Increased Phase Angle Reflects Improvement in Activities of Daily Living and Muscle Health in Post-stroke Rehabilitation
Article information
Abstract
Background
Phase angle (PhA) reflects cellular integrity and muscle quality. However, evidence is limited regarding whether an increase in PhA is associated with improvements in activities of daily living (ADL) and skeletal muscle mass. This study aimed to investigate the association between change in PhA and prognosis in terms of ADL and skeletal muscle mass in post-stroke patients undergoing rehabilitation.
Methods
This retrospective cohort study was conducted at a convalescent rehabilitation hospital in Japan. Patients with a PhA at admission below the cutoff values (4.76° for male and 4.11° for female) were included. Patients were categorized into a PhA-increase group (>0) and a non-increase group (≤0). Outcomes included the Functional Independence Measure (FIM)-motor score and skeletal muscle mass index (SMI) at discharge. Multivariate regression was used to assess associations.
Results
A total of 253 patients were included (mean age 78.0±10.9 years; 51% females). The median PhA at admission was 3.70° (interquartile range [IQR], 3.20–4.10), and the median change during hospitalization was 0.00° (IQR, -0.20–0.30). Of these, 119 patients had increased PhA and 134 did not. Change in PhA was independently associated with higher FIM-motor scores (β=0.078, p=0.040) and greater SMI (β=0.454, p<0.001) at discharge.
Conclusions
In post-stroke patients, an increase in PhA during hospitalization was associated with better functional and muscular outcomes. PhA may therefore serve as a valuable biomarker for assessing the efficacy of rehabilitation.
INTRODUCTION
Body composition plays a crucial role in assessing sarcopenia and malnutrition. In geriatric health evaluation, body composition—comprising fat mass, muscle mass, and bone mass—is commonly assessed using modalities such as dual-energy X-ray absorptiometry and bioelectrical impedance analysis (BIA).1) Phase angle (PhA), obtained from BIA, has been increasingly recognized as a valid biomarker reflecting cellular integrity, cell membrane function, and muscle quality.2) Aging contributes substantially to shifts in body composition, with muscle mass beginning to decline as early as the third decade of life, and fat mass typically increasing until approximately the seventh decade.3) Sarcopenia affects an estimated 10% of older adults,4) while malnutrition is present in nearly half of this population; these conditions frequently coexist.5) For instance, in individuals undergoing hemodialysis, malnutrition is a known risk factor for the development of sarcopenia.6) These changes in body composition not only compromise activities of daily living (ADL) and quality of life (QOL) but are also associated with increased mortality.7) In post-stroke populations—who are particularly vulnerable to both sarcopenia and malnutrition—such impairments have been linked to poorer rehabilitation outcomes.8,9) Therefore, PhA represents a clinically useful parameter for evaluating nutritional and functional status and may serve as a guide for targeted interventions to improve prognosis in this high-risk group.10)
However, the current body of evidence regarding the relationship between the improvement of PhA and enhancements in ADL and sarcopenia remains limited. Lower PhA values indicate impaired cellular function and malnutrition,11) making it a significant parameter for evaluating physiological status. PhA at hospital admission is an independent prognostic factor for ADL at discharge in acute stroke patients.12) Additionally, PhA is positively associated with improvements in ADL, while negatively associated with sarcopenia, in post-stroke patients undergoing rehabilitation.13) Nonetheless, the interrelationship among changes in PhA, ADL, and skeletal muscle mass remains poorly characterized. Clarifying PhA dynamics may provide valuable insights for predicting clinical outcomes across various populations.
Therefore, the aim of this study is to investigate the association between change in PhA and prognosis in terms of ADL and skeletal muscle mass in post-stroke patients undergoing rehabilitation.
