JACC: HEART FAILURE
VOL. 7, NO. 12, 2019
ª 2019 BY THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION PUBLISHED BY ELSEVIER
Frailty Among Older Decompensated Heart Failure Patients Prevalence, Association With Patient-Centered Outcomes, and Efficient Detection Methods Ambarish Pandey, MD, MSCS,a Dalane Kitzman, MD,b David J. Whellan, MD, MHS,c Pamela W. Duncan, PT, PHD,d Robert J. Mentz, MD,e Amy M. Pastva, PT, PHD,f M. Benjamin Nelson, MS,b Bharathi Upadhya, MD,b Haiying Chen, PHD,g Gordon R. Reeves, MD, MPTh
ABSTRACT OBJECTIVES This study sought to assess the prevalence of frailty, its associations with physical function, quality of life (QoL), cognition, and depression and to investigate more efficient methods of detection in older patients hospitalized with acute decompensated heart failure (ADHF). BACKGROUND In contrast to the outpatient population with chronic HF, much less is known regarding frailty in older, hospitalized patients with ADHF. METHODS Older hospitalized patients (N ¼ 202) with ADHF underwent assessment of frailty (using Fried criteria), short physical performance battery (SPPB), 6-min walk test (6-MWT) distance, quality of life (QoL using the Kansas City Cardiomyopathy Questionnaire), cognition (using the Montreal Cognition Assessment), and depression (using the Geriatric Depression Screen [GDS]). The associations of frailty with these patient-centered outcomes were assessed by using adjusted linear regression models. Novel strategies to identify frailty were examined. RESULTS A total of 50% of older, hospitalized patients with ADHF were frail, 48% were pre-frail, and 2% were nonfrail. Female sex, burden of comorbidity, and prior HF hospitalization were significantly associated with higher likelihood of frailty. Frailty (vs. pre-frail status) was associated with a significantly worse SPPB score (5 2.2 vs. 7 2.4, respectively), 6-MWT distance (143 79 m vs. 221 99 m, respectively), QoL (35 19 vs. 46 21, respectively), and more depression (GDS score: 5.5 3.5 vs. 4.2 3.3, respectively) but similar cognition. These associations were unchanged after adjustment for age, sex, race, total comorbidities, and body mass index. Slow gait speed plus low physical activity signaled frailty status as well (C-statistic ¼ 0.85). CONCLUSIONS Ninety-eight percent of older, hospitalized patients with ADHF are frail or pre-frail. Frailty (vs. pre-frail status) is associated with worse physical function, QoL, comorbidity, and depression. The simple 4-m walk test combined with self-reported physical activity may quickly and efficiently identify frailty in older patients with ADHF. (J Am Coll Cardiol HF 2019;7:1079–88) © 2019 by the American College of Cardiology Foundation.
From the aDivision of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas; bDepartment of Internal Medicine, Section of Cardiovascular Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina; cDepartment of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania; dDepartment of Neurology, Wake Forest School of Medicine, Winston-Salem, North Carolina; eDepartment of Medicine, Cardiology Division, Duke University School of Medicine, Durham, North Carolina; fDepartment of Medicine and Orthopedic Surgery, Duke University School of Medicine, Durham, North Carolina; gDepartment of Biostatistics and Data Science, Wake Forest School of Medicine, WinstonSalem, North Carolina; and the hHeart and Vascular Institute, Novant Health, Charlotte, North Carolina. Supported by U.S. National Institutes of Health (NIH) grants R01AG045551 and R01AG18915; the Kermit Glenn Phillips II Chair in Cardiovascular Medicine at Wake Forest School of Medicine (to Dr. Kitzman); the Claude D. Pepper Older Americans Independence Center (OAIC) NIH grants P30AG021332 (to Dr. Kitzman) and P30AG028716 (to Dr. Pandey); the OAIC Pepper National Coordinating Center NIH grant U24 AG05964; and the Wake Forest Clinical and Translational Science Award, NIH grant UL1TR001420. Dr. Kitzman is a consultant for Abbvie, AstraZeneca, Merck, Novartis, Corvia Medical, Bayer, CinRx, Boehringer Ingelheim, and St. Luke’s Medical Center, Kansas City, Kansas; and has received research support from Novartis, Bayer, AstraZeneca, and St. Luke’s Medical Center, Kansas City, Kansas; and owns stock in Gilead Sciences. Dr. Mentz has received research support from Amgen, AstraZeneca, Bayer,
