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Cognitive function is associated with home discharge in subacute stroke patients: a retrospective cohort study



To investigate the cognitive function and its relation to the home discharge of patients following subacute stroke.


This retrospective cohort study included 1,229 convalescent patients experiencing their first subacute stroke. We determined discharge destination and demographic and clinical information. We recorded the following measurement scores: Mini-Mental State Examination (MMSE) score, Stroke Impairment Assessment Set score, grip strength, and Functional Independence Measure (FIM). We performed a multivariable logistic regression analysis with the forced-entry method to identify factors related to home discharge.


Of the 1,229 participants (mean age: 68.7 ± 13.5 years), 501 (40.8%), 735 (59.8%), and 1,011 (82.3%) were female, had cerebral infarction, and were home discharged, respectively. Multivariable logistic regression analysis revealed that age (odds ratio [OR], 0.93; 95% confidence interval [CI], 0.91 – 0.96; P < 0.001), duration from stroke onset to admission (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 at admission (OR, 1.05; 95% CI, 1.00 – 1.09; P = 0.035), FIM motor score at admission (OR, 1.04; 95% CI, 1.01 – 1.06; P = 0.001), and FIM cognitive score at admission (OR, 1.08; 95% CI, 1.04 – 1.13; P < 0.001) were significantly associated with home discharge.


MMSE at admission is significantly associated with home discharge in patients with subacute stroke.

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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 [6,7,8,9,10,11,12,13,14,15,16,17,18]. 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.


Study design and participants

This retrospective cohort study was reported in adherence to the STROBE statement. This study collected 2,151 consecutive patients with subacute stroke admitted to Tokyo Bay Rehabilitation Hospital between April 1, 2015 and March 31, 2020. The inclusion criterion was a first occurrence of subacute stroke. The exclusion criteria were age < 20 years (n = 5), entered the facility before stroke onset (n = 19), subarachnoid hemorrhage (n = 250), infratentorial lesions (n = 204), bilateral cerebral lesions (n = 40), disturbance of consciousness (n = 55), aphasia (n = 215), hospital transfer (n = 86), death (n = 4), and loss of data (n = 44). After applying the selection criteria, 1,229 patients were finally included in this study (Fig. 1). This study was conducted in accordance with the Declaration of Helsinki [22] and was reviewed and approved by the Ethics Committee of Tokyo Bay Rehabilitation Hospital (approval number #246). The opt-out method was applied to obtain informed consent in this study.

Fig. 1
figure 1

Flowchart of the patient selection process


Tokyo Bay Rehabilitation Hospital is a subacute rehabilitation ward with 160 beds. All patients in this study completed a rehabilitation program for 120 – 180 min a day during the hospitalization, including ≥ 60 min of physical therapy, ≥ 60 min of occupational therapy, and/or ≥ 40 min of speech-language-hearing therapy.

Data collection

The following demographic characteristics and measures were collected from the patients’ medical records by the first author: age, sex, body mass index (BMI), stroke type (cerebral infarction or cerebral hemorrhage), brain side affected, duration from stroke onset to admission, hospital duration, living situation (alone or not), and discharge destination (home or facility). Hospital duration and discharge destination were collected at discharge, while the other data were collected at admission.

Mini-mental state examination

Mini-Mental State Examination (MMSE) is a questionnaire for evaluating cognitive function [23]. It consists of 11 items as follows (maximum score of each item): orientation to time (5), orientation to place (5), registration of three words (3), attention and calculation (serial sevens or spelling) (5), recall (3), naming (2), repetition (1), comprehension of verbal (3), comprehension of written (1), writing (1), and construction (1). The maximum score is 30 points, with a higher score representing greater cognitive function; the cut-off value is 23 points [23]. Occupational therapists administered the MMSE and determined the score at admission.

Stroke impairment assessment set

Motor function was assessed using the stroke impairment assessment set-motor function (SIAS-m) [24, 25], which consists of two tests for the upper extremity (knee-mouth and finger function tests) and three tests for the lower extremity (hip flexion, knee extension, and foot pat tests). Each test was rated on a 6-grade ordinal scale rating from 0 (no movement at all) to 5 points (normal). The total scores of the upper and lower extremities were 0 – 10 and 0 – 15 points, respectively [26]. Physical and occupational therapists administered the SIAS-m and determined the score at admission.

