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OUTLINE

 1.  Abstract
 2.  KEYWORDS
 3.  List of abbreviations
 4.  Introduction
 5.  Methods
 6.  Results
 7.  Discussion
 8.  Conclusions
 9.  Supplier
 10. Acknowledgment
 11. Appendix. Supplementary materials
 12. References

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FIGURES (3)

 1. 
 2. 
 3. 




TABLES (6)

 1. Table 1
 2. Table 2
 3. Table 3
 4. Table 4
 5. Table 5
 6. Table 6




EXTRAS (1)

 1. Document




ARCHIVES OF REHABILITATION RESEARCH AND CLINICAL TRANSLATION

Available online 2 August 2024, 100362
In Press, Corrected ProofWhat’s this?

ORIGINAL RESEARCH
BASELINE NUTRITIONAL STATUS AND REHABILITATION PROGRESS IN INDIVIDUALS REQUIRING
INPATIENT REHABILITATION: A RETROSPECTIVE COHORT STUDY

Author links open overlay panelHideki Arai MD, PhD a, Syuya Okada PT a,
Tatsuyuki Fukuoka SLP, PhD b, Masafumi Nozoe PT, PhD c, Kuniyasu Kamiya PT, PhD
d, Satoru Matsumoto MD b
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ABSTRACT


OBJECTIVE

To evaluate the relationships between baseline nutritional status, medical
events (MEs), and rehabilitation outcomes in individuals undergoing inpatient
rehabilitation (IR).


DESIGN

A retrospective single center cohort study.


SETTING

An IR ward.


PARTICIPANTS

This study included 409 patients (mean age, 80 years; men, 170 [42%]) undergoing
IR for hospital-associated deconditioning, neurologic disorders, or
musculoskeletal diseases. Participants were grouped according to the Controlling
Nutritional Status score at admission: normal nutrition (NN): 0 to 1, mild
malnutrition (MM): 2 to 4, and moderate/severe malnutrition (M/SM): 5 to 12.


INTERVENTIONS

None.


MAIN OUTCOME MEASURES

The primary outcomes included MEs leading to death or acute illness requiring
transfer to other hospitals for specialized treatments. The secondary outcomes
were the rehabilitation efficiency scores (changes in Functional Independence
Measure [FIM] score divided by length of stay) for motor function (FIM-M) and
cognitive function (FIM-C).


RESULTS

Among the 409 participants, 300 (73%) were malnourished at admission. The
adjusted hazard ratios (95% confidence interval) for MEs in the MM and M/SM
groups relative to the NN group were 1.48 (0.67-3.27) and 0.98 (0.34-2.81),
respectively. No significant differences were observed among the 3 groups in
FIM-M efficiency scores (mean ± SD, NN: 0.49±0.51 vs MM: 0.41±0.57 vs M/SM:
0.44±1.06, P=.7) or FIM-C efficiency scores (0.04±0.06 vs 0.04±0.06 vs 0.08±0.4,
P=0.1). Analysis of covariance showed no significant association between MM or
M/SM group and FIM-M efficiency score (beta coefficient = -0.038, P=.6; beta
coefficient = 0.15, P=.1, respectively) or FIM-C efficiency score (beta
coefficient = 0.004, P=.8; beta coefficient = 0.047, P=.08, respectively).


CONCLUSION

No significant associations were observed between the baseline nutritional
status and MEs, FIM-M efficiency score, or FIM-C efficiency score in individuals
undergoing IR.




KEYWORDS

Activities of daily living
Controlling Nutritional Status
Functional Independence Measure
Inpatient rehabilitation
Malnutrition
Medical events
Rehabilitation


LIST OF ABBREVIATIONS

ADL
activities of daily living
ANCOVA
analysis of covariance
CONUT
Controlling Nutritional Status
FIM
Functional Independence Measure
FIM-C
FIM for cognitive function
FIM-M
FIM for motor function
GNRI, geriatriic nutritional risk index, IQR
interquartile range
IR
inpatient rehabilitation
ME
medical event
MM
mild malnutrition
M/SM
moderate/severe malnutrition
NN
normal nutrition
NS
nutritional status
PNI
prognostic nutritional index


