Sarcopenia as a Robust Predictor of Readmission within 6 Months among Individuals Experiencing Acute Stroke

Takafumi Abe; Yoshihiro Yoshimura; Yoichi Sato; Fumihiko Nagano; Ayaka Matsumoto

doi:10.4235/agmr.24.0017

Ann Geriatr Med Res > Volume 28(3); 2024 > Article

Abe, Yoshimura, Sato, Nagano, and Matsumoto: Sarcopenia as a Robust Predictor of Readmission within 6 Months among Individuals Experiencing Acute Stroke

Original Article

Annals of Geriatric Medicine and Research 2024;28(3):307-314.

Published online: April 11, 2024

DOI: https://doi.org/10.4235/agmr.24.0017

Sarcopenia as a Robust Predictor of Readmission within 6 Months among Individuals Experiencing Acute Stroke

Takafumi Abe¹, Yoshihiro Yoshimura²

, Yoichi Sato¹, Fumihiko Nagano², Ayaka Matsumoto²

¹Department of Rehabilitation, Uonuma Kikan Hospital, Minami Uonuma-city, Niigata, Japan

²Center for Sarcopenia and Malnutrition Research, Kumamoto Rehabilitation Hospital, Kumamoto, Japan

Corresponding Author Yoshihiro Yoshimura, MD, PhD Center for Sarcopenia and Malnutrition Research, Kumamoto Rehabilitation Hospital, 760 Magate, Kikuyo Town, Kikuchi County, Kumamoto 869-1106, Japan
E-mail: hanley.belfus@gmail.com

Received January 22, 2024 Revised February 29, 2024 Accepted April 4, 2024

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Sarcopenia negatively affects the short-term prognosis of hospitalized older adults. However, no evidence currently supports a direct relationship between sarcopenia and readmission among individuals who have experienced an acute stroke. Therefore, we investigated whether sarcopenia is associated with readmission after discharge.

Methods

This retrospective cohort study included patients who had experienced acute stroke. Sarcopenia was defined as the coexistence of low skeletal muscle mass index (SMI) and grip strength. We applied the log-rank test and Cox proportional hazards regression analysis to analyze whether sarcopenia, low SMI, and low grip strength were associated with readmission within 6 months.

Results

Among 228 included patients (mean age, 72.8 years; 146 males), the prevalence of sarcopenia was 24.6% (n=56; male 17.8%; female 36.6%). Cox proportional hazards regression analysis using the propensity score as a covariate revealed that sarcopenia (hazard ratio [HR]=7.21; 95% confidence interval [CI] 1.45–35.8; p=0.016) and low skeletal muscle mass (HR=7.40; 95% CI 1.14–48.1; p=0.036), but not low grip strength (HR=1.42; 95% CI 0.281–7.21; p=0.670), were significantly associated with readmission for stroke within 6 months.

Conclusions

Sarcopenia was negatively associated with readmission within 6 months of stroke onset in patients in Japan who had experienced an acute stroke. These findings suggest that the identification of sarcopenia may facilitate prognostic prediction from the acute stage and intervention(s) to prevent rehospitalization.

Key words: Stroke, Sarcopenia, Skeletal muscle, Patient readmission, Prognosis

INTRODUCTION

Sarcopenia is prevalent and associated with poor prognosis in patients with stroke.^1-⁵⁾ Sarcopenia is characterized by the coexistence of low muscle mass and poor muscle strength or physical function⁶⁾ and has been investigated in patients who have experienced stroke. The prevalence rates of sarcopenia in patients who have experienced stroke are 15.8%–18% before onset, 28.2%–30.8% during acute hospitalization, and 50%–51.6% during convalescent hospitalization,^1,^3,^5,^7,⁸⁾ showing increasing prevalence with each stage of stroke. In the acute phase of stroke, low muscle mass and sarcopenia are associated with poor functional prognosis, poor walking function, and limitations in activities of daily living (ADL).^3,^5,⁹⁾ During the convalescent phase, sarcopenia is associated with limitations in ADL, discharge to home, and independence in urination and defecation.^4,¹⁰⁾

