusion The results of this systematic literature review imply that further research of discharge destination in acute stroke after initial medical care should focus on neurological comorbidities, medical complications, physiological characteristics and environmental/ socio-economic factors of a patient. Favorable factors for discharge home are being admitted to a teaching hospital, a high level of post-stroke functionality and cognitive independence, few medical comorbidities, being a young Caucasian patient and being uninsured. The latter is doubtful because in this instance financial concerns are the leading cause for the preferable discharge destination and may be of less importance in health systems with more inclusive coverage. having severe stroke or a high BMI, alcohol abuse, statin withdrawal during hospitalization, the presence of comorbidities such as respiratory failure and dementia or having a Medicaid insurance were determined as unfavorable factors.

Declaration of interest The authors report no conflict of interest.

References 1. Organisation WH. World Health Report 2002 – reducing risks, promoting healthy life. World Health Report; 2002. 2. Kaarisalo MM, Immonen-Raiha P, Marttila RJ, et al. Atrial fibrillation and stroke. Mortality and causes of death after the first acute ischemic stroke. Stroke 1997;28:311–15. 3. Sun H, Zou X, Liu L. Epidemiological factors of stroke: a survey of the current status in China. J Stroke 2013;15:109–11. 4. Myint PK, Vowler SL, Redmayne O, Fulcher RA. Cognition, continence and transfer status at the time of discharge from an acute hospital setting and their associations with an unfavourable discharge outcome after stroke. Gerontology 2008;54:202–9. 5. Petrilli S, Durufle A, Nicolas B, et al. Hemiplegia and return to domicile. Ann Readapt Med Phys 2002;45:69–76. 6. Stroke Association. Stroke Statistics: source World Health Report2002. Available from: http://wwwstrokecenterorg/patients/aboutstroke/stroke-statistics/ 2013. [last accessed July 2013]. 7. Prevalence of stroke–United States, 2006–2010. Centers for Disease Control and Prevention, 2013. Available from: http://www.cdc.gov/ stroke/facts.htm. [last accessed July 2013]. 8. Heart disease and stroke statistics – 2013 update. American Heart Association, Available from: http://circ.ahajournals.org/content/127/ 1/e6.full]. [last accessed July 2013]. 9. Stroke RCoPNS. Clinical Audit 2010 Round 7 Public report for England, Wales and Northern Ireland. Prepared on behalf of the Intercollegiate Stroke Working Party May 2011 P43. 2011. 10. Mittelmark MB, Psaty BM, Rautaharju PM, et al. Prevalence of cardiovascular diseases among older adults. The Cardiovascular Health Study. Am J Epidemiol 1993;137:311–17. 11. Wade DT, Wood VA, Hewer RL. Use of hospital resources by acute stroke patients. J R Coll Physicians Lond 1985;19:48–52. 12. Langton Hewer R. Rehabilitation after stroke. Quart J Med 1990;76: 659–74.

Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

1222

K. Van der Cruyssen et al.

13. Murray C, Lopez AD. Alternative projections of mortality and disability by cause 1990–2020: global burden of disease study. Lancet 1997;24:1498–504. 14. Department of Health & Human Services aoa. Profile of Older Americans; 2012. Available from: www.aoa.gov/aging_statistics/ profile/2013/6.aspx. 15. Department of Health & Human Services aoa. A profile of older Americans: 2012: living arrangements. 2012 (Based on online data from the U.S. Census Bureau’s American Community Survey. The Centers for Medicare and Medicaid Services’ Medicare Current Beneficiary Survey.) Available from: www.aoa.gov/aging_statistics/ profile/index.aspx. 16. Heart disease and stroke statistics. American Heart Association, 2004 update. Available from: http://circ.ahajournals.org/. [last accessed July 2013]. 17. Koyama T, Sako Y, Konta M, Domen K. Poststroke discharge destination: functional independence and sociodemographic factors in urban Japan. J Stroke Cerebrovasc Dis 2011;20:202–7. 18. Thijs V, Dewilde S, Putman K, Pince H. Cost of hospitalization for cerebrovascular disorders in Belgium. Acta Neurol Belg 2011;111: 104–10. 19. Brauer SG, Bew PG, Kuys SS, et al. Prediction of discharge destination after stroke using the motor assessment scale on admission: a prospective, multisite study. Arch Phys Med Rehabil 2008;89:1061–5. 20. Miyamoto H, Hagihara A, Nobutomo K. Predicting the discharge destination of rehabilitation patients using a signal detection approach. J Rehabil Med 2008;40:261–8. 21. Freburger JK, Holmes GM, Ku LJ, et al. Disparities in postacute rehabilitation care for stroke: an analysis of the state inpatient databases. Arch Phys Med Rehabil 2011;92:1220–9. 22. Herman JM, Culpepper L, Franks P. Patterns of utilization, disposition, and length of stay among stroke patients in a community hospital setting. J Am Geriatr Soc 1984;32:421–6. 23. Nuyen J, Spreeuwenberg PM, Groenewegen PP, et al. Impact of preexisting depression on length of stay and discharge destination among patients hospitalized for acute stroke: linked register-based study. Stroke 2008;39:132–8. 24. Ovbiagele B, Sanossian N, Liebeskind DS, et al. Indices of kidney dysfunction and discharge outcomes in hospitalized stroke patients without known renal disease. Cerebrovasc Dis 2009;28:582–8. 25. Saposnik G, Black S. Stroke in the very elderly: hospital care, case fatality and disposition. Cerebrovasc Dis 2009;27:537–43. 26. Nagaraja N, Bhattacharya P, Mada F, et al. Gender based differences in acute stroke care in Michigan hospitals. J Neurol Sci 2012;314: 88–91. 27. Diamond PT, Gale SD, Evans BA. Relationship of initial hematocrit level to discharge destination and resource utilization after ischemic stroke: a pilot study. Arch Phys Med Rehabil 2003;84:964–7. 28. Frontera JA, Egorova N, Moskowitz AJ. National trend in prevalence, cost, and discharge disposition after subdural hematoma from 1998–2007. Crit Care Med 2011;39:1619–25. 29. Lai SM, Alter M, Friday G, et al. Disposition after acute stroke: who is not sent home from hospital? Neuroepidemiology 1998;17: 21–9. 30. Kumlien S, Axelsson K, Ljunggren G, Winblad B. Stroke patients ready for discharge from acute care-a multi-dimensional assessment of functions and further care. Disabil Rehabil 1999;21:31–8. 31. Henley S, Pettit S, Todd-Pokropek A, Tupper A. Who goes home? Predictive factors in stroke recovery. J Neurol Neurosurg Psychiatr 1985;48:1–6. 32. Hakkennes SJ, Brock K, Hill KD. Selection for inpatient rehabilitation after acute stroke: a systematic review of the literature. Arch Phys Med Rehabil 2011;92:2057–70. 33. Meijer R, van Limbeek J, Kriek B, et al. Prognostic social factors in the subacute phase after a stroke for the discharge destination from the hospital stroke-unit. A systematic review of the literature. Disabil Rehabil 2004;26:191–7. 34. Maeshima S, Osawa A, Miyazaki Y, et al. Influence of dysphagia on short-term outcome in patients with acute stroke. Am J Phys Med Rehabil 2011;90:316–20.