INTRODUCTION

Recently, increasing attention has been paid to nutritional assessment.1, 2
Nutritional status (NS) affects outcomes in cases of acute heart failure,
coronary artery disease, or stroke.1, 2 Simple methods for nutritional
assessment, such as the prognostic nutritional index (PNI) and geriatric
nutritional risk index (GNRI), are often used in clinical practice.1,3 A
meta-analysis reported that patients with heart failure and low PNI
(undernourishment) had high risks of death and adverse cardiac outcomes.1 A
retrospective study with 12 years of observation found that patients with acute
heart failure and poor NS, as determined by the GNRI, had a high rate of
bleeding events.4 Nutritional assessment is important not only in the acute care
setting but also in rehabilitation medicine.3,5,6 A retrospective study with
approximately 2 months of observation revealed that severe malnutrition, as
measured by the PNI, was associated with poor functional outcomes in patients
with ischemic stroke admitted for inpatient rehabilitation (IR).6

In addition to PNI and GNRI, Controlling Nutritional Status (CONUT) is often
used in clinical practice as a simple method of nutritional assessment.3,7 The
CONUT score was developed to screen for malnutrition risk in hospitalized
patients, and its validity has been reported.2,8 This score is calculated as the
sum of serum albumin level, total cholesterol level, and total peripheral
lymphocyte count, which are indicators of protein metabolism, immune
dysfunction, and energy deficiency, respectively. The risk of malnutrition is
classified in order of declining CONUT score as normal nutrition (NN), mild
malnutrition (MM), moderate malnutrition, and severe malnutrition.2 The CONUT
score can predict outcomes in patients with stroke, coronary artery disease,
acute heart failure, and cancer.2,3,7 In particular, a meta-analysis reported
that stroke patients with malnutrition, as determined by the CONUT score, had
higher risks of death and poor functional outcomes.2

Few reports have investigated the relationship between NS and rehabilitation
progress.3,5,6 These studies have included only patients with stroke.3,5
Therefore, we investigated whether baseline NS, as assessed by the CONUT score,
was associated with rehabilitation progress in patients requiring IR, including
those with stroke.


METHODS


PARTICIPANTS

This retrospective cohort study was conducted using the medical records of
patients admitted to the rehabilitation unit of Toyonaka Heisei Hospital in
Japan between April 2019 and March 2021 as a result of hospital-associated
deconditioning, neurologic disorders, or musculoskeletal diseases. We did not
plan for the retrospective study period to be a certain length so that an
approximate number of patients could be used in this analysis. We used the
medical records to calculate the participants’ CONUT scores at admission. We
scored the participants’ serum albumin levels, total cholesterol concentrations,
and total peripheral lymphocyte counts on admission, as shown in table 1.
Participants were grouped according to their CONUT score by calculating the sum
of the scores.2,5 CONUT score was originally categorized as NN (0-1), MM (2-4),
moderate malnutrition (5-8), and severe malnutrition (9-12) (table 1).3,5
However, studies using the CONUT score have categorized scores of 0 to 1, 2 to
4, and 5 to 12 as NN, MM, and moderate/severe malnutrition (M/SM) groups,
respectively.3,5 We therefore classified participants into the 3 groups.
Patients whose CONUT score could not be calculated because of lack of data on
serum albumin level, total cholesterol level, or total peripheral lymphocyte
count were excluded. All participants were followed until they were discharged
from the hospital for one of the following reasons: completion of the IR
program, death, or transfer to other hospitals to receive specialized treatments
for acute illness. Furthermore, those whose rehabilitation was withdrawn because
of death or transfer to other hospitals were excluded from the analyses of
secondary outcomes.

