Background
Stroke is a leading cause of disability [
1,
2]. Patients with mild stroke in the acute phase are usually discharged within a short period after stroke onset [
3]. However, patients who need assistance in activities of daily living (ADL) after acute treatment require intensive rehabilitation. In Japan, subacute stroke patients still assisted in ADL after treatment in acute hospitals have been transferred to the convalescent rehabilitation wards and have undergone intensive rehabilitation since 2000 [
4]. From 2000 to 2006, patients were admitted within three months of stroke onset as subacute stroke patients; from 2006 to 2020, within two months [
4]; and after 2020, no longer depends on the duration from stroke onset. In convalescent rehabilitation wards, the maximum length of stay covered by the insurance is 150 days for stroke, 180 days for stroke with severe disability and cognitive disorders, and the maximum rehabilitation time for stroke patients is 3 h per day, including weekends (21 h per week) [
4]. Subacute stroke patients who are admitted to convalescent rehabilitation wards undergo rehabilitation to improve their ADL or return to their homes [
4]. Discharge planning for patients is a vital topic in subacute stroke rehabilitation. Appropriate discharge destination planning for inpatients following a stroke can enhance reasonable use of healthcare resources, improve clinical outcomes, and decrease the financial burden of patients [
5]. Thus, in the rehabilitation pipeline for subacute stroke patients, accurate prediction of the possibility of home discharge from the early stage of hospitalization is important.
Previous studies have reported factors related to home discharge in patients with subacute stroke with an onset of about 30 days [
6‐
18]. In particular, many studies have consistently suggested that functional disability is related to home discharge. In a meta-analysis, for every 1-point increase in the Functional Independence Measure (FIM), a stroke patient was 1.08-times more likely to be discharged home than to institutionalized care [
6]. Moreover, in a systematic review, marital status and social support were associated with the discharge destination [
7]. Therefore, functional disability and social factors are essential factors for predicting home discharge. Additionally, demographic characteristics such as age [
8], sex [
9], and duration of hospitalization [
10] were associated with home discharge. However, few studies have predicted home discharge based on the severity of post-stroke impairments, such as physical function [
11,
17] and cognitive impairment [
8]. Therefore, it is necessary to investigate these various factors, including common post-stroke impairments.
Cognitive impairment is a common symptom in patients with stroke. The prevalence of cognitive impairment within one-year post-stroke was 38%, according to a systematic review [
19]. Moreover, post-stroke cognitive impairment has been reported to be associated with dependency [
20] and increased costs for utilization of care [
21]. However, to date, no studies have investigated the relationship between home discharge and general cognitive impairment in subacute stroke patients by multivariable analysis.
Therefore, this study aimed to explore the factors associated with home discharge in subacute stroke patients, adding cognitive function to other factors reported in previous studies such as FIM, social factors, demographic characteristics, and physical function.
Results
The characteristics of the study participants are listed in Table
1. The mean age ± standard deviation of the 1,229 patients with stroke was 68.7 ± 13.5 years. There were 1,011 participants (82.3%) in the home discharge group and 218 participants (17.7%) in the facility discharge group. Male sex, cerebral infarction, right brain side being affected, and not living alone were factors more likely to be associated with the home discharge group; these patients also had a younger age, shorter duration from stroke onset to admission, shorter hospital duration, and higher BMI, MMSE score, SIAS-m score, grip strength, and FIM score than those in the facility discharge group (
P < 0.050).