Individuals who experience stroke are at risk of readmission after discharge, especially community-dwelling and hospitalized older adults with sarcopenia, sepsis, heart disease, respiratory diseases, cancer, diabetes, and kidney failure.^11-¹³⁾ Similarly, a history of stroke, atrial fibrillation, hypertension, diabetes, hyperlipidemia, obesity, and lifestyle factors increase the risk of stroke in these populations.^14,¹⁵⁾ Readmissions of patients who have experienced stroke are often caused by recurrent stroke, infection, cardiac disease, or falls.^16-¹⁸⁾ The reported readmission rates of these patients are 24% within 180 days¹⁹⁾ and 24%–39.1% within 1 year.^20,²¹⁾ The risk factors associated with readmission include older age; sex; history of stroke, cardiovascular disease, or diabetes mellitus; length of acute hospitalization; and complications during acute stays.¹⁷⁾ Readmissions significantly contribute to the cost of inpatient care and are indicators of quality of care.^16,²²⁾ Sarcopenia and low skeletal muscle mass also increase the risk of falls²³⁾ and stroke²⁴⁾ among community-dwelling adults. Furthermore, sarcopenia influences readmission rates in hospitalized older patients,¹²⁾ with probability rates of 32% at 6 months¹³⁾ and 71% at 3 years.²⁵⁾ Therefore, sarcopenia in patients with stroke may be associated with readmission.

However, limited evidence supports the relationship between sarcopenia and readmission among individuals who experience acute stroke. Clarifying this relationship may facilitate the early assessment of sarcopenia and its prevention and treatment. Accordingly, we aimed to determine the association of sarcopenia with readmission in patients who experienced acute stroke.

MATERIALS AND METHODS

Participants

This single-center, retrospective cohort study was conducted at the authors’ 454-bed acute-care hospital in Niigata, Japan, between August 2020 and March 2022. All patients admitted within 48 hours of stroke onset during the study period were enrolled. Patients diagnosed with subarachnoid hemorrhage were excluded because they require different treatment and management approaches from those for other patients with stroke. The inclusion criterion was evidence of stroke supported by computed tomography or magnetic resonance imaging findings. Individuals with metal implants, those who died in hospital or after discharge, or those with missing data were excluded from the study.

Definition of Sarcopenia

Sarcopenia was defined as the co-existence of low muscle mass (skeletal muscle mass index [SMI]: male <7.0 kg/m², female <5.7 kg/m²) and muscle strength (low grip strength: male <28 kg, female <18 kg).^1,⁶⁾ Body composition was measured using a portable, non-invasive, multifrequency bioimpedance device (InBody S10; InBody, Tokyo, Japan). This device can be conveniently used on patients who cannot remain in a standing or sitting position because of hemiplegia or those who are bedridden. Measurements were performed after the patients had rested for 15 minutes in the supine position and were avoided within 3 hours of eating. The electrodes were placed on the thumb, third finger, and ankle on both sides. SMI was calculated as the appendicular skeletal muscle mass divided by height squared (kg/m²). Handgrip strength was defined as the highest of two measures using a Smedley hand dynamometer (TKK 5401; Takei Scientific Instruments Co. Ltd., Tokyo, Japan) on the patient’s non-paralyzed side while in a supine position.^5,^7,²⁶⁾ Sarcopenia was assessed within 5 days of admission.

Data Collection

The data were collected retrospectively. Basic data, including age, sex, body mass index (BMI), and clinical details at the time of stroke onset were collected within 48 hours of admission. Stroke severity was assessed according to the National Institutes of Health Stroke Scale score, pre-stroke physical function using the pre-stroke modified Rankin Scale score, laboratory data (albumin and hemoglobin levels), stroke type, paralysis, infarct location, comorbidities, nutritional status using the Geriatric Nutritional Risk Index (GNRI), average daily energy intake, Functional Independence Measure (FIM) score, and outcomes at discharge. The GNRI was calculated using the following equation²⁷⁾:

GNRI = (1.489 × albumin [g/dL]) + (41.7 × [weight/ideal weight]).

The ideal body weight was defined as the weight of the patient at a BMI of 22.0 kg/m². Average daily energy intake was determined as previously described.²⁸⁾ Dietary records were reviewed to quantify the mean daily nutritional intake during the first week after admission to the acute-care hospital. Experienced nurses measured patient oral intake using visual estimation. The energy content of enteral and parenteral nutrition was collected from medical records.