ISSN 2213-1779/$36.00
https://doi.org/10.1016/j.jchf.2019.10.003
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JACC: HEART FAILURE VOL. 7, NO. 12, 2019 DECEMBER 2019:1079–88
Frailty in Older Patients With ADHF
F
ABBREVIATIONS AND ACRONYMS 6-MWT = 6-minute walk test ADHF = acute decompensated heart failure
EQ-5D-5L = EuroQol 5dimension questionnaire
railty is a geriatric syndrome charac-
ADHF would facilitate future efforts to incorporate
terized
functional
frailty assessment into care pathways and to develop
reserve and heightened vulnerability
and test novel interventions to mitigate frailty and its
to pathophysiological stressors due to multi-
contributions to adverse outcomes in this vulnerable
system impairment that involves upregula-
older ADHF population, who continue to experience
tion of inflammatory pathways, endocrine
high rates of clinical events and poor quality of life
dysregulation, and sarcopenia (1). There is
following hospitalization (5–7).
by
decreased
growing recognition of the importance of
Therefore, this study sought to address these
frailty in heart failure (HF), particularly in
important knowledge gaps by examining baseline
Cardiomyopathy Questionnaire
those who are older (>60 years of age). Out-
data from the first 202 consecutively enrolled patients
QoL = quality of life
patients with chronic HF have a relatively
in the multicenter REHAB-HF (A Trial of Rehabilita-
high prevalence of frailty, and in that popu-
tion Therapy in Older Acute Heart Failure Patients;
survey
lation, frailty is associated with higher risk
NCT02196038) trial. The study assessed clinical and
SF-12 MCS = Short Form
of adverse outcomes, including mortality
historic variables associated with frailty based on
12-item survey Mental
and rehospitalization (2,3). However, much
Fried criteria. Associations between frailty and mul-
less is known regarding frailty among hospi-
tiple
talized patients with acute decompensated
depression, and cognitive function were also exam-
HF = heart failure KCCQ = Kansas City
SF-12 = Short Form 12-item
Composite Score
SF-12 PCS = Short Form 12-item survey Physical Composite Score
SPPB = short physical performance battery
measurements
of
physical
function,
QoL,
HF (ADHF), particularly older patients with
ined. Finally, simplified methods for efficiently
ADHF, who are the most vulnerable due to
identifying frailty specifically among older patients
a plethora of underlying age-related changes
hospitalized with ADHF were investigated.
that reduce reserve capacity and due to a much higher burden of comorbidity, and who have
METHODS
the highest rates of clinical events. In the FRAIL-HF study, Vidan et al. (2) demonstrated the independent
STUDY POPULATION. The present analysis included
association between frailty and worse 1-year clinical
the first 202 consecutively enrolled participants in the
outcomes among older hospitalized patients with
REHAB-HF
HF. However, few data exist regarding the association
February 2017 (6,8). REHAB-HF is an ongoing multi-
of frailty with patient-centered outcomes among
center, randomized, attention-controlled trial evalu-
older patients who are hospitalized with ADHF. This
ating a novel physical rehabilitation intervention
is particularly relevant considering the growing
among older patients hospitalized with ADHF. The
importance of patient-centered outcomes such as
study protocol, recruitment strategy, and inclusion
functional capacity and quality of life (QoL) for clin-
and exclusion criteria for REHAB-HF have been pub-
ical care as the endpoint in clinical trials (4).
