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Italian version of the Edmonton Frail Scale (EFS) in elderly and its association with multidimensional and nutritional indexes

R E S E A R C H A R T I C L E Open Access
Performance of Edmonton Frail Scale on
frailty assessment: its association with
multi-dimensional geriatric conditions
assessed with specific screening tools
Simone Perna
, Matthew DArcy Francis
, Chiara Bologna
, Francesca Moncaglieri
, Antonella Riva
Paolo Morazzoni
, Pietro Allegrini
, Antonio Isu
, Beatrice Vigo
, Fabio Guerriero
and Mariangela Rondanelli
Background: The aim of this study was to evaluate the performance of Edmonton Frail Scale (EFS) on frailty assessment
in association with multi-dimensional conditions assessed with specific screening tools and to explore the prevalence of
frailty by gender.
Methods: We enrolled 366 hospitalised patients (women\men: 251\115), mean age 81.5 years. The EFS was given to the
patients to evaluate their frailty. Then we collected data concerning cognitive status through Mini-Mental State Examination
(MMSE), health status (evaluated with the number of diseases), functional independence (Barthel Index and Activities Daily
Living; BI, ADL, IADL), use of drugs (counting of drugs taken every day), Mini Nutritional Assessment (MNA), Geriatric
Depression Scale (GDS), Skeletal Muscle Index of sarcopenia (SMI), osteoporosis and functionality (Handgrip strength).
Results: According with the EFS, the 19.7% of subjects were classified as non frail, 66.4% as apparently vulnerable and
13.9% with severe frailty.
The EFS scores were associated with cognition (MMSE: β=0.980;p< 0.01), functional independence (ADL: β=0.512;
p<0.00);(IADL:β=0.338; p< 0.01); use of medications (β=0.110;p< 0.01); nutrition (MNA: β=0.413; p<0.01);
mood (GDS: β=0.324; p< 0.01); functional performance (Handgrip: β=0.114, p< 0.01) (BI: β=0.037; p<0.01),
but not with number of comorbidities (β=0.108;p= 0.052). In osteoporotic patients versus not-osteoporotic patients
the mean EFS score did not differ between groups (women: p=0.365;men:p= 0.088), whereas in Sarcopenic versus
not-Sarcopenic patients, there was a significant differences in women: p<0.05.
Conclusions: This study suggests that measuring frailty with EFS is helpful and performance tool for stratifying
the state of fragility in a group of institutionalized elderly. As matter of facts the EFS has been shown to be
associated with several geriatric conditions such independence, drugs assumption, mood, mental, functional
and nutritional status.
Keywords: Edmonton frail scale, Frailty, Functional status, Nutrition, Geriatric assessment
* Correspondence:
Department of Public Health, Experimental and Forensic Medicine, Section
of Human Nutrition and Dietetics, University of Pavia, Azienda di Servizi alla
Persona di Pavia, Via Emilia 12, Pavia, Italy
Full list of author information is available at the end of the article
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Perna et al. BMC Geriatrics (2017) 17:2
DOI 10.1186/s12877-016-0382-3
The main characteristics of frailty is a decrease of the
reserves in multiple organ systems. The distinction
between age and frailty appear to be so blurred that it
has been hypothesized that everyone becomes frail when
they grow old [1, 2].
In fact, physicians have often used the term frailty to
characterize the weakest and most vulnerable subset of
older adults. However, fraildoes not mean comorbidity
or disability, so this term cannot be chosen to describe
the elderly [3].
We can individuate three steps in the frailty
process: a pre-frail process, the frailty state and frailty
complications [4]. The pre-frail process is clinically si-
lent and the physiological reserves are enough to
allow the body to respond adequately to acute dis-
eases, injury, stress or generally any insult with the
possibility of complete recovery. The frailty state is
characterized by a slow, incomplete recovery after any
new acute disease, injury or stress, confirming that
the available functional reserves are insufficient to
allow a complete recovery. Complications of the
frailty process are directly related to physiologic
vulnerability resulting from impaired homeostatic
reserves and a reduced capacity of the organism to
withstand stresses. The risk of falls increases and a
functional decline also occurs, leading to disability,
poly-medication, an increased risk of hospitalization,
cross-infection, institutionalization and death [58].
We can conceptualize frailty as a phenotypical state of
weight loss, fatigue, and weakness or alternatively as a
multidimensional state of vulnerability arising from a
complex interplay of biological, cognitive, and social
factors [8].