Grip strength

Upper-body muscle strength was measured using grip strength, which has established reliability in patients with stroke [27]. Grip strength was measured for each participant’s non-paralyzed upper limb using a handgrip dynamometer (TKK 5401; Takei Scientific Instruments, Tokyo, Japan). Representative grip strength was calculated as the average of two trials [28]. Each measurement was assessed by trained physical or occupational therapists.

Functional independence measure

FIM version 3.0 is an observational evaluation tool for functional disability [29]. The FIM consists of 13 motor subscales (FIM motor) and five cognitive subscales (FIM cognitive). The FIM motor consists of the following four categories: self-care (eating, grooming, bathing, dressing-upper body, dressing-lower body, and toileting), sphincter control (bladder management and bowel management), transfers (bed/chair/wheelchair, toilet, and tub/shower), and locomotion (walk/wheelchair and stairs). The FIM cognitive consists of two categories: communication (comprehension and expression) and social cognition (social interaction, problem-solving, and memory). Each item has a 7-grade scale ranging from 1 (total assistance or not testable) to 7 points (complete independence). The total score is 18 – 126 points, 13 – 91 points, and 5 – 35 points for the total FIM, FIM motor, and FIM cognitive, respectively, with a higher score representing greater functional independence. Nurses evaluated FIM scores at admission and discharge.

Statistical analyses

The normality of continuous variables was assessed using the normal Q-Q plot. Patient characteristics were summarized for the home and facility discharge groups and compared between groups using the chi-squared test, unpaired t-test, or Mann–Whitney U test, as appropriate. Finally, a multivariable logistic regression analysis with the forced-entry method was performed to assess the factors affecting home discharge after controlling simultaneously for potential confounders. The dependent variable was the discharge destination (home or facility), and the independent variables were all factors at admission. The multicollinearity of the independent variables was assessed using the variance inflation factor. Multicollinearity is present when the variance inflation factor is higher than 5 to 10 [30]. Furthermore, we tested the validity of our model using a Hosmer–Lemeshow test and the percentage of correct classifications. All statistical analyses were performed using IBM SPSS Statistics (version 27.0; IBM, Tokyo, Japan). Statistical significance was set at P ≤ 0.05.


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

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


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 [7,8,9, 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.


The current study 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 in subacute stroke patients who were undergoing rehabilitation in convalescent wards. Among them, the significant association between MMSE score and home discharge is a novel finding. Therefore, screening for cognitive function on admission in patients with subacute stroke is important.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.



Body mass index


Confidence interval


Functional Independence Measure


Mini-Mental State Examination


Odds ratio


Stroke Impairment Assessment Set-motor function


  1. Feigin VL. Stroke in developing countries: can the epidemic be stopped and outcomes improved? Lancet Neurol. 2007;6:94–7.

    Article  Google Scholar 

  2. Kumar S, Selim MH, Caplan LR. Medical complications after stroke. Lancet Neurol. 2010;9:105–18.

    Article  Google Scholar 

  3. Langhorne P, Taylor G, Murray G, Dennis M, Anderson C, Bautz-Holter E, et al. Early supported discharge services for stroke patients: a meta-analysis of individual patients’ data. Lancet. 2005;365:501–6.

    Article  Google Scholar 

  4. Miyai I, Sonoda S, Nagai S, Takayama Y, Inoue Y, Kakehi A, et al. Results of new policies for inpatient rehabilitation coverage in Japan. Neurorehabil Neural Repair. 2011;25:540–7.

    Article  Google Scholar 

  5. Itaya T, Murakami Y, Ota A, Nomura E, Fukushima T, Nishigaki M. Assessment model to identify patients with stroke with a high possibility of discharge to home: a retrospective cohort study. Stroke. 2017;48:2812–8.

    Article  Google Scholar 

  6. Thorpe ER, Garrett KB, Smith AM, Reneker JC, Phillips RS. Outcome measure scores predict discharge destination in patients with acute and subacute stroke: a systematic review and series of meta-analyses. J Neurol Phys Ther. 2018;42:2–11.