lished previously (6). The study participants were
trial
between
September
2014
and
A major factor underlying our limited under-
older ($60 years of age) patients hospitalized with
standing of frailty in older patients with ADHF is that
ADHF who could perform basic activities of daily
it is rarely assessed in routine clinical care. Although
living independently and ambulate $4 m and whose
several
treatments planned for discharge to home. Both HF
frailty
assessment
methods
have
been
described (1), many are cumbersome and time inten-
with preserved ejection fraction ($45%) and HF with
sive and have not been fully validated in older pa-
reduced ejection fraction (<45%) were included. Pa-
tients with ADHF. Thus, there is a need for a simple,
tients with end-stage HF, severe valvular disease,
effective, and efficient screening tool to identify
advanced dementia, end-stage renal disease, or ter-
frailty in older patients with ADHF. A better under-
minal illness were excluded. The objective criteria for
standing of the relationships of frailty with patient-
ADHF included at least 2 signs of decompensated HF
centered outcomes and availability of a simpler
(pulmonary congestion by radiography or clinical
means to identify frailty in hospitalized patients with
examination,
elevated
jugular
venous
GlaxoSmithKline, Gilead, Luitpold, Medtronic, Merck, Novartis, Otsuka, and ResMed; and has received honoraria from Abbott, Bayer, Janssen, Luitpold Pharmaceuticals, Merck, Novartis, and ResMed; and has served on advisory boards for Amgen, Luitpold, Merck, and Boehringer Ingelheim. Dr. Whellan has received research support from National Institutes of Health, Amgen, CVR Global, Merck, Novartis, ResMed; and is a consultant for Akros Pharmaceuticals, BDC Advisors, Cytokinetics, and Fibrogen. Dr. Duncan is a consultant for Molec; and holds equity in Care Directions. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose. Barry Greenberg, MD, served as Guest Editor for this paper. Manuscript received September 3, 2019; revised manuscript received October 7, 2019, accepted October 7, 2019.
pressure,
Pandey et al.
JACC: HEART FAILURE VOL. 7, NO. 12, 2019 DECEMBER 2019:1079–88
Frailty in Older Patients With ADHF
elevated natriuretic peptide levels, or lower extrem-
provides a physical (SF-12 PCS) and mental (SF-12
ity edema), at least 1 symptom of decompensated HF
MCS) composite score. The SF-12 PCS was used to
(exertional dyspnea, fatigue, paroxysmal nocturnal
define physical activity frailty criteria (and is there-
dyspnea, or orthopnea), and use of ADHF therapies
fore not used as a QoL measure in this analysis),
such as diuretics, vasodilators, and inotropes. ADHF
whereas the SF-12 MCS was used as a measurement of
diagnosis was confirmed by a REHAB-HF investigator,
emotional QoL (6). Cognitive function was assessed
a board-certified cardiologist with expertise in HF.
by using the Montreal Cognitive Assessment (MoCA)
Informed consent was obtained from all patients, and
test. Depressive symptoms among study participants
the study was approved by the Institutional Review
were assessed using the Geriatric Depression Scale
Boards of all participating centers.
(GDS), a 15-item survey with a score of >5 indicating
FRAILTY DEFINITION. Frailty status (frail, pre-frail,
depression (6).
or non-frail) of the study participants was deter-
STATISTICAL ANALYSIS. The proportions of patients
mined based on the widely accepted and validated
hospitalized with ADHF who were frail, pre-frail, and
Fried criteria as described previously (9–11), using the
non-frail were determined by using the Fried frailty
following 5 criteria: 1) unintentional weight loss in
criteria. Owing to the small number of patients who
the last year; 2) self-reported exhaustion; 3) weakness
were non-frail (n ¼ 4 [2%]), the analyses focused on
as assessed by grip strength using a hand dynamom-
comparisons between the pre-frail and the frail
eter; 4) slowness as assessed by gait speed during a 4-
groups. The baseline characteristics of frail and pre-
m walk test; and 5) low physical activity as assessed
frail patients with ADHF were reported as mean
by the Short Form-12 Physical Composite Score (SF-12
SD and frequency, n (%), for continuous and cate-
PCS). The cutoff values for meeting each of these
gorical variables, respectively. Chi-square and t-tests
criteria are shown in Online Table 1. Participants were
were used for the between-group comparisons of the
identified as frail, pre-frail, and non-frail if $3, 1, or 2,
categorical and continuous variables, respectively.