Outcome

The endpoint of this study was readmission within 6 months of stroke onset. A self-administered questionnaire was sent to patients 6 months after stroke onset. Information regarding first readmission after discharge, date of readmission, and reasons for readmission were collected. From the questionnaire results, data regarding readmissions due to stroke at the authors’ hospital or other hospitals and all readmissions, including those for other diseases, were collected.

Ethical Approval

This retrospective cohort study was approved by the Ethics Committee of Uonuma Kikan Hospital (Approval No. 02-024) and conducted in accordance with the principles of the Declaration of Helsinki. Owing to the retrospective nature of the study and use of anonymized data, the requirement for informed written consent was waived. Instead, the patients were offered an opt-out option with the opportunity to withdraw from the study at any time. This study complied the ethical guidelines for authorship and publishing in the Annals of Geriatric Medicine and Research.²⁹⁾

Statistical Analysis

Continuous data are expressed as mean±standard deviation or medians (interquartile range). Categorical data are expressed as numbers (%) of participants. We compared the sarcopenia and non-sarcopenia groups using the chi-square test, unpaired t-test, and Mann–Whitney U test. Using the log-rank test, we evaluated the effects of sarcopenia, low skeletal muscle mass, and low grip strength on readmission within 6 months and reported the results using Kaplan–Meier survival curves. We applied Cox proportional hazards regression analysis to analyze whether sarcopenia, low SMI, and low grip strength were associated with readmission within 6 months, after adjusting for confounders. In this study, because the number of patients was low relative to the number of confounders, we used propensity scores to control for confounding factors. The propensity score, as a single summary of all covariates included in the propensity score model, can be included as a covariate in the treatment regression model.³⁰⁾ First, we performed logistic regression analysis with sarcopenia or low SMI and grip strength as the objective variables and each covariate as the explanatory variable, and the propensity score was calculated. Next, we performed Cox proportional hazards regression analysis with propensity score, sarcopenia or low SMI, and grip strength as explanatory variables and readmission within 6 months as the objective variable. The adjusted covariates were age; sex; BMI; premorbid mRS score; NIHSS score; stroke type; GNRI; hemoglobin level; atrial fibrillation; history of stroke, diabetes, dyslipidemia, and hypertension; FIM score at admission; and average daily energy intake.

All analyses were performed using EZR in R Commander, version 1.37 (Saitama Medical Center, Jichi Medical University, Saitama, Japan).³¹⁾ Differences with p<0.05 were considered statistically significant.

RESULTS

A flow diagram illustrating patient inclusion and exclusion criteria is shown in Fig. 1. We initially considered data from 435 individuals who experienced a stroke and were hospitalized during the study period. Of these, we excluded 114 patients for metal implants in the body (n=11), death in the hospital or after discharge (n=18), and missing data (n=85), resulting in 321 patients. The response rate to the questionnaire was 71% (n=228); thus, data from 228 patients were included in the study (Fig. 1).

The patient characteristics are summarized in Table 1. Sarcopenia was identified in 24.6% (n=56) of patients (male 17.8%; female 36.6%). The patients in the sarcopenia group were significantly older; predominantly female; and had lower BMI, GMRI, FOIS, and FIM total scores on admission than those in the non-sarcopenia group. The overall readmission rate was 16.1% (n=9) in the sarcopenia group and 6.4% (n=11) in the non-sarcopenia group (p=0.052), whereas the readmission rates due to stroke were 8.9% (n=5) and 2.3% (n=4), respectively (p=0.042) (Table 2). The reasons for readmission other than stroke were gastrointestinal disease (n=5), fall (n=1), and other unknown causes (n=5).

Kaplan–Meier curves illustrating the effects of sarcopenia, low skeletal muscle mass, and low grip strength on the duration of readmission within 6 months are presented in Fig. 2. For stroke readmission within 6 months, we observed significant differences in patients with sarcopenia (p=0.026) and low skeletal muscle mass (p=0.009), but not in those with low grip strength (p=0.397). For all readmissions within 6 months, we observed significant differences for patients with sarcopenia (p=0.023) and low skeletal muscle mass (p=0.006) but not for those with low grip strength (p=0.260).