Disabil Rehabil, 2015; 37(14): 1214–1227

35. Ohwaki K, Hashimoto H, Sato M, et al. Gender and family composition related to discharge destination and length of hospital stay after acute stroke. Tohoku J Exp Med 2005;207:325–32. 36. Schlegel DJ, Tanne D, Demchuk AM, et al. Prediction of hospital disposition after thrombolysis for acute ischemic stroke using the National Institutes of Health Stroke Scale. Arch Neurol 2004;61: 1061–4. 37. Moher D, Liberati A, Tetzlaff JF, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 2009;151:264–9. 38. Scottish International Guidelines Network: methodology checklist; 2013. Available from: http://www.sign.ac.uk/methodology/checklists.html. [last accessed July 2014]. 39. Ovbiagele B, Pineda S, Saver JL. Renal dysfunction and discharge destination in patients with intracerebral hemorrhage. J Stroke Cerebrovasc Dis 2011;20:145–49. 40. Mayo NE, Hendlisz J, Goldberg MS, et al. Destinations of stroke patients discharged from the Montreal area acute-care hospitals. Stroke 1989;20:351–6. 41. Jaja BN, Saposnik G, Nisenbaum R, et al. Racial/ethnic differences in inpatient mortality and use of institutional postacute care following subarachnoid hemorrhage. J Neurosurg 2013;119: 1627–32. 42. Hoh BL, Chi YY, Waters MF, et al. Effect of weekend compared with weekday stroke admission on thrombolytic use, in-hospital mortality, discharge disposition, hospital charges, and length of stay in the Nationwide Inpatient Sample Database, 2002 to 2007. Stroke 2010;41:2323–8. 43. Howrey BT, Kuo YF, Goodwin JS. Association of care by hospitalists on discharge destination and 30-day outcomes after acute ischemic stroke. Med Care 2011;49:701–7. 44. Bohannon RW, Lee N, Maljanian R. Postadmission function best predicts acute hospital outcomes after stroke. Am J Phys Med Rehabil 2002;81:726–30. 45. Van der Zwaluw CS, Valentijn SA, et al. Cognitive functioning in the acute phase poststroke: a predictor of discharge destination? J Stroke Cerebrovasc Dis 2011;20:549–55. 46. Hakkennes S, Hill KD, Brock K, et al. Accessing inpatient rehabilitation after acute severe stroke: age, mobility, prestroke function and hospital unit are associated with discharge to inpatient rehabilitation. Int J Rehabil Res 2012;35:323–9. 47. Stineman MG, Kwong PL, Bates BE, et al. Development and validation of a discharge planning index for achieving home discharge after hospitalization for acute stroke among those who received rehabilitation services. Am J Phys Med Rehabil 2014;93: 217–30. 48. Ovbiagele B, Liebeskind DS, Kim D, et al. Prognostic value of Framingham cardiovascular risk score in hospitalized stroke patients. J Stroke Cerebrovasc Dis 2011;20:222–6. 49. Flint AC, Kamel H, Navi BB, et al. Inpatient statin use predicts improved ischemic stroke discharge disposition. Neurology 2012;78: 1678–83. 50. Razinia T, Saver JL, Liebeskind DS, et al. Body mass index and hospital discharge outcomes after ischemic stroke. Arch Neurol 2007;64:388–91. 51. Gregory PC, Han E. Disparities in postacute stroke rehabilitation disposition to acute inpatient rehabilitation vs. home: findings from the North Carolina Hospital Discharge Database. Am J Phys Med Rehabil 2009;88:100–7. 52. Gregory PC, Han E, Morozova O, Kuhlemeier KV. Do racial disparities exist in access to inpatient stroke rehabilitation in the state of Maryland? Am J Phys Med Rehabil 2006;85: 814–19. 53. Onukwugha E, Mullins CD. Racial differences in hospital discharge disposition among stroke patients in Maryland. Med Decis Making 2007;27:233–42. 54. Kelly-Hayes M, Wolf PA, Kannel WB, et al. Factors influencing survival and need for institutionalization following stroke: the Framingham Study. Arch Phys Med Rehabil 1988;69:415–18. 55. Agarwal V, McRae MP, Bhardwaj A, Teasell RW. A model to aid in the prediction of discharge location for stroke rehabilitation patients. Arch Phys Med Rehabil 2003;84:1703–9.