MATERIALS AND METHODS
Participants and Setting
This study is a single-center retrospective cohort study conducted at the Kumamoto Rehabilitation Hospital with 225 beds. It included stroke patients consecutively admitted to the three convalescent rehabilitation wards (135 beds) between 2015 and 2023. Based on prior research, hospitalized patients with low PhA were identified using sarcopenia-specific cutoff values established for individuals in the recovery phase of stroke (4.76° for males and 4.11° for females). These thresholds have been associated with reductions in ADL and skeletal muscle mass.13-15) Only patients with PhA values below these cutoffs were included in the study cohort in order to focus on those at higher risk of functional or nutritional deterioration and to specifically examine the relationship between changes in PhA during hospitalization and rehabilitation outcomes. It should be noted that this inclusion criterion may limit the generalizability of our findings to patients with relatively preserved PhA values. Patients with missing data, those with altered consciousness, those with a pacemaker implantation, and those transferred to other hospitals or wards during rehabilitation were excluded from the analysis.
Data Collection
As patients’ baseline characteristics on hospital admission, the following variables were collected: age, sex, stroke type, stroke history, length of hospital stay, pre-stroke level of independence in ADL based on the modified Rankin Scale (mRS),16) and paralysis side. For admission assessments, the following evaluations were conducted: severity of paralysis using the Brunnstrom Recovery Stage (BRS),17) severity of comorbidities using the Charlson Comorbidity Index (CCI),18) handgrip strength (HG), skeletal muscle mass and PhA assessed by BIA, and both the motor and cognitive scores of the Functional Independence Measure (FIM).19) HG (measured on the upper limb without paralysis) was assessed using a Smedley hand dynamometer (TTM, Tokyo, Japan) with the patient either standing or sitting, depending on their ability, while keeping the arm extended laterally. The highest value among three trials was recorded. FIM at admission was assessed within 24 hours of hospitalization, while FIM at discharge was evaluated by a physical and occupational therapist on the day before or the day of discharge. The skeletal muscle mass index (SMI) was calculated by dividing the measured skeletal muscle mass by the square of the patient's height (m²).
Phase Angle
PhA and SMI were calculated using BIA with a body composition analyzer. BIA was performed by physiotherapists using the InBody S10 (InBody, Tokyo, Japan) with the patients in the supine position. All measurements were conducted at least two hours after the last meal, with patients instructed to rest in bed and restrict fluid intake for one hour prior to measurement. Patients with pacemakers and those unable to maintain a stable posture during measurement were excluded. PhA was calculated using the resistance (R) and reactance (Xc) of the right side of the body according to the following formula:
PhA (°) = arctangent (Xc/R) × (180/π).
In this calculation, resistance and reactance at 50 kHz were used. The difference between PhA at discharge and PhA at admission was calculated and defined as the change in PhA during hospitalization.
Outcomes
The primary outcome was the FIM-motor score at discharge. The FIM consists of two domains: the motor domain (FIM-motor), which includes 13 sub-items, and the cognitive domain (FIM-cognitive), which comprises five sub-items.19) Each item is rated on a 7-point ordinal scale, ranging from 1 (total assistance) to 7 (complete independence), with lower scores indicating greater dependence. The total FIM score ranges from 18 to 126, the FIM-motor score from 13 to 91, and the FIM-cognitive score from 5 to 35. The secondary outcome was the SMI at discharge.
Statistical Analysis
All analyses were conducted using IBM SPSS version 21 (IBM, Armonk, NY, USA). Results were reported as mean±standard deviation (SD) for parametric data, median and 25th–75th percentile (interquartile range [IQR]) for non-parametric data, and number (percentage) for categorical data. To examine changes in PhA from admission to discharge, patients were categorized into two groups: those with an increase in PhA (>0; PhA increase group) and those with no increase or a decrease in PhA (≤0; non-PhA increase group). For univariate analysis, differences in baseline characteristics and outcomes between the two groups were examined using Mann-Whitney U test and the chi-square test, depending on the variables.