In order to assess frailty in the elderly, Rolfson et al.
tested a brief and user-friendly screening interview in
both the inpatient and outpatient settings. The Edmon-
ton Frail Scale(EFS) was a valid measure of frailty com-
pared to the clinical impression of geriatric specialists
after their more comprehensive assessment. The EFS
had good construct validity, good reliability and
acceptable internal consistency. The interview com-
prises of 10 areas due to the multi-dimensional pre-
sentations of frailty.
The nine domains examined are: cognition, functional
performance, general health status, functional independ-
ence, social support, pharmacological condition, nutri-
tional aspect, mental condition and continence [9].
The aim of this study was evaluate the performance
of Edmonton Frail Scale on frailty assessment, to
explore the prevalence of frailty by gender, as assessed
by Edmonton Frail Scale, and its association with
multi-dimensional conditions assessed with specific
screening tools.
The study was made in Northern Italy. We evaluated
white elderly men and women in patients admitted to
our physical medicine and rehabilitation division (Santa
Margherita Hospital) [10].
Written informed consent was obtained from all par-
ticipants. In order for the consent to be valid, the patient
must had received the necessary information. She/he
must had the capacity to consent and the consent must
be given voluntarily. Otherwise, when the patient was
not able to consent for himself, the consent was gave by
the caregiver.
Study population
Patients with age over 65 years. Subjects not affected
by acute illness, severe liver, heart or kidney dysfunc-
tion, and with body weight which had been stable for
6 months were included in the study [10]. Data were
gathered from the year the beginning of 2011 to the
end of 2015.
Prior to commencing the study, we obtained approval
from the University of Pavia Research Ethics Board. All
participants gave oral consent to participate in this study
at the start of the interviews.
Assessment of frailty
Edmonton Frail Scale (EFS): The EFS assesses nine
domains of frailty (cognition, general health status,
functional independence, social support, medication
usage, nutrition, mood, continence, functional per-
formance) [9, 11].
Test results can be from 0 to 17. The participants were
classified conventionally into three categories, and a
higher score represents a higher degree of fragility.
Severe Frail and non-frail participants were defined ac-
cording of the EFS score from No frailty (5 points)
Apparently vulnerable (6 n11 points) and Severe
frailty (12 n17) respectively.
Of note, the EFS was validated in the hands of non-
specialists who had no formal training in geriatric care
and the administration requires few minutes [9].
Assessment of functional performance
Handgrip strength test: Hand grip strength was assessed
using a Jamar dynamometer adhering to the standard-
ized protocol recommended by the American Society of
Hand Therapists [12]. Handgrip measurement was
assessed on the dominant hand and the average value of
the handgrip in the two genders was used to define the
scores: a score lower than 30 kg for man and lower than
20 kg for women was considered weak [13, 14].
Perna et al. BMC Geriatrics (2017) 17:2 Page 2 of 8
Barthel Index (BI): The functional status was assessed
by BI score. This scale ranges from 0 (totally dependent)
to 100 (totally independent) and assays 10 individual
aspects of daily living [15, 16].
Assessment of cognitive status and mood
Mini-Mental State Examination (MMSE): the MMSE is
a well-validated and widely used questionnaire to assess
global cognitive function, particularly to measure cogni-
tive impairment [17, 18].
Geriatric Depression Scale (GDS): The Geriatric
Depression Scale was administered to the patients to
measure depression. The scale has good internal
consistency (α= 0.86) [19], and a sensitivity of 80%
when compared to clinical diagnoses of depression [20, 21].
Assessment of comorbidities
The number of chronic medical comorbidities and drugs
was assessed from the hospital records of each patient.
Assessment of functional independence
Activities Daily Living (ADL) and Indipendent Activities
Daily Living (IADL): was measured by interviewing and
observing the participants during the interview [22].
Some studies suggest that a composite ADL/IADL scale
can be used to represent a single underlying dimension
of disability [23, 24].
Assessment of nutritional status
Mini nutritional assessment (MNA)
The MNA is composed of 18 items divided in four cat-
egories: anthropometric assessment, general state, diet-
ary assessment and self-assessment. A score 24 points
indicates a good nutritional status. A score from 17 to
23.5 points is an indicator of a risk of malnutrition,
while a score 17 points indicates malnutrition [25, 26].
Assessment of sarcopenia
Body composition measurement was evaluated using
fanbeam dualenergy Xray absorptiometry (DXA)
(Lunar Prodigy DXA; GE Medical Systems, Waukesha,
WI, USA). The in vivo coefficients of variation were
4.20% and 0.48% for fat and muscle mass, respectively.
The same investigator carried out all measurements for
every parameter. Evaluation of total bodyfat mass was
obtained by a whole body scan. Skeletal Muscle Index
(SMI) is the result of the sum of fat-free soft tissue mass
of arms and legs, all divided for height squared [27].