Frontera et al. [28] USA

Flint et al. [49] USA

Diamond et al. [27] USA

Bohannon et al. [44] USA

Authors

1.96–1.27

1.16*

1.2–1.4 1.2–1.3 1.2–1.5

1.2* 1.4*

0.8–0.9

0.8–0.9 0.7–0.8 0.5–0.6 0.3–0.41 0.9–0.9

1.3*

Medicaid insurance Private insurance Uninsured

0.9* 0.7* 0.6* 0.3* 0.9*

Age 65–69 Age 70–74 y Age 75–79 y Age 80 y Gender, female

0.8–0.9

Insurance

0.9*

Age 60–64 y

0.8*

Gender

Multivariate logistic regression multivariate logistic regression Multivariate logistic regression

0.63–0.94

0.77*

1.1–1.11

1.25–1.52

1.38*

1.1*

1.11–1.32

NR

1.21*

NR*

NR

NR

NR

NR NR

NR

NR

NR

95% confidence interval

Alcohol abuse

Age

Year of hospitalization

Statin use

Multivariate logistic regression

NR

50 y

Hematocrit level

Adjusted ordinary logistic regression Generalized ordered logistic regression Generalized ordered logistic regression Generalized ordered logistic regression Adjusted logistic regression Multivariate logistic regression

NR*

NR*

Comorbidities

Hemi/paraplegia

NR*

Age

Adjusted ordinary logistic regression

Adjusted ordinary logistic regression Adjusted ordinary logistic regression

NR NR

Age Gender

NR

NR*

Pearson correlation Pearson correlation

Functionality (Barthel Index)

Stroke severity

Odds ratio

NR

Mean 68 y

36 y–98 y

Variable

Subcategory variable

Pearson correlation

Pearson correlation

Pearson correlation

Statistical analyses

Age range population

Table A1. Summary of the main results of the included studies including a statistical parameter and confidence interval.

Appendix

NR

NR

NR

NR

NR NR NR NR NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

0.226y 0.022

0.246y

NIHSS: 0.355; NIHSS 5,6: 0.344 0.535*

Pearson correlation coe¨fficient

Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

(continued )

Having medicaid insurance ! higher odd of an unsatisfactory destination Being uninsured ! higher odd of a favorable discharge destination

Being older ! lower odd of a favorable discharge destination

Favorable disposition: home or self-care; home under care of organized home health service organization, home intravenous provider, inpatient rehabilitation facility

Diagnoses related to comorbidity categories (dementia, rheumatologic, peptic ulcer, mild liver, renal or moderate or severe liver disease) ! less favorable discharge destination Hemi-/paraplegia is related to discharge destination (home, home with organized home care service, rehabilitation hospital, skilled nursing facility, interpediate care) High or low hematocrit level ! less favorable discharge destination Use before hospitalization ! more likely referred home (54.6% statin users $ 50% non-users) Use before and during hospitalization ! more likely home((56.5% statin user $ 47.3% non-users) Withdrawal in-hospital ! less likely discharge home (39.1% withdrawal $ 54.9% continuation) Inpatient treatment ! improved discharge destination (home)

Older ! less favorable discharge destination

Barthel Index ¼ 20 (prestroke functional independence) ! more likely referred home Younger ! more likely home No significant correlation

Higher post-stroke function ! more likely home

More severe stroke patients ! less likely being discharged home

Qualitative synthesis

Gregory et al. [52] USA

Authors

0.6–0.7

0.6–0.7

1.1–1.2 0.6–0.6

0.4–0.5

0.6* 0.7*

0.6*

1.1* 0.6*

0.5*

Dementia Acquired abnormality platelet function Acquired abnormality in coagulation factors Burr hole drainage Charlson Comorbidity Index: 3–4 Charlson Comorbidity Index: 5