Table 1. Assessment of the degree of undernutrition based on the Controlling
Nutritional Status score

ParameterUndernutrition DegreeEmpty CellNormalMildModerateSevereSerum albumin,
g/dL≥3.53-3.492.5-2.9<2.5Score0246Total cholesterol,
mg/dL>180140-180100-139<100Score0123Total peripheral lymphocyte,
/mm3>16001200-1599800-1199<800Score0123Total score0-12-45-89-12


INPATIENT REHABILITATION

IR was tailored according to the activities of daily living (ADL) of each
individual, in line with the recommendations of the public medical insurance
system in Japan.9 Rehabilitation was administered daily in 20-minutes units.9
Individuals with hospital-associated deconditioning were treated with 6 units of
physical, occupational, and speech therapy daily for up to 90 days.9 Individuals
with neurologic disorders were treated with 9 units of physical, occupational,
and speech therapy daily for up to 150 days (180 days for patients with higher
brain dysfunction).9 Individuals with musculoskeletal diseases were treated with
6 units of physical and occupational therapy daily for up to 90 days.9 These
units were individualized according to the disability and included muscle
strengthening, gait training, training for higher brain dysfunction, and
swallowing training.9 No adjustment of exercise load was made based on the CONUT
score.


DATA COLLECTION

We reviewed the hospital records to collect the following baseline data: age,
sex (men), body mass index, hand-grip strength, revised Hasegawa's Dementia
Scale score, disease category (hospital-associated deconditioning, neurologic
disorders with or without higher brain dysfunction, and musculoskeletal
diseases), comorbidities (chronic heart failure and chronic respiratory
disease), laboratory data (blood hemoglobin, creatinine, blood urea nitrogen,
serum total protein, and serum albumin levels), tube feeding, urinary catheter
use, mobility aids, and Functional Independence Measure (FIM) for performance of
ADL evaluated within 48 hours of admission and within 48 hours before
discharge.9 Dementia was diagnosed as a score of ≤20 points on the revised
Hasegawa's Dementia Scale.9 The level of dependence in ADL was recorded using
FIM for motor domain (FIM-M; 13 items) and FIM for cognitive domain (FIM-C; 5
items).9 Individual items were scored from 1 (fully dependent) to 7 (fully
independent), with higher scores indicating less need for care.9 The FIM-M and
FIM-C scores were calculated as sums of individual item scores.9


OUTCOMES

The primary outcomes in this study were medical events (MEs) such as all-cause
death and acute illness requiring transfer to other hospitals for specialized
treatments.10 From the perspective of cessation of rehabilitation, death and
acute illness were considered together as a single ME, even though they differed
in severity.

Among individuals who completed the IR program with no MEs, secondary outcomes
were FIM-M and FIM-C efficiency scores ([FIM score at discharge - FIM score at
admission]/length of stay).10


STATISTICAL ANALYSIS

We compared clinical features and outcomes among the groups. Categorical and
continuous data were reported as frequencies (%) and mean (SD) or median
(interquartile range [IQR]), as appropriate, respectively, and compared using
the chi-squared test and analysis of variance or the Kruskal-Wallis test,
respectively. The numbers of missing values were presented, but not imputed to
ensure accurate reporting of the clinical status.

Primary outcomes were analyzed based on the cumulative incidence using the
Kaplan-Meier method. The log-rank test was used to evaluate group differences.
The outcomes were compared among the groups using Cox proportional hazard
models, with results presented as hazard ratios and 95% confidence intervals.
Variables considered to be clinically relevant were included in the
multivariable Cox proportional hazard models to adjust for potential
confounders, including age, sex (men), hand-grip strength, chronic heart
failure, and chronic respiratory disease. Furthermore, we presented the details
of MEs.

Analysis of covariance (ANCOVA) was conducted to evaluate relationships between
baseline NS (NN, MM, or M/SM) and secondary outcomes (FIM-M and FIM-C efficiency
scores). We did not assess the normality assumption of the ANCOVA. Variables
deemed to be clinically relevant were included in the ANCOVA to adjust for
potential confounders. Covariates for the FIM-M efficiency score were age, sex
(men), hand-grip strength, revised Hasegawa's Dementia Scale,
hospital-associated deconditioning, neurologic disease with or without higher
brain dysfunction, musculoskeletal disorders, chronic heart failure, and chronic
respiratory disease. For the FIM-C efficiency score, covariates were age, sex
(men), the revised Hasegawa's Dementia Scale, hospital-associated
deconditioning, neurologic disorders with or without higher brain dysfunction,
and musculoskeletal diseases. To evaluate multicollinearity, we used the
variance inflation factor (values of 1-10 indicated no multicollinearity).