Assessment of osteoporosis
Bone Mineral Density (BMD) (g/cm2) of the total hip
was measured using DXA. BMD was labeled as normal
when T- score > 1.0, osteopenic if T-score < 1.0, osteo-
porosis when T-score ≤−2.5 [28].
Assessment of serum albumin
Data of biochemical investigations including serum albu-
min on the first day of admission were retrieved from
hospital records.
Statistical analysis
All statistical analyses were performed with the SPSS
22.0 package for MAC [27].
Descriptive data are expressed as means ± Standard
Deviations of the variables. Mean and standard devia-
tions are reported for continuous variables and percent-
ages for categorical variables.
Linear regression models adjusted for gender and age
were calculate for evaluating the association between
Edmonton Frail Scale and each evaluation tool with a
significant p-value <0.05.
A separate one-way ANOVA was performed for as-
categories of frailty. Comparisons of means for gender
were made by using the Student t-test for unpaired
values (p<0.05).
Baseline characteristics
Figure 1 summarizes patients recruitment. The baseline
characteristics for the entire study population (n= 366)
are listed in Table 1. The study population of 366 partic-
ipants had a mean age of 81.46 ± 6.55 years. The major-
ity were women (251, 68.6%), and living with an
impairment on admission upon hospitalization (ADL:
3.20 points). The mean body mass index (BMI) was
slightly overweight (25.05 ± 4.84 kg\m2).
Handgrip tests showed a general mean low muscle
strength of 16.51 ± 6.30 kg. Mean values of the Barthel
Index (62.45 ± 24.77 points) indicated a moderate
dependence overall.
The mean values of cognitive status and mood (Mini
Mental State Examination: 18.54 ± 6.24 points; Geriatric
Depression Scale: 5.80 ± 3.58 points) indicated a state of
mild impairment and depression.
In addition, the majority of the patients suffered of
osteopenia (hip T-score: 2.02 ± 1.31 SD) and showed a
moderate risk of malnutrition (Mini nutritional Assess-
ment: 18.10 ± 3.47 points).
Total and gender prevalence of frailty with different
Edmonton Frail Scale cut-off
As reported in Table 2, the prevalence of frailty accord-
ing to the level of the Edmonton Frail Scale, 19.7% were
classified as non-frail (men: 18.9%; women: 22.4%) sub-
jects, 66.4% as apparently vulnerable (men: 18.5%;
women: 47.8%), and 13.9% as severe frail (men: 14.9%;
women: 29.8%).
Perna et al. BMC Geriatrics (2017) 17:2 Page 3 of 8
Fig. 1 Flow diagram
Table 1 Baseline characteristics of the sample
Variable Men (115) Women (251) Total (366) P-value
(Mean ± SD) (Mean ± SD) (Mean ± SD)
Assessment of general data
Age, years 80.48 ± 6.09 81.90 ± 6.72 81.46 ± 6.55 0.045
Body Mass Index (kg/m
) 24.80 ± 4.02 25.17 ± 5.18 25.05 ± 4.84 0.494
EFS, points 8.03 ± 2.93 8.38 ± 2.85 8.27 ± 2.87 0.284
Assessment of functional performance
Hand Grip DX, kg 20.79 ± 6.08 14.58 ± 5.42 16.51 ± 6.30 p<0.001
Bartel Index, points 58.76 ± 25.01 64.09 ± 24.55 62.45 ± 24.77 0.089
Assessment of cognitive status and mood
MMSE, points 19.32 ± 6.43 18.18 ± 6.14 18.54 ± 6.24 0.192
GDS, points 4.75 ± 3.58 6.18 ± 3.59 5.80 ± 3.58 0.351
Assessment of general health status
Drugs, n 9.12 ± 3.45 8.41 ± 3.26 8.63 ± 3.33 0.260
Diseases, n 6.24 ± 2.96 5.88 ± 2.71 5.99 ± 2.79 0.063
Assessment of living independence
ADL, points 3.32 ± 1.88 3.32 ± 1.81 3.20 ± 1.83 0.103
Assessment of sarcopenia
SMI, n 7.50 ± 1.23 6.41 ± 1.10 6.75 ± 1.25 p<0.001
Assessment of osteoporosis
BMD, g/cm
0.88 ± 0.18 0.72 ± 0.14 0.77 ± 0.11 p<0.001
T-SCORE, points 1.49 ± 1.40 2.27 ± 1.20 2.02 ± 1.31 p<0.001
Assessment of nutritional status
Albumin, g/dl 3.67 ± 0.44 3.59 ± 0.57 3.65 ± 0.48 0.224
MNA, points 18.20 ± 3.2 18.06 ± 3.60 18.10 ± 3.47 0.696
Perna et al. BMC Geriatrics (2017) 17:2 Page 4 of 8
Variables mean among subjects with different frailty statuses
As showed in Table 3, among the three categories of
frailty, we found significant differences in mean scores of
all screening tools considered (p< 0.01). However, there
was not found significant differences across the three
frailty categories in Albumin level (p= 0.079), Skeletal
Muscle Index (p= 0.194) and BMI (p= 0.992).