    Article  Google Scholar 

  7. Meijer R, van Limbeek J, Kriek B, Ihnenfeldt D, Vermeulen M, de Haan R. 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.

    Article  Google Scholar 

  8. Maeshima S, Okamoto S, Okazaki H, Mizuno S, Asano N, Maeda H, et al. Potential factors, including activities of daily living, influencing home discharge for patients with putaminal haemorrhage. BMC Neurol. 2016;16:16.

    Article  Google Scholar 

  9. Mutai H, Furukawa T, Araki K, Misawa K, Hanihara T. Factors associated with functional recovery and home discharge in stroke patients admitted to a convalescent rehabilitation ward. Geriatr Gerontol Int. 2012;12:215–22.

    Article  Google Scholar 

  10. Kose E, Hirai T, Seki T, Hayashi H. The association of increased drugs use with activities of daily living and discharge outcome among elderly stroke patients. Int J Clin Pharm. 2018;40:599–607.

    Article  Google Scholar 

  11. Kim MS, Joo MC, Sohn MK, Lee J, Kim DY, Lee SG, et al. Development and validation of a prediction model for home discharge in patients with moderate stroke: the Korean stroke cohort for functioning and rehabilitation study. Top Stroke Rehabil. 2020;27:453–61.

    Article  Google Scholar 

  12. Tsujimoto K, Mizuno K, Kobayashi Y, Tanuma A, Liu M. Right as well as left unilateral spatial neglect influences rehabilitation outcomes and its recovery is important for determining discharge destination in subacute stroke patients. Eur J Phys Rehabil Med. 2020;56:5–13.

    Article  Google Scholar 

  13. Hirano Y, Maeshima S, Osawa A, Nishio D, Takeda K, Baba M, et al. The effect of voluntary training with family participation on early home discharge in patients with severe stroke at a convalescent rehabilitation ward. Eur Neurol. 2012;68:221–8.

    Article  Google Scholar 

  14. Yoshimura Y, Wakabayashi H, Momosaki R, Nagano F, Shimazu S, Shiraishi A. Shorter interval between onset and admission to convalescent rehabilitation wards is associated with improved outcomes in ischemic stroke patients. Tohoku J Exp Med. 2020;252:15–22.

    Article  Google Scholar 

  15. Li TKT, Ng BHP, Chan DYL, Chung RS, Yu KK. Factors predicting clinically significant functional gain and discharge to home in stroke in-patients after rehabilitation - a retrospective cohort study. Hong Kong J Occup Ther. 2020;33:63–72.

    Article  Google Scholar 

  16. Yoshimura Y, Wakabayashi H, Bise T, Nagano F, Shimazu S, Shiraishi A, et al. Sarcopenia is associated with worse recovery of physical function and dysphagia and a lower rate of home discharge in Japanese hospitalized adults undergoing convalescent rehabilitation. Nutrition. 2019;61:111–8.

    Article  Google Scholar 

  17. Yang G, Gu R, Sato S, Zheng F, Sano M, Yashima C, et al. The Ability for Basic Movement Scale II can predict functional outcome and discharge destination in stroke patients. J Stroke Cerebrovasc Dis. 2020;29:104484.

    Article  Google Scholar 

  18. Tooth L, McKenna K, Goh K, Varghese P. Length of stay, discharge destination, and functional improvement: utility of the Australian National Subacute and nonacute Patient Casemix Classification. Stroke. 2005;36:1519–25.

    Article  Google Scholar 

  19. Sexton E, McLoughlin A, Williams DJ, Merriman NA, Donnelly N, Rohde D, et al. Systematic review and meta-analysis of the prevalence of cognitive impairment no dementia in the first year post-stroke. Eur Stroke J. 2019;4:160–71.

    Article  Google Scholar 

  20. Narasimhalu K, Ang S, De Silva DA, Wong MC, Chang HM, Chia KS, et al. The prognostic effects of poststroke cognitive impairment no dementia and domain-specific cognitive impairments in nondisabled ischemic stroke patients. Stroke. 2011;42:883–8.