Data were analyzed using JMP 16 software.a Two-tailed P values <.05 indicated
statistical significance.


ETHICS

The study protocol was approval by the Research Ethics Committee of the Toyonaka
Heisei Hospital (No. 202402). The study was performed in accordance with the
Declaration of Helsinki and the Ethical Guidelines for Medical and Health
Research involving Human Subjects in Japan.11 Considering that the data analyzed
in this study were drawn from medical records, an opt-out method on a notice
board in the hospital was used to obtain patient consent. The study adhered to
the STROBE guidelines. All necessary has been reported.


RESULTS


PATIENT CHARACTERISTICS

Among the 428 patients included, 19 were excluded because of the inability to
determine CONUT scores. Of the 409 individuals who fulfilled the eligibility
criteria, 109 had NN (27%), 231 had MM (56%), 62 had moderate malnutrition
(15%), and 7 had severe malnutrition (2%). Therefore, a total of 73% of patients
had malnutrition (fig 1). The mean age was 80±10 years, and 170 participants
(42%) were men (table 2). The median (IQR) follow-up duration was 73 (47-89)
days.

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Fig 1. Study flowchart.

Table 2. Baseline patient characteristics

VariableAll Patients (n=409)NN Group (n=109)MM Group (n=231)M/SM Group (n=69)P
ValueAge, y, mean (SD)80 (10)77 (13)80 (8)82 (12).0006Men, n (%)170 (42)44
(40)91 (39)35 (51).2Body mass index, kg/m2, mean (SD)*20.4 (4)21.2 (4.6)20.5
(3.8)18.8 (3.3).0004Hand-grip strength, kg, median (IQR)* Men17 (11–22)20
(15–26)17 (10–21)14 (10–20).02 Women10 (7–15)12 (9–16)10 (7–15)6 (4–9)<.0001The
revised Hasegawa's Dementia Scale, median (IQR)15 (7–24)16 (8–27)15 (8–24)14
(6–23).3Disease category, n (%) Hospital-associated deconditioning120 (29)28
(26)65 (28)27 (39).4 Neurologic disorders without higher brain dysfunction28
(7)6 (6)17 (7)5 (7) Neurologic disorders with higher brain dysfunction142 (35)40
(37)78 (34)24 (35) Musculoskeletal diseases119 (29)35 (32)71 (31)13
(19)Comorbidities, n (%) Chronic heart failure155 (38)36 (33)78 (34)41
(59).0003 Chronic respiratory disease27 (7)6 (6)14 (6)7 (10).4Baseline
laboratory data Hemoglobin, g/dL, mean (SD)11.5 (1.7)12 (1.7)11.7 (1.6)10.4
(1.6)<.0001 Creatinine, mg/dL, median (IQR)0.7 (0.6–1.0)0.8 (0.6–1.0)0.7
(0.6–0.9)0.7 (0.6–1.0).3 Blood urea nitrogen, mg/dL, median (IQR)16.8
(12.9–22.2)16.4 (13.3–22.3)17.2 (13–22.2)16.8 (12.1–22.9).96 Total protein,
g/dL, mean (SD)6.5 (0.6)6.8 (0.5)6.5 (0.6)6.0 (0.7)<.0001 Albumin, g/dL, mean
(SD)3.7 (0.5)4.0 (0.3)3.8 (0.4)3.1 (0.4)<.0001Tube feeding, n (%)82 (20)21
(19)45 (19)16 (20).8Urinary catheter use, n (%)39 (10)6 (6)25 (11)8
(13).3Mobility aid, n (%) Wheelchair377 (92)93 (85)216 (94)68 (99).02 Walker10
(2)7 (6)3 (1)0 (0) Cane6 (1)2 (2)4 (2)0 (0) None†16 (4)7 (6)8 (3)1 (1)FIM,
median (IQR) FIM-M27 (15–45)35 (16–56)26 (15–44)19 (13–33).0001 FIM-C18
(11–26)18 (11–30)19 (11–25)16 (8–24).2

⁎

Variables with missing data: body mass index (1 in MM group); hand-grip strength
(15 in NN group, 25 in MM group, and 10 in M/SM group); urinary catheter use (9
in NN group, 11 in MM group, and 6 in M/SM group).