Association between Edmonton Frail Scale and geriatric
evaluation tools
Table 4 Linear regression models adjusted for gender
and age showed an association between Edmonton Frail
Scale and each specific screening tool.
Frailty scores assessed by EFS were associated with
cognition (MMSE: β= 0.980; p> 0.01);); functional
independence (ADL: β=0.512; p< 0.00); (IADL: β=
0.338; p< 0.01); use of medications (β= 0.110; p<
0.01); Nutrition (MNA: β=0.413; p< 0.01); mood
(GDS: β=0.324; p< 0.01); functional performance
(Handgrip: β=0.114, p< 0.01) (Barthel Index: β=
0.037; p< 0.01), but not with number of comorbidities
(β= 0.108; p= 0.052).
Edmonton score according to sarcopenia and
As showed in Table 5, Between osteoporotic (and not)
patients, the mean EFS score did not differ (p= 0.365 in
women and p= 0.088 in men), whereas in Sarcopenic
(and not) patients, there was a significant difference in
women (p< 0.05) but not in men (p= 0.318).
This study shows the performance of Edmonton Frail
Scale on frailty assessment in clinical practice. We dem-
onstrate its association with multi-dimensional geriatric
conditions, with specific screening tools, such as MMSE,
ADL, IADL, MNA, GDS, Handgrip and Barthel Index.
Moreover, the EFS captures appropriately every single
area of frailty. Our study highlights this aspect, showing
Table 2 Distribution of frailty syndrome according to the score
on the Edmonton Frail Scale (EFS)
Level of frailty Men
No frailty (5 points) 18.5 22.4 19.7
Apparently vulnerable (6 n11 points) 66.6 47.8 66.4
Severe frailty (12 n17) 14.9 29.8 13.9
Table 3 Distribution of baseline characteristics among subjects with different frailty categories
No frailty
(5 points)
Apparently vulnerable
(6 n11 points)
Severe frailty
(12 n17)
(Mean ± SD) (Mean ± SD) (Mean ± SD) Pvalue
Age, years 78.93 ± 7.19 81.80 ± 6.41 82.92 ± 5.47 p<0.001
Body Mass Index (kg/m
) 24.96 ± 4.17 25.16 ± 5.01 24.85 ± 5.46 0.922
Assessment of functional performance
Hand Grip DX, kg 19.10 ± 6.43 16.21 ± 6.15 14.12 ± 5.73 p<0.05
Bartel Index, points 75,38 ± 21,85 61,6 ± 23,81 51 ± 26,80 p<0.001
Assessment of cognitive status and mood
MMSE, points 20.54 ± 5.86 18.37 ± 6.01 15.1 ± 7.05 p<0.001
GDS, points 7.57 ± 3.70 5.52 ± 3.49 4.60 ± 2.61 p<0.001
Assessment of general health status
Drugs, n 7,62 ± 3,42 8,77 ± 3,34 9,38 ± 2,92 p<0.05
Diseases, n 5.43 ± 2,42 5,95 ± 2,77 6,92 ± 3,20 p<0.05
Assessment of living independence
ADL, points 4,28 ± 1,69 3,10 ± 1,75 2,25 ± 1,79 p<0.001
Assessment of sarcopenia
SMI, n 6.96 ± 1.22 6.75 ± 1.28 6.48 ± 1.06 0.194
Assessment of osteoporosis
BMD, g/cm
0.81 ± 0.14 0.77 ± 0.17 0.73 ± 0.16 p<0.05
T-SCORE, points 1.79 ± 0.96 2.02 ± 1.35 2.41 ± 1.33 p<0.05
Assessment of proteinuria
Albumin, g/dl 3.73 ± 0.44 3.64 ± 0.50 3.62 ± 0.44 0.079
MNA, points 20,33 ± 3,35 17,96 ± 3,13 15,48 ± 3,11 p<0.001
Perna et al. BMC Geriatrics (2017) 17:2 Page 5 of 8
the association between EFS score and with specific
areas, such as independence living, drugs assumption,
mood, mental, functional and nutritional status. More-
over we determined relationship between EFS and osteo-
porosis and sarcopenia. Both these elements are the
novelty. To our knowledge other studies have taken in
account the relationship between EFS and single areas.