The results of the Cox proportional hazards regression analysis, with propensity score as a covariate, are summarized in Table 3. Sarcopenia (hazard ratio [HR]=7.21; 95% confidence interval [CI] 1.45–35.8; p=0.016) and low skeletal muscle mass (HR=7.40; 95% CI 1.14–48.1; p=0.036) were significantly associated with readmission for stroke within 6 months, whereas low grip strength was not (HR=1.42; 95% CI 0.281–7.21; p=0.670). Low skeletal muscle mass (HR=3.88; 95% CI 1.17–12.8; p=0.026) was significantly associated with all readmissions within 6 months, whereas sarcopenia (HR=3.26; 95% CI 0.96–11.0; p=0.058) and low grip strength (HR=1.14; 95% CI 0.372–3.49; p=0.815) were not.

DISCUSSION

In this study, we aimed to determine whether sarcopenia at admission was associated with readmission within 6 months among individuals who had experienced an acute stroke. Our results yielded two important findings: first, sarcopenia and low muscle mass at admission were negatively associated with readmission within 6 months; second, 16.1% of patients with stroke and sarcopenia were readmitted for any reason within 6 months.

Sarcopenia and low muscle mass at admission were negatively associated with stroke readmission within 6 months of admission. The potential mechanism underlying this association lies in the decrease in muscle mass and strength, which are crucial for physical function and recovery after stroke. Sarcopenia and low muscle mass can lead to increased risks of cerebral infarction²⁴⁾ and hypertension,^32,³³⁾ thus increasing the risk of stroke readmission. Although associations between sarcopenia and readmission in patients with cardiovascular disease³⁴⁾ and older adults³⁵⁾ have been reported, to the best of our knowledge, the present study is the first to examine the association between sarcopenia and readmission in patients who had experienced acute stroke.

Sarcopenia was not significantly associated with all readmission rates within 6 months of admission in the present study. Sarcopenia can lead to decreased overall physical performance,^3,⁵⁾ hindering rehabilitation and increasing the risk of readmission. In addition, a decline in physical function in patients with stroke is associated with a risk for readmission within 1 year.^20,^36,³⁷⁾ In this study, sarcopenia may not have been significantly associated with all readmissions because of the short observation period (6 months).

We also observed no significant association between low grip strength and readmission rates. Grip strength was assessed at the early stage of disease onset, wherein the patients were in a supine position for rest during treatment, and they showed varying degrees of cognitive decline and impaired consciousness due to stroke. Our findings suggest the need to evaluate sarcopenia and muscle mass in addition to the current prognostic evaluations.

In the present study, 16% of patients with stroke and sarcopenia were readmitted for any reason within 6 months. The reported readmission rates of patients with stroke are 24% within 180 days,¹⁹⁾ 24%–39.1% within 1 year,^20,²¹⁾ and 24.7% within 1 year among patients with stroke admitted to convalescent rehabilitation wards,³⁸⁾ with most hospitalizations occurring within 100 days of discharge.³⁶⁾ The factors contributing to the lower readmission rate in the present study compared with those in previous studies include regional differences in the indications for thrombolysis or surgery as well as the length of hospitalization and rehabilitation.^39,⁴⁰⁾ Additionally, the present investigation included patients in the acute phase of stroke; thus, the patient background differed from those of studies that targeted patients in the convalescent phase.

Evaluations of low skeletal muscle mass and sarcopenia in patients with acute stroke and providing interventions for prevention and improvement are important. Falls, as a factor in readmission, are associated with decreased balance and walking speed, suggesting the importance of improving physical function.⁴¹⁾ Regarding rehabilitation load, while previous research has shown that more hours of exercise can reduce the risk of readmission,⁴²⁾ opinions regarding these findings are mixed in Japan.³⁸⁾ During the short-term acute phase, sufficient exercise and nutrition cannot be guaranteed owing to the bed rest associated with treatment; therefore, improving sarcopenia is difficult. However, future studies should identify patients at a high risk of readmission due to sarcopenia at an early stage and investigate interventions to prevent readmission from the acute phase. Measurement of lower leg circumference should be considered an alternative assessment for sarcopenia, enabling a more comprehensive and precise evaluation of the patient's condition.^5,⁴³⁾ As pre-sarcopenia and low skeletal muscle mass can lead to decreased physical function^3,⁹⁾ and an increased risk of readmission,²⁴⁾ preventing sarcopenia before stroke onset is important. Furthermore, behaviors such as the intake of high-quality protein⁴⁴⁾ and resistance training such as standing exercises⁴⁵⁾ may help prevent and improve sarcopenia after the acute phase of stroke. Maintaining skeletal muscle mass and preventing sarcopenia are critical during the acute phase, whereas interventions to improve these conditions are important after the recovery phase.