Table 1
Characteristics of the study participants
Age, ya | 68.7 (13.5) | 66.5 (13.3) | 78.7 (8.9) | < 0.001 |
Sex (men)b | 728 (59.2) | 645 (63.8) | 83 (38.1) | < 0.001 |
BMI, kg/m2 a | 21.8 (3.2) | 22.2 (3.2) | 20.4 (3.1) | < 0.001 |
Stroke type (cerebral infarction)b | 735 (59.8) | 589 (58.3) | 146 (67.0) | 0.017 |
Brain side affected (right)b | 667 (54.3) | 530 (52.4) | 137 (62.8) | 0.005 |
Duration from stroke onset to admissiona | 32.2 (12.7) | 31.1 (12.3) | 37.2 (13.5) | < 0.001 |
Hospital durationa | 88.5 (45.3) | 82.4 (44.9) | 116.9 (35.6) | < 0.001 |
Living circumstance (alone)b | 225 (18.3) | 157 (15.5) | 68 (31.2) | < 0.001 |
MMSE score at admissiona | 23.5 (6.2) | 24.8 (5.3) | 17.4 (6.6) | < 0.001 |
Grip strength at admission, kgfa | 24.2 (10.5) | 26.1 (10.0) | 15.2 (8.4) | < 0.001 |
SIAS-m U/E score at admission (0–10) c | 7 (3–8) | 8 (3–9) | 3 (0–8) | < 0.001 |
SIAS-m L/E score at admission (0–15)c | 12 (6–13) | 12 (8–14) | 6 (1–12) | < 0.001 |
FIM motor score at admissionc | 51 (32–68) | 56 (40–71) | 24 (17–37) | < 0.001 |
FIM cognitive score at admissionc | 26 (20–31) | 28 (23–32) | 17 (13–22) | < 0.001 |
FIM total score at admissionc | 78 (54–96) | 84 (65–101) | 42 (32–57) | < 0.001 |
FIM motor score at dischargec | 82 (67–88) | 85 (76–88) | 48 (34–65) | < 0.001 |
FIM cognitive score at dischargec | 31 (25–35) | 32 (28–35) | 22 (17–27) | < 0.001 |
FIM total score at dischargec | 112 (93–121) | 116 (105–122) | 70 (52–91) | < 0.001 |
Multivariable logistic regression analysis was performed to identify variables associated with home discharge (Table
2). The factors at admission significantly associated with home discharge were age (odds ratio [OR], 0.93; 95% confidence interval [CI], 0.91 – 0.96;
P < 0.001), duration from stroke onset (OR, 0.98; 95% CI, 0.96 – 0.99;
P = 0.003), living situation (OR, 4.40; 95% CI, 2.69 – 7.20;
P < 0.001), MMSE score (OR, 1.05; 95% CI, 1.00 – 1.09;
P = 0.035), FIM motor score (OR, 1.04; 95% CI, 1.01 – 1.06;
P = 0.001), and FIM cognitive score (OR, 1.08; 95% CI, 1.04 – 1.13;
P < 0.001). There were no factors with variance inflation rate ≥ 5. The Hosmer–Lemeshow test shows
P = 0.944 and the percentage of correct classification is 88.3%, which indicates a good fit for the regression model.
Table 2
Multivariable logistic regression analysis of the home discharge
Age | 0.93 | 0.91 | 0.96 | < 0.001 | 2.06 |
Sex |
Women | 0.98 | 0.57 | 1.69 | 0.947 | 1.94 |
Men (reference) | Reference | | |
BMI | 1.03 | 0.96 | 1.10 | 0.431 | 1.23 |
Stroke type |
Cerebral hemorrhage | 1.17 | 0.73 | 1.85 | 0.519 | 1.29 |
Cerebral infarction (reference) | Reference | | |
Brain side affected |
Left | 1.38 | 0.90 | 2.12 | 0.144 | 1.09 |
Right (reference) | Reference | | |
Duration from stroke onset to admission | 0.98 | 0.96 | 0.99 | 0.003 | 1.08 |
Living circumstance |
Not alone | 4.40 | 2.69 | 7.20 | < 0.001 | 1.03 |
Alone (reference) | Reference | | |
MMSE score | 1.05 | 1.00 | 1.09 | 0.035 | 2.42 |
Grip strength | 1.03 | 0.99 | 1.06 | 0.166 | 3.13 |
SIAS-m U/E score | 1.03 | 0.93 | 1.15 | 0.560 | 3.63 |
SIAS-m L/E score | 1.07 | 0.99 | 1.16 | 0.105 | 4.17 |
FIM motor score | 1.04 | 1.01 | 1.06 | 0.001 | 4.16 |
FIM cognitive score | 1.08 | 1.04 | 1.13 | < 0.001 | 2.81 |
Discussion
We investigated factors associated with home discharge in patients with subacute stroke. Multivariable logistic regression analysis revealed that age, duration from stroke onset to admission, living situation, MMSE score at admission, FIM motor score at admission, and FIM cognitive score at admission were significantly associated with home discharge.