Race Stroke subtype Stroke subtype/race Insurance Length of stay

Logistic regression

Logistic regression

Logistic regression

Logistic regression

1.05y

1.38y

1.71y

0.60y

1.19

1.44y

Living environment/Race

NR

NR

1.04–1.06

1.15–1.66

1.39–2.10

0.42–0.86

0.88–1.62

1.07–1.93

1.36–1.84

NR

NR

1.58y

Black

0.9–0.9 0.2–0.2

0.9* 0.2* 0.5–0.6

0.2–0.2

0.5–0.6

2.1–2.9

95% confidence interval

0.2*

0.6*

2.5*

Odds ratio

Respiratory failure Trauma Herniation

Emergent/elective admission Encephalopathy

Subcategory variable

Living environment

Logistic regression

Logistic regression

Living environment

Comorbidities

MultivAriate logistic regression

NR

Admission

Variable

Multivariate logistic regression

Statistical analyses

Age range population

Table A1. Continued

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR NR

NR

NR

NR

Pearson correlation coe¨fficient

Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

Rural population: no difference in rate of discharge to inpatient rehabilitation facilities and other destinations Rural’s population rate of discharge to inpatient rehabilitation facilities was 50% of that of black and white patients in the urban population Living in an urban area ! higher odds of discharge to inpatient rehabilitation facilities Urban population: black and white equally discharged to rehabilitation in a skilled nursing facility/there is a greater rate of discharge to inpatient rehabilitation facilities among black and white patients. No significant association between black patients and discharge to inpatient rehabilitation facilities Having a hemorrhagic stroke is ! less likely discharge inpatient rehabilitation facilities Blacks with hemorrhagic stroke ! more likely to be discharged to inpatient rehabilitation facilities Having a medicare insurance ! more likely discharge to inpatient rehabilitation facilities

a higher score on the Charlson Comorbidity Index ! lower odd of a favorable discharge destination

An acquired abnormality in coagulation factors ! lower odd of a good discharge destination

Having brain herniation ! lower odd of a favorable discharge destination Having dementia ! lower odd of a favorable discharge destination An acquired abnormality in platelet function ! lower odd of a favorable discharge destination

Having encephalopathy ! lower odd of a favorable discharge destination Having respiratory failure ! lower odd of a favorable discharge destination

emergent ! favorable discharge destination

Qualitative synthesis

0.24–0.36

0.30*

0.64*

Rural county

Specialist

Race

66 y

418 y

Multinomial logistic regression

Multinominal logistic regression

Howrey et al. [43] USA

Jaja et al. [41] Canada

1.14–1.40

0.87–1.09

0.98*

1.07–1.43

0.981–1.025

1.27*

1.24*

1.003

0.77

Cognition Day of admission

0.75–101.49

8.71

72.9 y ± 13.5

2.02–85.95

13.17*

0.57–1.04

1.04–1.71

0.80–0.95

0.48–0.85

0.32–0.63

1.33*

0.87*

0.45*

Poor county

1.60–2.32

0.03–0.07

0.05*

1.93*

1.15–3.83 0.89–1.29 0.00–0.02

1.31–2.03

0.83–1.07

0.92–1.19

2.10y 1.07 0.00*

1.63*

Age 60 y

Male Therapy charges ¼ $0 Therapy charges 4$0  $500 Therapy charges 4$500 ICU  $1000

0.94

1.05

Married

Male

Mobility Scale for Acute Stroke (MSAS) Modified Rankin Scale (mRS) Continence (bladder)

Generalized linear

Multilevel logistic regression Multilevel logistic regression Multilevel logistic regression Multilevel logistic regression

Age

Living environment

Logistic regression

44–92 y

ICU charges

Logistic regression

Multilevel logistic regression

Race Gender Therapy charges

Logistic regression Logistic regression Logistic regression

Age

Logistic regression

NR

Marital status

Logistic regression

Gender

Hoh et al. [42] USA

Hakkeness et al. [46] Australia

Gregory and Han [51] USA

Logistic regression

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR NR NR

NR

NR

NR

Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

(continued )

Black patients ! more likely discharge to post-acute institutional care

Hospitalist (general practitioner, internest, geriatrician, family medicine physician) ! more likely discharge to inpatient rehabiliation facilities No sign differences in the group hospitalist vs non-hospitalist in odd of discharge to a skilled nursing facility