Secondary, this study has taken into account the reli-
ability of EFS to assess the prevalence of frailty in a
group of Italian institutionalized elderly patients. The
prevalence rate of severe frailty covered the 13.9% of the
subjects. The current most cited study was performed
by Fried et al. and showed that the prevalence of frailty
increased progressively with increasing age, up to a 25%
in the age group over 85 years old [5, 8].
Similar progression was reported by Klein et al. in the
United States [29]. In the past both the studies of
Walston [30] and Graham [31] which considered
patients over the age of 65 years, showed a prevalence
rate of 6.3% and 7.8% respectively.
In accordance with our study, similar data was
reported in the study by Bandeen-Roche, where in a
group of elderly patients between 70 and 79 years old,
the frailty showed a prevalence of 11.3% [32]. All areas
of frailty investigated showed a statistically significant as-
sociation with the EFS score. If in some ways, finding an
association among the EFS and outcome measures is not
surprisingly, in our opinion this evidence enlightens the
EFS usefulness as a powerful tool (easy to use and less
time-expensive) for geriatric multi-dimensional assess-
ment of frailty.
Specifically, the relationship between EFS and
MMSE showed a significant association, as described
previously in the literature by Kim et al. in [33] and
Ratio of developing dementia increases with worsen-
ing frailty [33, 34].
The area of frailty, which concerns the general
health status was assessed by counting the number of
pathologies showing a positive association with the
increase of the score of frailty according Edmonton
Frail Scale. Our results were in agreement with the
results obtained from previous studies in older
Americans in which shows a positive relationship
between dependence and frailty [35, 36].
Furthermore, drugs were found to be closely associ-
ated with the EFS score as already demonstrated in a
recent study on an Australian geriatric population [37].
Geriatric Depression Scale (GDS), shows an associ-
ation with the EFS. In recent study has also
highlighted the relationship between an increase of
frailty and depression [38].
Also the relationship between frailty and nutritional
status was investigated. The MNA appears to be asso-
ciated with the EFS. Among the areas of the frailty,
and therefore of potentially considerable of high clin-
ical relevance (as showed in Fig. 2). This point is fur-
ther justified in the scientific literature in the studies
by Izawa et al. [39] which demonstrated that the need
for clinical care increases with decreasing nutritional
status [39] and by Bollwein et al. [40] in which the
percentage of people at risk of malnutrition increased
progressively from no frail to severe frailty [40]. Our
study also emphasizes the importance of monitoring
the state of nutrition in the frail elderly population.
In fact, the data show a serious malnutrition both in
patients with severe frailty as well as in the
Table 5 Mean values of EFS score in references to sarcopenia
and osteoporosis diagnosis
(EFS: Mean ± SD)
No sarcopenic
(EFS: Mean ± SD)
Women 9.07 ± 2.34 8.24 ± 2.93 p<0.05
Men 8.37 ± 3.7 7.73 ± 2.93 0.318
(EFS: Mean ± SD)
No osteoporotic
(EFS: Mean ± SD)
Women 8.50 ± 2.57 8.17 ± 3.00 0.365
Men 9.04 ± 3.32 7.73 ± 2.82 0.088
Table 4 Association among EFS with multi-dimensional geriatric
conditions assessed with specific screening tools
Edmonton Frail
Scale area
Evaluation tools βCI 95% p- value
Cognition Mini Mental
State Examination
0.988 0.149;
General health
Number of
0.108 0.001;
Activities daily
living (ADL)
0.512 0.674;
Activities daily
living (IADL)
0.338 0.491;
Social Support No recorded - - -
Use of
Number of drugs 0.110 0.022;
Nutrition Mini Nutritional
0.413 0.487;
Mood Geriatric Depression
0.314 0.332;
Continence No recorded - - -
Handgrip 0.114 0.173;
Barthel Index 0.037 0.049;
Perna et al. BMC Geriatrics (2017) 17:2 Page 6 of 8
apparently vulnerable. Considering the parameters of
diagnosis of sarcopenia by gender, related to muscle
mass, the mean of the patients enrolled this study
were not sarcopenic (mean of Skeletal muscle index
in men: 7.51 kg/m2 and mean of Skeletal muscle
index in women: 6.41 kg/m2). However, if we con-
sider only muscle strength (through evaluation of the
handgrip strength), the preliminary associations within
the categories of frailty was significant.
Finally, another aspect of frailty, assessed by the evalu-
ation of bone mineral density (BMD), is osteoporosis.