The MMSE score at admission was significantly associated with home discharge. While a previous study also reported that the MMSE score is associated with home discharge [
8], the examination was limited to univariate analysis. To date, this is the first study to investigate the relationship between home discharge and MMSE score for stroke patients in a multivariable analysis. We found a significant association between home discharge and MMSE score, even after adjusting for factors associated with home discharge. The MMSE may be a predictor of home discharge in subacute stroke patients. Therefore, assessing the MMSE at admission in the subacute phase can lead to appropriate discharge support following intensive rehabilitation.
Furthermore, it was shown that besides the MMSE, the FIM cognitive score was also associated with home discharge. Many previous studies have reported on the association between FIM cognitive score and discharge [
9,
11,
12,
17]. Although both are cognitive assessments, the MMSE evaluates cognitive impairment such as that affecting memory, attention, and executive function, and the FIM cognitive scale evaluates cognitive disability in ADL. Specifically, the severity of cognitive impairment and amount of assistance related to cognitive disability affect home discharge independently. For example, a previous study of Alzheimer's disease reported that the severity of cognitive impairment did not correlate with the severity of burden; instead, anosognosia and behavioral abnormalities are associated with care burden [
31]. Similarly, in stroke patients, it is essential to evaluate cognitive function from the functional and ADL aspects to predict home discharge accurately.
Multivariable logistic regression analysis revealed that age, duration from stroke onset to admission, living situation, and FIM motor score at admission were also associated with home discharge in subacute stroke patients. Previous studies have reported the association between discharge and age [
8], duration from stroke onset to admission [
14], social factors [
7‐
9,
11,
15,
17], and FIM score [
6,
8,
10,
16]; these findings are consistent with our findings. Therefore, it is essential to prepare for home discharge by assessing cognitive function and considering age, social factors, and ADL ability at admission in subacute stroke patients.
The strength of this study is the use of large-scale data to comprehensively identify factors associated with home discharge of subacute stroke patients, including demographic characteristics, functional impairment, and disability. Investigation of factors associated with home discharge requires large-scale data studies to consider confounding factors. Thus, the results of this study, using large-scale data and including functional outcomes such as SIAS-m score, grip strength, and MMSE score, are important findings regarding the rehabilitation of subacute stroke patients.
However, this study had some limitations. First, we used the MMSE scores to determine cognitive impairment; thus, we excluded patients with disturbance of consciousness and aphasia. Cognitive function may be associated with home discharge, even in patients with aphasia. Thus, future studies using nonverbal cognitive assessments are needed. Similarly, we used the SIAS-m scores to determine motor function; thus, we excluded patients with bilateral cerebral lesions. The inclusion of patients with bilateral motor paralysis may reveal different associated factors compared to this study. Second, data related to the location of the brain lesion, such as stroke subtypes, region, volume, or dominance, were not collected. Several previous studies have reported that stroke subtypes are associated with home discharge; therefore, including them may improve the accuracy of the analysis. Third, the severity of stoke was not examined. In the acute phase, stroke severity, such as the National Institutes of Health Stroke Scale, may be useful for home discharge. However, our study includes MMSE, SIAS, and FIM, making for similar consideration. Finally, the study was conducted in a single facility, which limits the generalizability of our results. Despite these limitations, the findings of this study are valuable as they suggest that the MMSE is a useful predictor of home discharge in subacute stroke patients. The MMSE is widely and commonly used for subacute stroke patients; hence, the MMSE can be a useful tool for such patients. In the future, it will be necessary to investigate whether interventions for cognitive dysfunction and higher brain dysfunction can improve return-to-home rates.
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