Weekday or weekend admissions give no difference in discharge disposition

Current mobility (MSAS) ! discharge to inpatient rehabilitation facilities. Patients who were pre stroke functionally independent ! more likely to be discharged to inpatient rehabiliation facilities. Discharge to inpatient rehabilitation facilities ! more likely continent Lower impairment in cognition ! discharge to inpatient rehabilitation facilities

Younger patients ! discharge to inpatient rehabilitation facilities

Higher intensive care unit charges ! more likely discharge to inpatient rehabiliation facilities. Living in counties with less poverty and an urban location ! more likely discharge to inpatient rehabiliation facilities. Living in rural or poor countyhome ! more likely discharge home

Being older 60 y ! more likely discharge to inpatient rehabilitation facilities/younger 60 y ! more likely to be discharged home Other minorities ! less likely inpatient rehabilitation facilities No correlation gender and discharge destination Lower therapy charges are related with a higher odd of discharge home.

Length of stay ! more likely discharge to inpatient rehabilitation facilities No correlation between gender and discharge to inpatient rehabilitation facilities No correlation between being married and discharge to inpatient rehabilitation facilities

Proportional- odds model (ordered- logit model)

Multivariate logistic regression

Ovbiagele et al. [39] USA

Cox’s proportional hazard Cox’s proportional hazard Cox’s proportional hazard Cox’s proportional hazard

Cox’s proportional hazard

Statistical analyses

Onukwugha et al. [53] USA

Mayo et al. [40] Canada

Authors

25 y–96 y

NR

0.41

No insurance Hemorrhagic

Health care insurance Type of stroke

NR NR* NR NR NR 0.24

Age Severity of stroke White blood cells Cause of stroke Hematocrit level Estimated glomerular filtration rate (eGFR)

0.38

0.76

Marital status

1.05

Lenght of stay in ICU in days

Length of stay

1.16

White female 1.01

1.38

Black female

Age

1.66

Black male

NR

NR

Gender

NR

NR

Socio-economic status/ environment Gender

0.04–1.39

NR

NR

NR NR

NR

0.35–0.41

0.33–0.51

0.70–0.82

1.03–1.07

1.01–1.01

1.10–1.21

1.24–1.54

1.55–1.77

NR

NR

Type of stroke

NR

NR

0.99–1.37

1.17* NR*

95% confidence interval

Odds ratio

NR

Kind of hospital

2/3  65 y

Subcategory variable

Age

Variable

Age range population

Table A1. Continued

NR

NR

NR

NR NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

Pearson correlation coe¨fficient

Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

Higher admission NIHSS ! lower likelihood of discharge home Higher admission peripheral WBC count !lower likelihood of discharge home Presumptive hypertensive stroke mechanism ! lower likelihood of discharge home Higher admission hematocrit ! higher likelihood of discharge home Patients with low estimated glomerular filtration rate ! less likely discharged home

Older patients ! lower likelihood of discharge home

Black males ! higher odds of being discharged to a less favorable discharge destination (a medical care facility (acute-care general hospitals, rehabilitation facilities, nursing facilities, on-site psychiatric wards, subacute care facilities, hospice, other health care facilities) as compared to white males Black females ! higher odd of a less favorable discharge destination compared to white males White females ! higher odd of less favorable discharge destination compared to white males Older patients ! higher odd of less favorable discharge destination compared to younger patients Patients with longer ICU length of stay compared to those spending little time in ICU ! higher odd of less favorable discharge destination Married patients ! lower odds of a less favorable discharge destination Uninsured patients ! lower odds of a less favorable discharge destination Hemorrhagic stroke !lower odd of a less favorable discharge destination

Younger patients ! more likely to be discharged to inpatient rehabiliation facilities. Non- hemorrhagic stroke ! more likely discharge to inpatient rehabilitation facilities Living in a high socio-economic status neigherborhood ! discharge to inpatient rehabilitation facilities Men ! more likely to be discharged home