The present study has several limitations. The first was its single-center design (i.e., one hospital in Japan); moreover, 41% of the participants were excluded, which may have limited the generalizability of the results. Second, owing to the retrospective study design, we were unable to fully adjust for the impact of confounding factors such as genetic, social, and clinical factors on readmission. To enhance the robustness of our findings, future prospective studies with rigorous methodologies, high quality, adequate sample sizes, and strong statistical analyses are needed. Third, because this study was based on data from a questionnaire survey, it may have included cases in which it was difficult to respond to the questionnaire owing to a lack of support. Fourth, although we used propensity scores to assess the impact of sarcopenia on readmission, the specific effects of other covariates remain unclear. Fifth, this study was relatively short-term as it targeted patients within 6 months of stroke onset.

In conclusion, among patients who experienced acute stroke in Japan, sarcopenia was negatively associated with stroke readmission within 6 months of stroke onset but was not significantly associated with readmission rates. Our findings suggest that the identification of sarcopenia or low muscle mass may facilitate prognostic prediction based on the acute stage and intervention(s) to prevent rehospitalization.

ACKNOWLEDGMENTS

We thank the staff at Uonuma Kikan Hospital who supported this study.

CONFLICT OF INTEREST

The researchers claim no conflicts of interest.

FUNDING

None.

AUTHOR CONTRIBUTIONS

Conceptualization, TA, YY, YS; Data curation, TA; Investigation, TA, YS; Methodology, TA, YY, YS, FN, AM; Project administration, TA; Supervision, TA; Writing-original draft, TA, YS; Writing-review & editing, TA, YY, YS, FN, AM.

Fig. 1.

Flow diagram illustrating participant inclusion and exclusion.

Fig. 2.

Kaplan–Meier curves demonstrating the association between stroke readmission and sarcopenia (A); all readmissions and sarcopenia (B); stroke readmission and low SMI (C); all readmissions and low SMI (D); stroke readmission and low grip strength (E); and all readmissions and low grip strength using the log-rank test (F). SMI, skeletal muscle mass index.

Table 1.

Patient characteristics

	Total (n=228)	Non-sarcopenia (n=172)	Sarcopenia (n=56)	p-value
Age (y)	72.8±13.3	69.2±12.3	83.9±9.9	<0.001^a)
Sex, male	146 (64.0)	120 (69.8)	26 (46.4)	0.002^b)
BMI (kg/m²)	23.2±4.2	24.0±3.9	20.9±4.1	<0.001^a)
Premorbid mRS	0 (0–0)	0 (0–0)	1 (0–2)	<0.001
NIHSS (point)	4 (2–6)	4 (2–6)	5 (3–7)	0.096^c)
Stroke type				0.125^b)
Ischemic	164 (71.9)	119 (69.2)	45 (80.4)
Hemorrhage	64 (28.1)	53 (30.8)	11 (19.6)
Infratentorial lesion	39 (17.1)	26 (15.1)	13 (23.2)	0.219
Comorbidity
Hypertension	154 (67.5)	120 (69.8)	34 (60.7)	0.250^b)
Previous stroke	37 (16.2)	23 (13.4)	14 (25.0)	0.059^b)
Atrial fibrillation	34 (14.9)	24 (14.0)	10 (17.9)	0.518^b)
Dyslipidemia	49 (21.5)	44 (25.6)	5 (8.9)	0.008^b)
Diabetes mellitus	62 (27.2)	48 (27.9)	14 (25.0)	0.732^b)
GNRI	104.6±10.3	106.9±9.2	97.4±10.3	<0.001^c)
Length of hospital stay (day)	20 (13–31)	20 (12–32)	21 (14–28)	0.933^a)
Energy intake (kcal/kg/day)	23.6 (18.3–26.9)	23.9 (18.6–27)	22.1 (17.2–26.6)	0.252^a)
Albumin (g/dL)	4.1 (3.8–4.3)	4.2 (3.9–4.4)	3.9 (3.6–4.1)	<0.001^a)
Hemoglobin (g/dL)	13.8 (12.5–14.8)	13.9 (12.9–14.9)	13.1 (11.3–14.2)	0.001^a)
FIM motor score at admission	35 (14.8–52.3)	37 (15–54)	28 (14–44)	0.046^a)
FIM cognitive score at admission	26.5 (15–34.3)	29 (19–35)	19 (10–28.5)	<0.001^a)
Discharge outcome				<0.001^b)
Home	134 (58.8)	109 (63.4)	25 (44.6)
Convalescent hospital	86 (37.7)	62 (36)	24 (42.9)
Other	8 (3.5)	1 (0.6)	7 (12.5)

Values are presented as mean±standard deviation or number (%) or median (interquartile range).