†

Walking independently.

Individuals with malnutrition were older than those without malnutrition (mean
[SD] age, NN: 77 [13] years; MM: 80 [8] years; M/SM: 82 [12] years; P=.0006).
The mean (SD) body mass index was reduced in individuals with malnutrition than
in those without malnutrition (NN: 21.2 [4.6] kg/m2; MM: 20.5 [3.8] kg/m2; M/SM:
18.8 [3.3] kg/m2; P=.0004). The median (IQR) hand-grip strength was reduced in
individuals with malnutrition than in those without malnutrition in men (NN: 20
[15-26] kg; MM: 17 [10-21] kg; M/SM: 14 [10-20] kg; P=.02) and women (NN: 12
[9-16] kg; MM: 10 [7-15] kg; M/SM: 6 [4-9] kg; P<.0001). No differences were
observed in the median (IQR) revised Hasegawa's Dementia Scale among the 3
groups (NN: 16 [8-27]; MM: 15 [8-24]; M/SM: 14 [6-23]; P=.3). A lower median
(IQR) FIM-M score was observed in individuals with malnutrition than in those
without malnutrition (NN: 35 [16-56]; MM: 26 [15-44]; M/SM: 19 [13-33];
P=.0001). No differences were found among the groups in terms of the median
(IQR) FIM-C score at admission (NN: 18 [11-30]; MM: 19 [11-25]; M/SM: 16 [8-24];
P=.2; table 2).


OUTCOMES

The cumulative incidences of MEs at 150 days in the NN, MM, and M/SM groups were
22.1%, 21.3%, and 19.9%, respectively (fig 2). The adjusted hazard ratios (95%
confidence intervals) of the MM and M/SM groups relative to the NN group for MEs
were 1.48 (0.67-3.27) and 0.98 (0.34-2.81), respectively (table 3). The most
frequent MEs were aspiration pneumonia (n=7) and gastrointestinal bleeding
(n=7), followed by congestive heart failure (n=5) and cerebral hemorrhage (n=5),
most of which were observed in the malnutrition group (supplemental table S1).

 1. Download: Download high-res image (470KB)
 2. Download: Download full-size image

Fig 2. Cumulative incidence of medical events including death and acute illness
requiring transfer to other hospitals for specialized treatments.

Table 3. Cox proportional hazard model for medical events such as all-cause
death and acute illness requiring transfer to other hospitals for specialized
treatments

VariableCrude HR95% CIAdjusted HR95% CINN group (reference)----MM
group1.250.65-2.41.480.67-3.27M/SM group1.060.44-2.510.980.34-2.81



NOTE. Adjusters for adverse events: age, men, hand-grip strength, chronic heart
failure, and chronic respiratory disease.

Abbreviations: CI, confidence interval; HR, hazard ratio.



Among the 353 individuals who completed the IR program with no MEs, poor NS
resulted in a longer length of stay and lower FIM scores (NN: 57 [39-85] days;
MM: 74 [51-90] days; M/SM: 78 [60-93]; P=.02). The mean (SD) changes in FIM-M
and FIM-C scores were not different among the groups (change in FIM-M, NN: 22
[16]; MM: 23 [16]; M/SM: 18 [18], P=.09; change in FIM-C, NN: 3 [5]; MM: 3 [4];
M/SM: 2 [3], P=.03). No differences were found among the groups in terms of mean
(SD) FIM-M or FIM-C efficiency scores (FIM-M efficiency score, NN: 0.49 [0.51];
MM: 0.41 [0.57]; M/SM: 0.44 [1.06], P=.7; FIM-C efficiency score, NN: 0.04
[0.06]; MM: 0.04 [0.06]; M/SM: 0.08 [0.4], P=.1; table 4, fig 3). The ANCOVA did
not reveal any multicollinearity among variables or significant association of
malnutrition status with the FIM-M or FIM-C efficiency score in each group
(FIM-M efficiency score, MM: beta coefficient =-0.038, P=.6; M/SM: beta
coefficient =0.15, P=.1; FIM-C efficiency score, MM: beta coefficient =0.004,
P=.8; M/SM: beta coefficient =0.047, P=.08; Table 5, Table 6).