Hispanic and white patients ! similar in likelihood of discharge to institutional care Asian Pacific Islander patients ! more likely discharge institutional care Teaching hospitals discharged sooner to long-term care, rehabilitation centers, home

Qualitative synthesis

Logistic regression

Stineman et al. [47] USA

Age Length of stay

Functionality (Barthel Index) Cognition

Cognitive screening test Mini Mental State Examination Clock-drawing test

2.26* 4.65*

Cognition

440 y, mean 71.3 ± 11.7 y

2.35* 5.45*

Functionality

560 y ! 80 y

0.88–1.93

1.3

0.99–1.07 NR

0.97–1.48

1.19

1.02 NR*

0.55–0.94

0.67–0.82 0.72y

0.74*

1.76–2.88 3.41–6.34

1.74–3.17 3.52–8.45

0.13–1.37

Adjusted: 0.42

Age

0.25–1.72

0.04–0.86

Unadjusted: 0.65

569 y ! 90 y

0.18*

BMI

Framingham Cardiovascular Risk Score

NR

NR

0.83–0.89

NR

0.86*

Severity of stroke (National Institute of Health Stroke Scale [NIHSS]) Thrombolytic intervention White blood cells

NR

NR

0.07–2.58 0.02–1.76

NR*

NR*

Serum glucose level

NR*

18 y/mean 65 (range 83–101 y)

median 66.5 y

0.41 0.20

NR NR

NR

NR

NR

NR

NR NR

NR NR

NR

NR

NR

NR

NR

NR

NR

NR

NR

NR NR

Age not related to discharge destination Longer length of stay ! dependent discharge destination (home with outpatient rehabilitation facility, rehabilitation center, nursing home)

Clock-drawing not related to discharge destination

Mini Mental State Examination not discharge destination

Higher Cognitive Screening Test ! more likely home

Higher Barthel Index ! more likely discharge home

Cognitive stage II ! determinant of discharge home Cognitive stage VI ! determinant of discharge home

Physical grades IV/V ! determinant of discharge home Physical grades VI/VII ! determinant of discharge home

Difference in discharge destination among all age groups, 490 y ! 55% decrease in odischarge destinations of discharge home compared with their counterparts 80–89 y

Highest BMI category (BMI435) ! less likely discharge directly home

Thrombolytic intervention ! less favorable discharge destination Higher admission peripheral WBC count ! less favorable discharge destination After adjusting for confounders: Framingham Cardiovascular Risk Score associated with decrease in likelihood of discharge directly home

Higher serum glucose level ! less favorable discharge destination Higher adm NIHSS ! less favorable discharge destination

Older patients ! higher odds of a less favorable discharge destination

Patients with protenuria ! less likely discharged home Patients with low estimated glomerular filtration rte and protenuria ! less likely discharged home

p: level of significance; NR, not reported; r, Pearson’s correlation coe¨fficient; MMSE, Mini Mental State Examination; FCRS, Framingham Cardiovascular Risk Score; MSAS, Mobility Scale for Acute Stroke; mRS, modified Rankin Scale; NIHSS, National Institues of Health Stroke Scale; ICU, Intensive Care Unit; BMI, body mass index; WBC, white blood cells. *p50.01; yp50.05.

Van der Zwaluw et al. [45] the Netherlands

Multivariable analysis

Saposnik et al. [25] Canada

Logistic regression

Logistic regression

Spearman rank correlation statistics Spearman rank correlation statistics Multivariable regression

Spearman rank correlation statistics Multivariable regression

Spearman rank correlation statistics

Razinia et al. [50] USA

Ovbiagele et al. Framingham [48] USA

Proteinuria Estimated glomerular filtration rate and proteinuria Age

Downloaded by [University of Prince Edward Island] at 14:57 05 November 2015

Prognostic factors for discharge destination after acute stroke: a comprehensive literature review.

In the future, budget constraints will make efficient care for stroke patients more important. The cost of hospitalization for stroke is high. It is d...
2MB Sizes 0 Downloads 12 Views