Multiple regression analysis was performed to determine whether change in PhA was independently associated with FIM-motor at discharge and SMI at discharge. Covariates used for adjustment as potential confounders of the outcomes included age, sex, stroke type, premorbid mRS, CCI, FIM-motor/cognitive at admission, BRS (lower limb), SMI, HG and PhA at admission. These covariates were identified through discussion among multiple researchers and a review of previous studies.13,16-19) Multicollinearity was assessed using the variance inflation factor (VIF), with VIF <10 indicating no multicollinearity. A p-value of <0.05 was considered statistically significant.
Sample Size Calculation
The sample size calculation was based on data from our previous study,30) which demonstrated that the FIM-motor scores of hospitalized patients followed a normal distribution with a standard deviation of 26.0. Assuming a minimal clinically important difference of 17 in FIM-motor scores between the PhA-increase group and the non-PhA increase group, a minimum sample size of 51 participants per group was estimated to achieve a statistical power of 0.9 with an alpha error of 0.05 to reject the null hypothesis.
Ethics
This study was approved by the Institutional Review Board of Kumamoto Rehabilitation Hospital (Kikuyo, Japan) (Approval No. 2024-2) and conducted in accordance with the Declaration of Helsinki and the Ethical Guidelines for Medical and Health Research Involving Human Subjects. Due to the retrospective study design, written informed consent could not be obtained; however, participants were given the opportunity to withdraw from the study at any time through an opt-out procedure.
RESULTS
Fig. 1 presents the flowchart of participant selection. During the study period, a total of 1,124 stroke patients were newly admitted. Missing data (n=340), altered consciousness (n=48), pacemaker (n=48), and transferred to other hospitals or wards during rehabilitation (n=92), were excluded. After applying the exclusion criteria, 596 patients underwent PhA assessment, and ultimately, 253 participants were included in the final analysis.
Flowchart of participant screening and inclusion criteria.
Table 1 summarizes the baseline characteristics of the enrolled participants. The mean age was 78.01±10.93 years, and 51% of were women. The median PhA for all participants was 3.70° (IQR, 3.20–4.10). In males, the median PhA was 3.60° (IQR, 3.10–3.80) in the non-PhA increase group and 3.40° (IQR, 3.00–3.70) in the PhA increase group (p=0.423). In females, the median PhA was 4.00° (IQR, 3.60–4.20) in the non-PhA increase group and 4.10° (IQR, 3.50–4.40) in the PhA increase group (p=0.078). The median change in PhA for all participants was 0.00° (IQR, -0.20–0.30). In men, the median change in PhA was -0.20° (IQR, -0.40–-0.10) in the non-PhA increase group and 0.40° (IQR, 0.20–0.60) in the PhA increase group (p<0.001). In women, the median change PhA was -0.30° (IRQ, -0.40–-0.10) in the non-PhA increase group and 0.30° (IQR, 0.20–0.50) in the PhA increase group (p<0.001).
Patients’ baseline characteristics on hospital admission
Table 2 presents the results of the between-group comparisons of the FIM and the SMI at discharge. The results showed no significant differences between the groups in terms of FIM-motor at discharge (male p=0.070, female p=0.135) or SMI at discharge (male p=0.159, female p=0.123).
Univariate assessment of clinical outcomes
Table 3 shows the results of multiple regression analyses performed to further investigate the relationship between change in PhA during hospitalization and these outcomes, after adjusting for potential confounding factors. The results indicated that change in PhA during hospitalization was independently and positively associated with the FIM-motor at discharge (β=0.078, B [95% confidence interval]=2.324 [0.104–4.544], p=0.040) and SMI at discharge (β=0.454, B [95% confidence interval]=0.785 [0.694–0.876], p<0.001). No multicollinearity was detected among the variables.
Multiple regression analyses of change in PhA for study outcomes (FIM-motor at discharge and SMI at discharge)
In addition, higher age, male sex, lower premorbid mRS, and lower baseline motor function were independently associated with lower FIM-motor scores at discharge, whereas greater lower limb function, handgrip strength, higher baseline PhA, and increase in PhA were positively related. For SMI at discharge, male sex, higher baseline SMI, baseline PhA, and change in PhA were independently associated with greater skeletal muscle mass.