Sarcopenia defined by low skeletal muscle index (men <7.0 kg/m², women <5.7 kg/m²) and low hand grip strength (men <28 kg, women <18 kg).

BMI, body mass index; mRS, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale; GNRI, Geriatric Nutritional Risk Index; FIM, Functional Independence Measure.

^a) t-test,

^b) chi-squared test,

^c) Mann–Whitney U test.

Table 2.

Comparison of readmission after 6 months between the two groups

	Total (n = 228)	Non-sarcopenia (n = 172)	Sarcopenia (n = 56)	p-value^a)
All readmission	20 (8.8)	11 (6.4)	9 (16.1)	0.052
Stroke	9 (3.9)	4 (2.3)	5 (8.9)	0.042
Digestive diseases	5 (2.2)	3 (1.7)	2 (3.6)	0.599
Fall	1 (0.4)	1 (0.6)	0 (0)	1
Other or unknown	5 (2.2)	3 (1.7)	3 (5.4)	0.599

Values are presented as number (%).

Sarcopenia defined by low skeletal muscle index (men <7.0 kg/m², women <5.7 kg/m²) and low hand grip strength (men <28 kg, women <18 kg).

^a) Chi-squared test.

Table 3.

Cox proportional hazards regression analysis examining the relationship between readmission within 6 months and sarcopenia or low SMI, low grip strength

	Stroke readmission		All admission
	HR (95% CI)	p-value	HR (95% CI)	p-value
Sarcopenia	7.210 (1.450–35.800)	0.016	3.260 (0.960–11.000)	0.058
Propensity score	0.239 (0.017–3.330)	0.286	0.341 (0.045–2.610)	0.300
Subitem
Low SMI	7.400 (1.140–48.100)	0.036	3.880 (1.170–12.800)	0.026
Propensity score	0.719 (0.072–7.140)	0.778	0.513 (0.093–2.830)	0.444
Low hand grip strength	1.420 (0.281–7.210)	0.670	1.140 (0.372–3.490)	0.815
Propensity score	2.280 (0.112–46.700)	0.592	2.120 (0.255–17.500)	0.487

SMI, skeletal muscle mass index; HR, hazard ratio; CI, confidence interval.

Adjusted covariates as propensity scores included age, sex, body mass index, premorbid modified Rankin Scale score, National Institutes of Health Stroke Scale score, stroke type, Geriatric Nutritional Risk Index, hemoglobin level, atrial fibrillation, history of stroke, diabetes, dyslipidemia, hypertension, Functional Independence Measure score at admission, and average daily energy intake.

REFERENCES

1. Yoshimura Y, Wakabayashi H, Bise T, Tanoue M. Prevalence of sarcopenia and its association with activities of daily living and dysphagia in convalescent rehabilitation ward inpatients. Clin Nutr 2018;37(6 Pt A):2022–8.

2. Shiraishi A, Yoshimura Y, Wakabayashi H, Tsuji Y. Prevalence of stroke-related sarcopenia and its association with poor oral status in post-acute stroke patients: Implications for oral sarcopenia. Clin Nutr 2018;37:204–7.

3. Nozoe M, Kanai M, Kubo H, Yamamoto M, Shimada S, Mase K. Prestroke sarcopenia and functional outcomes in elderly patients who have had an acute stroke: a prospective cohort study. Nutrition 2019;66:44–7.

4. Kido Y, Yoshimura Y, Wakabayashi H, Momosaki R, Nagano F, Bise T, et al. Sarcopenia is associated with incontinence and recovery of independence in urination and defecation in post-acute rehabilitation patients. Nutrition 2021;91-92:111397.