The study considered subjects with average of bone
mineral density in a situation of osteopenia. The statis-
tical analysis shows a striking association between
T-score and EFS. This finding is confirmed and corrobo-
rated if we take into account the association with BMD,
which are rather significant. A previous study showed
that patients with osteoporosis have a higher risk of
developing frailty (OR = 2.1) [41].
A limitation of this study has been the lack of informa-
tion considering social support and incontinence due to
practical considerations in objectively quantifying these
parameters for this number of patients. No appropriate
scales with defined scores are known. In addition, data
were collected only by the administration of the test in
the interview with the patient.
Functional performance, measured by a walking test
in which measure the time it takes for the patient to
get up from a chair, walk about 3 m away and return
to sit, were instead represented in the statistical test
of Handgrip since this was most easily detectable in
immobile patients. Furthermore in patients not able
to run the tests mentioned above, the score was
awarded after an interview with the caregiver or by
evaluating the gait of the patient through the examin-
ation by the medical staff.
In conclusion, this study suggests that EFS is helpful and
performance tool to stratifying the state of frailty in a
group of institutionalized elderly. Using EFS, we have
demonstrated a significant association with all other
screening tools that impacting the frail state.
This highlights the potential of this scale as a cheap
and convenient performance screening tool to assess
frailty upon hospital admission.
ADL: Activities daily living; BMD: Bone mineral density; BMI: Body mass index;
EFS: Edmonton Frail Scale; GDS: Geriatric depression scale; IADL: Instrumental
activities of daily living; MMSE: Mini mental state examination; MNA: Mini
nutritional assessment; OR: Ozz ratio; SMI: Skeletal muscle index
We thank all nutritional team unit of Santa Margherita Hospital for their
collaboration in the study, and for critically reading the paper.
This work was not supported by any sponsor.
Availability of data and materials
The dataset supporting the conclusions of this article is available on request.
For further information on this database, you may contact the PI of the
project, Dr. Simone Perna (
SP designed this study in collaboration with MR. SP and MDF wrote this
protocol paper, receiving critical input from FM, AI, and CB. SP and FG
performed the statistical analysis, and wrote the statistical analysis together.
All authors read the paper and provided feedback. All authors read and
approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
Written informed consent was obtained from the patient for publication of
this study. A copy of the written consent is available for review by the
Editor-in-Chief of this journal.
Fig. 2 Graphical representation of the average values of MNA for each score of Edmonton Frail Scale
Perna et al. BMC Geriatrics (2017) 17:2 Page 7 of 8
Ethics approval and consent to participate
The present study received approval from the Ethics Committee of University
of Pavia, Italy. The participants received oral and written information about
the study and that participation in the evaluation was voluntary. They all gave
their written informed consent.
Author details
Department of Public Health, Experimental and Forensic Medicine, Section
of Human Nutrition and Dietetics, University of Pavia, Azienda di Servizi alla
Persona di Pavia, Via Emilia 12, Pavia, Italy.
Deprtment of Internal Medicine
and Medical Therapy, Section of Geriatrics University of Pavia, Azienda di
Servizi alla Persona, Pavia, Italy.
Research and Development Unit, Indena,
Milan, Italy.
Received: 16 February 2016 Accepted: 25 November 2016
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Background Patients with chronic kidney disease tend to have impaired functional status, and this can increase the risk of morbidity and mortality. However, no previous studies have rigorously evaluated the relationship between incident acute kidney injury (AKI) and functional status of elderly patients. Methods Elderly patients (≥65 years-old) were prospectively from the general medical wards of a single medical center in Taiwan between January, 2014 and August, 2014. These patients were divided into those with and without AKI at initial presentation, according to Kidney Disease Improving Global Outcomes (KDIGO) criteria. Functional status was assessed by Barthel Index on admission. Multiple regression analyses were utilized to investigate the relationship between AKI and functional status. Results One hundred and fifty-two elderly patients were recruited, 38.9 % of whom had AKI. Patients with AKI at admission had significantly higher mean Charlson Comorbidity Index score (p = 0.05) and borderline lower mean Barthel Index score (34.5 vs. 43.1; p = 0.08), and a significantly lower bladder continence subscale (5.4 vs. 7.0; p = 0.05). Multiple regression analyses indicated that the presence of AKI at admission was associated with a significantly lower Barthel Index score (p = 0.04). Increasing AKI severity (higher KDIGO stage) was also associated with significantly lower Barthel Index score (p <0.01). Conclusions This study documented a close relationship between AKI and functional status in the elderly. Interventions that aim to restore functional status might help to lower the risk of AKI in the elderly.