DISCUSSION
This study investigated the association between changes in PhA during hospitalization and both ADL and skeletal muscle mass at discharge in post-stroke patients undergoing rehabilitation. Two key clinical findings emerged from our analysis. First, the change in PhA during hospitalization was positively associated with ADL at discharge. Second, the change in PhA during hospitalization was also associated with skeletal muscle mass at discharge.
The change in PhA during hospitalization was positively associated with ADL at discharge. Previous studies have demonstrated that an increase in PhA during hospitalization in the acute phase of stroke is associated with improved ADL at discharge.21) However, this study is the first to establish a similar relationship in post-acute stroke patients, thereby extending the understanding of PhA's prognostic value to the recovery phase of stroke care. PhA calculated using BIA, reflects cellular health and is typically higher in individuals with well-structured cell membranes, such as healthy individuals and athletes. Conversely, PhA decreases in individuals with structural damage to the cell membrane and reduced cellular integrity due to aging, cachexia, or malnutrition. PhA has been linked to nutritional status,22) muscle quality,23) functional capacity,24) and sarcopenia,15) suggesting that improvements in PhA may reflect enhancements in these factors. In older adults, higher PhA values are associated with better physical performance.24) Previous studies have reported a positive association between baseline PhA and ADL outcomes at discharge in acute stroke patients.12) Additionally, PhA has been correlate with standing ability and gait performance in patients with osteoarthritis of the hip.25) Given that PhA can improve with rehabilitation and is associated with improved nutritional status,26) PhA elevation could serve as a valuable indicator for assessing functional recovery and nutritional status in stroke patients, as well as evaluating the impact of rehabilitation interventions.
Our findings indicate that, in addition to changes in PhA during hospitalization, several baseline characteristics—including age, sex, and functional status at admission—play an independent role in determining FIM-motor and SMI at discharge. Age and sex may reflect underlying biological differences in muscle mass and recovery potential, consistent with previous studies reporting slower functional recovery in older adults and sex-specific differences in muscle mass preservation.27) Baseline functional status, as indicated by FIM, mRS, and BRS HG, likely reflects the severity of neurological impairment and motor function at admission, which directly affects the capacity for improvement during rehabilitation. PhA at admission, as a marker of cellular integrity and nutritional status, may provide additional prognostic information beyond conventional functional assessments, suggesting that monitoring PhA could help identify patients at higher risk for poor functional recovery and muscle loss. Conversely, a decrease or lack of change in PhA during hospitalization may indicate limited recovery of cellular integrity, persistent malnutrition, or muscle wasting, reflecting inadequate response to rehabilitation or insufficient physiological improvement. Therefore, continuous monitoring of PhA could help identify patients who may require earlier or more intensive intervention. Collectively, these results highlight the multifactorial nature of rehabilitation outcomes and underscore the importance of considering both functional and physiological parameters when predicting patient prognosis.
The change in PhA during hospitalization was also associated with skeletal muscle mass at discharge. Previous research has shown that when PhA remains within the normal range, muscle mass and quality are likely to be maintained, lower PhA values are associated with sarcopenia and muscle dysfunction. This finding suggests that changes in PhA could serve as a critical indicator of skeletal muscle mass maintenance or improvement. This relationship is plausible given that PhA reflects the integrity of the cell membrane and is influenced by the nutritional and metabolic status of the myocyte.28,29) Previous studies have reported that when PhA remains within the normal range, muscle mass and quality are likely to be maintained, whereas lower PhA values are associated with sarcopenia and muscle dysfunction.30) Moreover, improvements in PhA have been linked to increased skeletal muscle mass at discharge in acute stroke patients,21) and our study extends these findings to post-stroke patients. This suggests that monitoring changes in PhA could serve as a useful indicator of muscle mass changes during rehabilitation. In elderly stroke patients, nutritional interventions or rehabilitation programs aimed at improving PhA may contribute to maintaining and enhancing muscle mass. Therefore, continuous evaluation of PhA may play an important role in preventing sarcopenia and assessing the effectiveness of rehabilitation interventions.