Table 4. Outcomes and outcome components in the 3 groups completed the inpatient
rehabilitation program

VariableAll Patients (n=353)NN Group (n=97)MM Group (n=196)M/SM Group (n=60)P
ValueLength of stay, d, median (IQR)73 (47-89)57 (39-85)74 (51-90)78
(60-93).02FIM-M at admission, median (IQR)29 (16-47)38 (20-57)29 (16-48)20
(13-33)<.0001FIM-C at admission, median (IQR)19 (11-27)20 (12-31)19 (11-27)17
(10-24).07FIM-M at discharge, median (IQR)62 (28-80)71 (38-86)63 (31-79)40
(18-64)<.0001FIM-C at discharge, median (IQR)23 (15-30)25 (15-33)23 (16-30)18
(10-27).004Change in FIM-M, mean (SD)22 (17)22 (16)23 (16)18 (18).09Change in
FIM-C, mean (SD)3 (4)3 (5)3 (4)2 (3).03FIM-M efficiency score, mean (SD)0.44
(0.67)0.49 (0.51)0.41 (0.57)0.44 (1.06).7FIM-C efficiency score, mean (SD)0.05
(0.16)0.04 (0.06)0.04 (0.06)0.08 (0.4).1

 1. Download: Download high-res image (338KB)
 2. Download: Download full-size image

Fig 3. Distributions of functional independent measure scores and functional
independent measure efficiency scores in patients who completed the inpatient
rehabilitation program (n=353).

Table 5. Analysis of covariance for the Functional Independence Measure for
motor function efficiency score in patients completed the inpatient
rehabilitation program

VariableLeast Square Mean (SE)Beta coefficient95% CIP ValueVIFNN group
(reference)0.49 (0.087)----MM group0.452 (0.077)-0.038-0.18 to 0.11.61.42M/SM
group0.64 (0.109)0.15-0.05 to 0.35.11.52



NOTE. Covariates for FIM-M efficiency score: age, men, hand-grip strength, the
revised Hasegawa's Dementia Scale, hospital-associated deconditioning,
neurologic disorders without higher brain dysfunction, neurologic disorders with
higher brain dysfunction, musculoskeletal diseases, chronic heart failure, and
chronic respiratory disease.

Abbreviations: CI, confidence interval; VIF, variance inflation factor.



Table 6. Analysis of covariance for the Functional Independence Measure for
cognitive function efficiency score in patients completed the inpatient
rehabilitation program

VariableLeast Square Mean (SE)Beta coefficient95% CIP ValueVIFNN group
(reference)0.035 (0.023)----MM group0.039 (0.02)0.004-0.034 to 0.043.81.38M/SM
group0.081 (0.027)0.047-0.006 to 0.099.081.42



NOTE. Covariates for FIM-C efficiency score: age, men, the revised Hasegawa's
Dementia Scale, hospital-associated deconditioning, neurologic disorders without
higher brain dysfunction, neurologic disorders with higher brain dysfunction,
and musculoskeletal diseases.

Abbreviations: CI, confidence interval; VIF, variance inflation factor.




DISCUSSION

We found that malnutrition was prevalent in individuals admitted to a IR ward.
However, baseline NS was not significantly related to MEs or rehabilitation
outcomes such as FIM-M and FIM-C efficiency scores.

This study found no significant association between malnutrition at admission
and MEs. Our findings align with those of a previous study.6 However, the study
could not explain the lack of a significant association of NS with MEs.6 On the
other hand, contrary to the findings of this study, previous studies have shown
a significant association between malnutrition and MEs.1,2,4,12 The discrepancy
between the present and previous findings was due to differences in study
design, that is, differences in nutritional screening tools, populations, and
follow-up periods.6 In particular, in the short follow-up period of almost 2
months, differences in NS may not have appeared as MEs. Moreover, our findings
that MEs such as pneumonia and gastrointestinal bleeding were more common in the
malnutrition group are in line with previous findings.2,4 Therefore, patients
with malnutrition in IR wards need to be strictly managed to prevent the
development of acute illnesses. Factors other than NS may have contributed to
the lack of MEs among the 353 people who completed the IR program without MEs;
however, this was not investigated in this study.