    Article  Google Scholar 

  21. Claesson L, Lindén T, Skoog I, Blomstrand C. Cognitive impairment after stroke - impact on activities of daily living and costs of care for elderly people. The Göteborg 70+ Stroke Study. Cerebrovasc Dis. 2005;19:102–9.

    Article  Google Scholar 

  22. World Medical Association. WMA Declaration of Helsinki: ethical principles for medical research involving human subjects. Adopted by the 18th WMA General Assembly, Helsinki, Finland. Fortaleza, Brazil: October. p. 2013; June 1964, and last amended by the 64th WMA General Assembly. Accessed 24 Feb 2014.

  23. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189–98.

    Article  CAS  Google Scholar 

  24. Chino N, Sonoda S, Domen K, Saitoh E, Kimura A. Stroke Impairment Assessment Set (SIAS): A new evaluation instrument for stroke patients. Jpn J Rehabil Med. 1994;31:119–25.

    Article  Google Scholar 

  25. Tsuji T, Liu M, Sonoda S, Domen K, Chino N. The stroke impairment assessment set: its internal consistency and predictive validity. Arch Phys Med Rehabil. 2000;81:863–8.

    Article  CAS  Google Scholar 

  26. Miyai I, Suzuki T, Kang J, Volpe BT. Improved functional outcome in patients with hemorrhagic stroke in putamen and thalamus compared with those with stroke restricted to the putamen or thalamus. Stroke. 2000;31:1365–9.

    Article  CAS  Google Scholar 

  27. Bertrand AM, Fournier K, Wick Brasey MG, Kaiser ML, Frischknecht R, Diserens K. Reliability of maximal grip strength measurements and grip strength recovery following a stroke. J Hand Ther. 2015;28:356–62 quiz 363.

    Article  Google Scholar 

  28. Yamada M, Kimura Y, Ishiyama D, Nishio N, Abe Y, Kakehi T, et al. Differential Characteristics of Skeletal Muscle in Community-Dwelling Older Adults. J Am Med Dir Assoc. 2017;18:807.e9-807.e16.

    Article  Google Scholar 

  29. Data Management Service of the Uniform Data System for Medical Rehabilitation, the Center for Functional Assessment Research. Guide for use of the uniform data set for medical rehabilitation including the Functional Independence Measure (FIM). version 3.0. Buffalo, NY: State University of New York Press; 1990.

  30. Kim JH. Multicollinearity and misleading statistical results. Korean J Anesthesiol. 2019;72:558–69.

    Article  Google Scholar 

  31. Al-Aloucy MJ, Cotteret R, Thomas P, Volteau M, Benmaou I, Dalla BG. Unawareness of memory impairment and behavioral abnormalities in patients with Alzheimer’s disease: relation to professional health care burden. J Nutr Health Aging. 2011;15:356–60.

    Article  CAS  Google Scholar 

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We are profoundly grateful to the medical staff of the Department of Rehabilitation Medicine, Tokyo Bay Rehabilitation Hospital, in Chiba, Japan, for their administrative support.


This work was supported by AMED under Grant Number JP19he2302006.

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MK reviewed the manuscript and pointed out the problems of the study. RI participated in data analysis and reviewed the drafts. MT, HK, and KK reviewed the manuscript. TT presented the direction to the conclusion and finally checked the manuscript. All authors read and approved the final manuscript.

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Correspondence to Michiyuki Kawakami.

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This study conformed to the Declaration of Helsinki guidelines and was reviewed and approved by the Ethics Committee of Tokyo Bay Rehabilitation Hospital (#246). The opt-out method was applied to obtain informed consent in this study. The opt-out method ensures that our research protocol, including the use of patient data, is described on our hospital website, and that research subjects and others have the opportunity to refuse that their data be used ( The opt-out method for informed consent was approved by the Ethics Committee of Tokyo Bay Rehabilitation Hospital (approval number #246).

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Ito, D., Kawakami, M., Ishii, R. et al. Cognitive function is associated with home discharge in subacute stroke patients: a retrospective cohort study. BMC Neurol 22, 219 (2022).

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