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Small vessel disease is a stroke subtype characterized by pathology of the small perforating arteries, which supply the sub-cortical structures of the brain. Small vessel disease is associated with high rates of apathy and depression, thought to be caused by a disruption of white matter cortical-subcortical pathways important for emotion regulation. It provides an important biological model to investigate mechanisms underlying these key neuropsychiatric disorders. This study investigated whether apathy and depression can be distinguished in small vessel disease both in terms of their relative relationship with white matter microstructure, and secondly whether they can independently predict functional outcomes. Participants with small vessel disease (n = 118; mean age = 68.9 years; 65% male) defined as a clinical and magnetic resonance imaging confirmed lacunar stroke with radiological leukoaraiosis were recruited and completed cognitive testing, measures of apathy, depression, quality of life and diffusion tensor imaging. Healthy controls (n = 398; mean age = 64.3 years; 52% male) were also studied in order to interpret the degree of apathy and depression found within the small vessel disease group. Firstly, a multilevel structural equation modelling approach was used to identify: (i) the relationships between median fractional anisotropy and apathy, depression and cognitive impairment; and (ii) if apathy and depression make independent contributions to quality of life in patients with small vessel disease. Secondly, we applied a whole-brain voxel-based analysis to investigate which regions of white matter were associated with apathy and depression, controlling for age, gender and cognitive functioning. Structural equation modelling results indicated both apathy (r = -0.23, P ≤ 0.001) and depression (r = -0.41, P ≤ 0.001) were independent predictors of quality of life. A reduced median fractional anisotropy was significantly associated with apathy (r = -0.38, P ≤ 0.001), but not depression (r = -0.16, P = 0.09). On voxel-based analysis, apathy was associated with widespread reduction in white matter integrity, with the strongest effects in limbic association tracts such as the anterior cingulum, fornix and uncinate fasciculus. In contrast, when controlling for apathy, we found no significant relationship between our white matter parameters and symptoms of depression. In conclusion, white matter microstructural changes in small vessel disease are associated with apathy but not directly with depressive symptoms. These results suggest that apathy, but not depression, in small vessel disease is related to damage to cortical-subcortical networks associated with emotion regulation, reward and goal-directed behaviour.
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Background: The aim of this study was to evaluate the factors associated with low skeletal muscle mass (SMM), sarcopenia, and sarcopenic obesity using nationally representative samples of people aged ≥65 years from diverse geographical regions of the world. Methods: Data were available for 18 363 people aged ≥65 years who participated in the Collaborative Research on Ageing in Europe survey conducted in Finland, Poland, and Spain, and the World Health Organization Study on global AGEing and adult health survey conducted in China, Ghana, India, Mexico, Russia, and South Africa, between 2007 and 2012. A skeletal muscle mass index (SMI) was created to reflect SMM. SMM, SMI, and percent body fat (%BF) were calculated with specific indirect population formulas. These estimates were based on age, sex, weight, height, and race. Sarcopenia and sarcopenic obesity were defined with specific cut-offs. Results: The prevalence of sarcopenia ranged from 12.6% (Poland) to 17.5% (India), and that of sarcopenic obesity ranged from 1.3% (India) to 11.0% (Spain). Higher %BF was associated with lower SMM in all countries, and with sarcopenia in five countries (p < 0.001). Compared to high levels of physical activity, low levels were related with higher odds for sarcopenia [OR 1.36 (95%CI 1.11-1.67)] and sarcopenic obesity [OR 1.80 (95%CI 1.23-2.64)] in the overall sample. Also, a dose-dependent association between higher numbers of chronic diseases and sarcopenic obesity was observed. Conclusions: Physical activity and body composition changes such as high %BF are key factors for the prevention of sarcopenia syndrome.
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Frailty and cognitive impairment are considered the most common and yet least understood conditions in older adults. This study was conducted to investigate the correlation between frailty and cognitive function in non-demented older Koreans. Korean Mini-Mental Status Examination (K-MMSE) scores and Cardiovascular Health Study Frailty Indices were obtained for 486 older adults aged 65 and over who registered at six senior welfare centers in Seoul and Gyeonggi province. Multiple linear regression was performed to identify the association between frailty and K-MMSE scores. Of the 486 older adults, 206 (42.4%) were robust, 244 (50.2%) were prefrail, and 36 (7.4%) were frail. Prevalence of cognitive impairment (K-MMSE ≤ 23) was 6.3% in the robust group, 16.8% in the prefrail group, and 30.6% in the frail group (P < 0.001), and mean K-MMSE score was 27.5 ± 2.2, 26.5 ± 3.1, and 23.7 ± 5.3, respectively (P < 0.001). Frailty tended to be associated with lower MMSE scores (B = -1.92, standard error, 0.52; P < 0.001). Frailty was found to be correlated with cognitive impairment in non-demented older Koreans. However, further cohort studies are required to determine the association between frailty and cognitive function.