This study revealed no significant relationships of malnutrition at admission
with FIM-M efficiency, which is in disagreement with previous research showing
significant associations between malnutrition and physical function.5,6 Although
muscle weakness, fatigue, and impaired neurologic recovery due to malnutrition
have been reported as possible mechanisms of the link between malnutrition and
impaired physical function, the effects of malnutrition on impaired physical
function remain poorly understood.5,6,13 One possible reason for the discrepancy
between our findings and those of previous studies is that factors other than
malnutrition may have affected the FIM-M efficiency. Reduced lower extremity
range of motion and muscle strength and gait speed have been reported as factors
related to ADL.8,14,15 In this study, although such factors may have made
patients with malnutrition less disadvantaged than those with NN, this was not
scrutinized.

Our finding that malnutrition at admission was not significantly related to
FIM-C efficiency was line with the findings of previous studies.2,5 This may be
because of the short follow-up duration.5 A previous report showed that 2 to 13
years of follow-up is required to determine the association between low albumin
level, one of the components of CONUT, and decreased cognitive function.5
Therefore, the median follow-up duration of 73 days in this study may have been
inadequate to confirm the association between malnutrition at admission and
FIM-C efficiency.


STUDY LIMITATIONS

This study had certain limitations. First, MEs were defined as death or acute
illness requiring transfer to other hospitals for specialized treatments, which
was decided by the attending physician, making the categorization less robust.10
Second, in-hospital changes in CONUT score were not assessed, which may be
related to the level of nutrition and antihyperlipidemic medications
administered during hospitalization. These changes may affect improvement in
ADL.16 Third, we could not evaluate the rehabilitation protocols, which could
have influenced rehabilitation outcomes.9 Finally, this was a single-center
study, our results may not be applicable to other settings. Additional
multicenter studies are needed to determine the effects of baseline NS on
rehabilitation progress.


CONCLUSIONS

Almost 70% of individuals admitted to a IR ward had malnutrition; however, no
significant relationship was observed between baseline NS and MEs, FIM-M, or
FIM-C efficiency score. This study suggests that patients with malnutrition at
admission may benefit from IR as much as those without malnutrition at
admission, without an increased risk of MEs.


SUPPLIER



 * a.
   
   JMP 16 software; SAS Institute Inc, 100 SAS Campus Dr, Cary, NC 27513.




ACKNOWLEDGMENT

We thank the staff in the rehabilitation ward at Toyonaka Heisei Hospital for
providing excellent rehabilitation services with kindness.


APPENDIX. SUPPLEMENTARY MATERIALS

Download: Download Word document (27KB)