and none of the criteria for frailty were met at base-
Negative binomial regression was used for count data
line assessment, respectively. Gait speed assessed by
(e.g., hospitalizations, falls). Participant characteris-
using a simple 4-m walk test and grip strength were
tics that differed between frail and pre-frail status (at
also investigated as alternative single-item frailty
a p level of <0.10) were entered into a logistic
measurements (1), as discussed below.
regression model with a backward selection method
ASSESSMENT OF PHYSICAL FUNCTION, QoL, AND
to identify clinical predictors of frail versus pre-frail
COGNITIVE
status. A significance level of 0.05 was used for ef-
FUNCTION. All
measurements
were
conducted by trained personnel using standardized
fect variable removal during the selection process.
protocols after initial treatment and stabilization of
Adjusted linear regression models were also con-
ADHF symptoms. Physical function was assessed by
structed to determine the association between frailty
using the short-physical performance battery (SPPB)
phenotype and its individual components and out-
score, the 6-min walk test (6-MWT) distance, and
comes of 6-MWT distances, QoL measurements, and
handgrip strength in accordance with standardized
cognitive function measurements. Separate models
protocols. The SPPB score is a well-established and
were constructed for each outcome and exposure
reproducible measurement of physical function in
variables of interest and adjusted for age, sex, race,
older adults and the primary outcome for the REHAB-
body mass index, and total comorbidities. The SPPB
HF trial (6,12). The SPPB test consists of 3 compo-
score and physical health components of the SF-12
nents, standing balance, gait speed, and timed
were not included in this analysis due to overlap
repeated chair rises. Each component is scored on a
with the Fried criteria used in this study. The sample
scale of 0 to 4 and combined for a total score of up to
size of the present study (n ¼ 202) provided 80%
12, with a lower score indicating greater functional
power to detect correlations as low as 0.20 between
impairment. A 6-MWT was measured by participants
frailty status and other patient-centered outcomes.
walking
in
an
unobstructed
hallway.
Handgrip
strength was measured using a hand dynamometer.
Finally, receiver-operating characteristic curves were created to assess how each frailty criterion
QoL assessment was performed using the following
identified frailty versus pre-frailty by using area un-
3 complementary assessments: 1) the Kansas City
der the curve (C-statistic). The 2 criteria with the
Cardiomyopathy Questionnaire (KCCQ) overall and
highest discrimination index (C-statistic) were com-
physical limitation scores; 2) the EuroQoL-5D-5L
bined in a model to assess how this improved frailty
questionnaire (EQ-5D-5L); and 3) the SF-12 Score.
identification. Additional receiver-operating charac-
The SF-12 Score is a 12-item questionnaire that
teristic curves were constructed for gait speed by
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JACC: HEART FAILURE VOL. 7, NO. 12, 2019 DECEMBER 2019:1079–88
Frailty in Older Patients With ADHF
C E N T R A L IL L U ST R A T I O N Synopsis of Key Findings From This Study
Frailty Is Highly Prevalent Among Older, Hospitalized Patients With ADHF, Is Associated with Patient-centered Outcomes, and Is Easily Detected by a Novel Method 98% are frail or pre-frail by the Fried Criteria
More Depressive Symptoms
Not Frail 2%
Pre-frail 48%
Poor Functional Status
Frail 50%
Poor Quality of Life
Frailty can be quickly and easily identified by 4-meter walk test and physical activity assessment (C-statistic:0.85) Pandey, A. et al. J Am Coll Cardiol HF. 2019;7(12):1079–88. ADHF ¼ acute decompensated heart failure.
using simplified cutoff values ranging from 0.4 to
pre-frail) and exhaustion (92% in frail and 63% in pre-
1.0 m/s at intervals of 0.2 m/s based on the previously
frail cases).
reported thresholds for meaningful associations with functional status (13). All statistical analyses were performed using SAS version 7.1 software (SAS Institute, Cary, North Carolina).