5. Abe T, Yoshimura Y, Sato Y, Nagano F, Matsumoto A. Validity of sarcopenia diagnosis defined by calf circumference for muscle mass to predict functional outcome in patients with acute stroke. Arch Gerontol Geriatr 2023;105:104854.

6. Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, et al. Asian Working Group for Sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc 2020;21:300–7.

7. Sato Y, Yoshimura Y, Abe T. Phase angle as an indicator of baseline nutritional status and sarcopenia in acute stroke. J Stroke Cerebrovasc Dis 2022;31:106220.

8. Inoue T, Ueshima J, Kawase F, Kobayashi H, Nagano A, Murotani K, et al. Trajectories of the prevalence of sarcopenia in the pre- and post-stroke periods: a systematic review. Nutrients 2022;15:113.

9. Abe T, Iwata K, Yoshimura Y, Shinoda T, Inagaki Y, Ohya S, et al. Low muscle mass is associated with walking function in patients with acute ischemic stroke. J Stroke Cerebrovasc Dis 2020;29:105259.

10. 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.

11. Wang S, Zhu X. Nationwide hospital admission data statistics and disease-specific 30-day readmission prediction. Health Inf Sci Syst 2022;10:25.

12. Zhao Y, Zhang Y, Hao Q, Ge M, Dong B. Sarcopenia and hospital-related outcomes in the old people: a systematic review and meta-analysis. Aging Clin Exp Res 2019;31:5–14.

13. Gariballa S, Alessa A. Sarcopenia: prevalence and prognostic significance in hospitalized patients. Clin Nutr 2013;32:772–6.

14. Caprio FZ, Sorond FA. Cerebrovascular disease: primary and secondary stroke prevention. Med Clin North Am 2019;103:295–308.

15. Xu J, Zhang X, Jin A, Pan Y, Li Z, Meng X, et al. Trends and risk factors associated with stroke recurrence in China, 2007-2018. JAMA Netw Open 2022;5:e2216341.

16. Zhong W, Geng N, Wang P, Li Z, Cao L. Prevalence, causes and risk factors of hospital readmissions after acute stroke and transient ischemic attack: a systematic review and meta-analysis. Neurol Sci 2016;37:1195–202.

17. Rao A, Barrow E, Vuik S, Darzi A, Aylin P. Systematic review of hospital readmissions in stroke patients. Stroke Res Treat 2016;2016:9325368.

18. Lim JY, Jung SH, Kim WS, Paik NJ. Incidence and risk factors of poststroke falls after discharge from inpatient rehabilitation. PM R 2012;4:945–53.

19. Lin HJ, Chang WL, Tseng MC. Readmission after stroke in a hospital-based registry: risk, etiologies, and risk factors. Neurology 2011;76:438–43.

20. Tay MR. Hospital readmission in stroke survivors one year versus three years after discharge from inpatient rehabilitation: prevalence and associations in an Asian cohort. J Rehabil Med 2021;53:jrm00208.

21. Bjerkreim AT, Naess H, Khanevski AN, Thomassen L, Waje-Andreassen U, Logallo N. One-year versus five-year hospital readmission after ischemic stroke and TIA. BMC Neurol 2019;19:15.

22. Rumball-Smith J, Hider P. The validity of readmission rate as a marker of the quality of hospital care, and a recommendation for its definition. N Z Med J 2009;122:63–70.

23. Landi F, Liperoti R, Russo A, Giovannini S, Tosato M, Capoluongo E, et al. Sarcopenia as a risk factor for falls in elderly individuals: results from the ilSIRENTE study. Clin Nutr 2012;31:652–8.

24. Minn YK, Suk SH. Higher skeletal muscle mass may protect against ischemic stroke in community-dwelling adults without stroke and dementia: the PRESENT project. BMC Geriatr 2017;17:45.

25. Yang M, Hu X, Wang H, Zhang L, Hao Q, Dong B. Sarcopenia predicts readmission and mortality in elderly patients in acute care wards: a prospective study. J Cachexia Sarcopenia Muscle 2017;8:251–8.

26. Abe T, Yoshimura Y, Sato Y, Nagano F, Matsumoto A. Applicability of the diagnostic criteria for sarcopenic obesity defined by ESPEN/EASO criteria in acutely admitted patients with stroke: prevalence and association with outcomes. J Nutr Sci Vitaminol (Tokyo) 2023;69:454–62.