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REFERENCES

 1.  1
     MY Chen, JX Wen, MT Lu, et al.
     Association between prognostic nutritional index and prognosis in patients
     with heart failure: a meta-analysis
     Front Cardiovasc Med, 9 (2022), Article 918566
     View in ScopusGoogle Scholar
 2.  2
     O Di Vincenzo, L D'Elia, G Ballarin, F Pasanisi, L Scalfi
     Controlling Nutritional Status (CONUT) score and the risk of mortality or
     impaired physical function in stroke patients: a systematic review and
     meta-analysis
     Nutr Metab Cardiovasc Dis, 33 (2023), pp. 1501-1510
     View PDFView articleView in ScopusGoogle Scholar
 3.  3
     T Kamimoto, K Shindo, T Shimomura, et al.
     Relationship between initial nutritional status and functional independence
     measures at discharge in subacute stroke
     J Stroke Cerebrovasc Dis, 31 (2022), Article 106754
     View PDFView articleView in ScopusGoogle Scholar
 4.  4
     Y Sato, A Yoshihisa, Y Nozaki, et al.
     Geriatric nutritional risk index predicts bleeding event in patients with
     heart failure
     ESC Heart Fail, 11 (2024), pp. 702-708
     CrossrefView in ScopusGoogle Scholar
 5.  5
     Y Kokura, K Kimoto, Y Okada, S. Kawakita
     The Controlling Nutritional Status score as a functional prognostic marker
     in patients with acute stroke: a multicenter retrospective cohort study
     Nutrition, 79-80 (2020), Article 110889
     View PDFView articleView in ScopusGoogle Scholar
 6.  6
     D Scrutinio, B Lanzillo, P Guida, A Passantino, S Spaccavento, P. Battista
     Association between malnutrition and outcomes in patients with severe
     ischemic stroke undergoing rehabilitation
     Arch Phys Med Rehabil, 101 (2020), pp. 852-860
     View PDFView articleView in ScopusGoogle Scholar
 7.  7
     Y Nanri, M Shibuya, K Fukushima, K Uchiyama, N Takahira, M. Takaso
     Preoperative malnutrition is a risk factor for delayed recovery of
     mobilization after total hip arthroplasty
     PM R, 13 (2021), pp. 1331-1339
     CrossrefView in ScopusGoogle Scholar
 8.  8
     J Ignacio de Ulíbarri, A González-Madroño, NG de Villar, et al.
     CONUT: a tool for controlling nutritional status. First validation in a
     hospital population
     Nutr Hosp, 20 (2005), pp. 38-45
     View in ScopusGoogle Scholar
 9.  9
     H Arai, N Ikegawa, M Nozoe, K Kamiya, S. Matsumoto
     Association between skeletal muscle mass index and convalescent
     rehabilitation ward achievement index in older patients
     Prog Rehabil Med, 7 (2022), Article 20220003
     Google Scholar
 10. 10
     H Arai, S Okada, T Fukuoka, et al.
     Association of baseline skeletal muscle mass index with adverse events and
     rehabilitation outcomes in patients admitted for rehabilitation
     Arch Rehabil Res Clin Transl, 6 (2023), Article 100314
     Google Scholar
 11. 11
     Ministry of Health, Labour and Welfare. Ethical guidelines for medical and
     health research involving human subjects.
     https://www.mhlw.go.jp/file/06-Seisakujouhou-10600000-Daijinkanboukouseikagakuka/0000080278.pdf.
     Accessed February 9, 2024.
     Google Scholar
 12. 12
     BR Wilkinson, Q An, N Glass, A Miller, J Davison, MC. Willey
     Malnutrition is common and increases the risk of adverse medical events in
     older adults with femoral fragility fractures
     Iowa Orthop J, 42 (2022), pp. 69-74
     View in ScopusGoogle Scholar
 13. 13
     S Nishioka, H Wakabayashi, E Nishioka, T Yoshida, N Mori, R. Watanabe
     Nutritional improvement correlates with recovery of activities of daily
     living among malnourished elderly stroke patients in the convalescent
     stage: a cross-sectional study
     J Acad Nutr Diet, 116 (2016), pp. 837-843
     View PDFView articleView in ScopusGoogle Scholar
 14. 14
     H Jung, M. Yamasaki
     Association of lower extremity range of motion and muscle strength with
     physical performance of community-dwelling older women
     J Physiol Anthropol, 35 (2016), p. 30
     Google Scholar
 15. 15
     DM Mijnarends, YC Luiking, RJG Halfens, et al.
     Musle, health and costs: a glance at their relationship
     J Nutr Health Aging, 22 (2018), pp. 766-773
     View PDFView articleCrossrefView in ScopusGoogle Scholar
 16. 16
     S Nishioka, H Wakabayashi, R. Momosaki
     Nutritional status changes and activities of daily living after hip
     fracture in convalescent rehabilitation units: a retrospective
     observational cohort study from the Japan rehabilitation nutrition database
     J Acad Nutr Diet, 118 (2018), pp. 1270-1276
     View PDFView articleView in ScopusGoogle Scholar


CITED BY (0)



Study data are available from the corresponding author upon reasonable request.

Disclosures: The authors have no conflicts of interest to declare.

© 2024 The Authors. Published by Elsevier Inc. on behalf of American Congress of
Rehabilitation Medicine.


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