Monitoring the change in PhA during rehabilitation in post-stroke patients could be instrumental in optimizing patient outcomes. Our study demonstrated that changes in PhA are positively associated with ADL and skeletal muscle mass at discharge, suggesting that PhA may serve as an objective indicator of rehabilitation effectiveness. Recent studies have reported that PhA at admission is a predictive factor for poor functional outcomes at discharge in acute stroke patients,31) and that a PhA cutoff value of 4.0° is associated with readmission, in-hospital falls, and 9-month mortality in hospitalized patients.32) Identifying patients with low PhA at admission may be useful in developing rehabilitation plans during hospitalization. Resistance training has been identified as a rehabilitation intervention capable of enhance PhA,33) nutritional interventions using high-protein, individualized diets and dietary supplements have been shown to improve PhA in cancer patients.34) These findings suggest that integrating rehabilitation and nutritional therapy—termed "rehabilitation nutrition"—may further promote PhA elevation. The association between PhA changes and improvements in ADL and skeletal muscle mass highlights the potential of PhA as a novel, objective marker for evaluating rehabilitation outcomes in post-stroke patients. Furthermore, routine measurement of PhA derived from BIA could be integrated into post-stroke rehabilitation, as it is noninvasive, quick, and increasingly available in clinical settings. Although changes in PhA during hospitalization cannot be predicted in advance, baseline PhA at admission may still serve as a useful prognostic marker for identifying patients at risk of poor recovery. Several studies have proposed reference thresholds for low PhA associated with adverse outcomes in stroke and frail populations.14,31,32) Therefore, PhA at admission could help stratify patients and guide the intensity and focus of rehabilitation and nutritional interventions from an early stage. Meanwhile, continuous PhA monitoring throughout hospitalization may provide complementary information to evaluate the effectiveness of these interventions. Regular assessment of PhA at admission and during hospitalization may help identify patients at higher risk—such as those with persistently low or declining PhA values—and support the implementation of comprehensive intervention strategies that combine intensive exercise therapy, individualized nutritional support, and targeted pharmacotherapy. Incorporating continuous PhA measurements in this way may facilitate the development of personalized rehabilitation plans and efficient monitoring of treatment outcomes, potentially improving overall prognosis.
This study has several limitations. First, due to the retrospective observational study design, the causal relationship between PhA changes and rehabilitation outcomes cannot be determined. Second, since this study was conducted at a single facility, the generalizability of the results may be limited. Third, since this study used cutoff values for patients in the recovery phase of stroke, the generalizability may be limited. Fourth, potential confounding factors such as pre-stroke physical activity, detailed nutritional status, and the effects of medications on muscle metabolism could not be considered. These confounding factors may influence changes in PhA, but due to the retrospective observational nature of the study, it was difficult to obtain detailed data. To validate the results of this study and enhance its external validity, future high-quality prospective studies that adjust for these potential confounding variables are essential. To validate our findings and enhance their external validity, future high-quality prospective studies are necessary to adjust for these potential confounding variables.
In conclusion, change in PhA during hospitalization in post-stroke patients undergoing rehabilitation was positively associated with improvements in ADL and skeletal muscle mass. The change in PhA may serve as a valuable indicator for assessing the effectiveness of rehabilitation interventions and predicting patient prognosis. Our findings support the clinical utility of PhA and highlight the importance of integrating rehabilitation and nutrition while monitoring PhA changes to optimize patient outcomes.
Notes
CONFLICT OF INTEREST
The researchers claim no conflicts of interest.
FUNDING
None.
AUTHOR CONTRIBUTIONS
Conceptualization, KY, YY, HW; Data curation, KY; Investigation, KY, HW; Methodology, KY, YY; Project administration, YY; Supervision, YY, HW; Formal analysis, KY; Writing – original draft, KY; Writing – review & editing, KY, YY, HW.