27. Bouillanne O, Morineau G, Dupont C, Coulombel I, Vincent JP, Nicolis I, et al. Geriatric Nutritional Risk Index: a new index for evaluating at-risk elderly medical patients. Am J Clin Nutr 2005;82:777–83.

28. Sato Y, Yoshimura Y, Abe T. Nutrition in the first week after stroke is associated with discharge to home. Nutrients 2021;13:943.

29. Noh JH, Jung HW, Ga H, Lim JY. Ethical guidelines for publishing in the Annals of Geriatric Medicine and Research. Ann Geriatr Med Res 2022;26:1–3.

30. Fairchild AJ, McDaniel HL. Best (but oft-forgotten) practices: mediation analysis. Am J Clin Nutr 2017;105:1259–71.

31. Kanda Y. Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics. Bone Marrow Transplant 2013;48:452–8.

32. Han JM, Lee MY, Lee KB, Kim H, Hyun YY. Low relative skeletal muscle mass predicts incident hypertension in Korean men: a prospective cohort study. J Hypertens 2020;38:2223–9.

33. Kara M, Kara O, Ceran Y, Kaymak B, Kaya TC, Citir BN, et al. SARcopenia assessment in hypertension: the SARAH study. Am J Phys Med Rehabil 2023;102:130–6.

34. Konishi M, Kagiyama N, Kamiya K, Saito H, Saito K, Ogasahara Y, et al. Impact of sarcopenia on prognosis in patients with heart failure with reduced and preserved ejection fraction. Eur J Prev Cardiol 2021;28:1022–9.

35. Perez-Zepeda MU, Sgaravatti A, Dent E. Sarcopenia and post-hospital outcomes in older adults: a longitudinal study. Arch Gerontol Geriatr 2017;69:105–9.

36. Bohannon RW, Lee N. Association of physical functioning with same-hospital readmission after stroke. Am J Phys Med Rehabil 2004;83:434–8.

37. Ottenbacher KJ, Graham JE, Ottenbacher AJ, Lee J, Al Snih S, Karmarkar A, et al. Hospital readmission in persons with stroke following postacute inpatient rehabilitation. J Gerontol A Biol Sci Med Sci 2012;67:875–81.

38. Nagayama H, Tomori K, Ikeda K, Yamauchi K. Medical costs and readmissions after intensive poststroke rehabilitation: Japanese claims data. J Am Med Dir Assoc 2021;22:1762–6.

39. Sacco RL, Gardener H, Wang K, Dong C, Ciliberti-Vargas MA, Gutierrez CM, et al. Racial-ethnic disparities in acute stroke care in the Florida-Puerto Rico collaboration to reduce stroke disparities study. J Am Heart Assoc 2017;6:e004073.

40. Gardener H, Leifheit EC, Lichtman JH, Wang K, Wang Y, Gutierrez CM, et al. Race-Ethnic Disparities in 30-Day Readmission After Stroke Among Medicare Beneficiaries in the Florida Stroke Registry. J Stroke Cerebrovasc Dis 2019;28:104399.

41. Ng MM, Hill KD, Batchelor F, Burton E. Factors predicting falls and mobility outcomes in patients with stroke returning home after rehabilitation who are at risk of falling. Arch Phys Med Rehabil 2017;98:2433–41.

42. Andrews AW, Li D, Freburger JK. Association of rehabilitation intensity for stroke and risk of hospital readmission. Phys Ther 2015;95:1660–7.

43. Rose Berlin Piodena-Aportadera M, Lau S, Chew J, Lim JP, Ismail NH, Ding YY, et al. Calf circumference measurement protocols for sarcopenia screening: differences in agreement, convergent validity and diagnostic performance. Ann Geriatr Med Res 2022;26:215–24.

44. Yoshimura Y, Bise T, Shimazu S, Tanoue M, Tomioka Y, Araki M, et al. Effects of a leucine-enriched amino acid supplement on muscle mass, muscle strength, and physical function in post-stroke patients with sarcopenia: a randomized controlled trial. Nutrition 2019;58:1–6.

45. Yoshimura Y, Wakabayashi H, Nagano F, Bise T, Shimazu S, Shiraishi A, et al. Chair-stand exercise improves sarcopenia in rehabilitation patients after stroke. Nutrients 2022;14:461.