Objectives To establish Montreal Cognitive Assessment (MoCA) scores that correspond to well-established cut-points on the Mini-Mental State Examination (MMSE). DesignCross-sectional observational study. SettingGeneral medical service of a large teaching hospital. ParticipantsIndividuals aged 75 and older (N = 199; mean age 84, 63% female). MeasurementsThe MoCA (range 0-30) and the MMSE (range 0-30) were administered within 2 hours of each other. The Abbreviated MoCA (A-MoCA; range 0-22) was calculated from the full MoCA. Scores from the three tests were analyzed using equipercentile equating, a statistical method for determining comparable scores on different tests of a similar construct by estimating percentile equivalents. ResultsMoCA scores were lower (mean 19.3 5.8) than MMSE scored (mean 24.1 +/- 6.6). Traditional MMSE cut-points of 27 for mild cognitive impairment and 23 for dementia corresponded to MoCA scores of 23 and 17, respectively. Conclusion Scores on the full and abbreviated versions of the MoCA can be linked directly to the MMSE. The MoCA may be more sensitive to changes in cognitive performance at higher levels of functioning.
Objectives: Increasing numbers of older people are undergoing emergency and elective arterial vascular procedures. Many older patients are frail which is a recognised predictor of adverse postoperative outcomes in other surgical specialties. This study in older patients undergoing arterial vascular surgery examined; the prevalence of preoperative frailty; the clinical feasibility of preoperatively measuring frailty and functional status; the association between these characteristics and adverse postoperative outcome. Methods: Prospective observational study in patients aged over 60 years undergoing elective and emergency arterial vascular surgery. Baseline measures of frailty (Edmonton Frail Scale), functional status (gait velocity, timed up and go, hand grip strength) and cognitive function (Montreal Cognitive Assessment) were obtained preoperatively. The primary outcome measure Length of Stay (LOS) and secondary outcome measures of postoperative morbidity (medical and surgical complications), functional status and postoperative in-hospital mortality were recorded. Results: 125 patients were recruited. Frailty was common in this older surgical population (52% EFS score of ≥ 6.5) with high frailty scores observed (mean EFS 6.6, SD 3.05) and poor functional status (60% had TUG > 15 s, 45% had gait velocity of < 0.6 m/s). Higher preoperative EFS (> 6.5) was univariately associated with longer LOS (≥ 12 days), composite measures of postoperative infections, postoperative medical complications and adverse functional outcomes. EFS ≥ 6.5 was predictive of LOS ≥ 12 days, adjusted for age (AUC 0.660, CI 0.541-0.779, p = 0.010). This association between EFS ≥ 6.5 and LOS ≥ 12 days was strengthened with the addition of MoCA < 24 (AUC 0.695, CI 0.584-0.806, p = 0.002). Conclusions: Patients aged over 60 years admitted for arterial vascular surgery were frail, had impaired functional status and were cognitively impaired. This combination of preoperative characteristics was predictive of longer hospital length of stay and associated with adverse postoperative outcome.
Objectives The aim of this study was to investigate the relationship between nutritional and functional status in acute geriatric patients including mobility and considering health status. Design Cross-sectional study. Setting Hospital. Participants 205 geriatric patients (median age 82.0 (IQR: 80–86) years, 69.3% women). Measurements Nutritional status was determined by Mini Nutritional Assessment (MNA) and patients were categorized as well-nourished (≥ 24 points), at risk of malnutrition (17–23.5 points) or as malnourished (< 17 points). Functional status was determined by Barthel Index (BI) and Timed ‘Up and Go’ Test (TUG) and related to MNA categories. Using binary multiple logistic regression the impact of nutritional status on functional status was examined, adjusted for health status. Results 60.3 % of the patients were at risk of malnutrition and 29.8 % were malnourished. Ability to perform basic activities of daily living (ADL) decreased with declining nutritional status. The proportion of patients unable to perform the TUG increased with worsening of nutritional status (45.0 % vs. 50.4 % vs. 77.0 %, p<0.01). After adjusting for age, gender, number of diagnoses, disease severity and cognitive function, a higher MNA score significantly lowered the risk of being dependent in ADL (OR 0.85, 95 % CI 0.77–0.94) and inability to perform the TUG (OR 0.90, 95 % CI 0.82–0.99). Conclusion Nutritional status according to MNA was related to ADL as well as to mobility in acute geriatric patients. This association remained after adjusting for health status.