CLINICAL
CHARACTERISTIC
DIFFERENCES
BE-
TWEEN FRAIL AND PRE-FRAIL PATIENTS WITH ADHF. Female sex, chronic kidney disease, higher
burden of comorbidity, and HF hospitalization (but
RESULTS
not all-cause hospitalizations) in the 6 months prior to enrollment were associated with being frail in the
FRAILTY BURDEN IN PATIENTS WITH ADHF. Based
unadjusted analysis. There were no differences in
on the standard Fried criteria for frailty, 50%
age, ejection fraction, New York Heart Association
(n ¼ 101) of participants were classified as frail, 48%
functional classes, and use of HF therapies among
(n ¼ 97) as pre-frail, and only 2% (n ¼ 4) as non-frail
pre-frail versus frail participants (Table 1). In logistic
(Central
regression, significant predictors of frailty were fe-
Illustration).
The
most
common
frailty
criteria met among the frail and the pre-frail patients
male sex (odds ratio [OR]: 2.69; 95% confidence
with ADHF were slowness (95% in frail and 49% in
interval [CI]: 1.47 to 4.93; p ¼ 0.001), prior HF
Pandey et al.
JACC: HEART FAILURE VOL. 7, NO. 12, 2019 DECEMBER 2019:1079–88
Frailty in Older Patients With ADHF
hospitalization (OR: 2.19; 95% CI: 1.09 to 4.39; p ¼ 0.027), and overall comorbidity burden (OR: 1.21; 95% CI: 1.04 to 1.41; p ¼ 0.012).
T A B L E 1 Baseline Characteristics, Comorbidities, and Medications by Frailty
Status of Older Hospitalized Patients With Acute Decompensated Heart Failure*
PHYSICAL FUNCTION, COGNITION, QoL DIFFERENCES BETWEEN
FRAIL
AND
PRE-FRAIL
PATIENTS
WITH
Pre-Frail (n ¼ 97)
Frail (n ¼ 101)
p Value
ADHF. Frail participants had significant impairment in
Age, yrs
71.1 7.3
72.9 7.7
0.091
physical function with a lower mean SPPB score
Women
43 (44)
65 (64)
0.005
across all domains and significantly decreased 6MWT distance results than pre-frail participants. A total of 99% of frail and 85% of pre-frail participants
Non-white
54 (56)
48 (48)
0.25
BMI, kg/m2
32.8 7.7
33.9 9.8
0.39
56 (58)
47 (47)
0.11 0.72
Ejection fraction, <45% New York Heart Association functional class
had an SPPB score of <10 (p < 0.001), a cutoff value
II
16 (16)
13 (13)
associated with significantly higher risk of disability
III
50 (52)
52 (51)
IV
23 (24)
22 (22)
Patients previously hospitalized within 6 months
37 (38)
49 (48)
0.14
Patients previously hospitalized for HF within 6 months
18 (19)
34 (34)
0.016
strength was significantly lower in frail (vs. pre-frail) women but was comparable among men across the 2
Comorbidities
groups. A high burden of mild cognitive impairment
Hypertension
89 (92)
94 (93)
0.73
(MoCA: <26) was observed in both the frail and the
Hyperlipidemia
69 (71)
69 (68)
0.67
Diabetes mellitus
54 (56)
54 (53)
0.76
Atrial fibrillation
39 (40)
52 (51)
0.11
CAD (previous MI, PCI, or CABG)
37 (38)
35 (35)
0.61
and mortality in older adults (12). Gait speed was also significantly decreased in frail participants compared to that in pre-frail participants. In contrast, grip
pre-frail study participants (82% vs. 73%, respectively; p ¼ 0.23). There was also no significant association
between
frailty
status
and
cognitive
performance on the MoCA scale (Table 2). Frail (vs. pre-frail) participants had significantly
Peripheral vascular disease
13 (13)
13 (13)
0.91
Chronic obstructive pulmonary disease
25 (25)
37 (37)
0.10
Obstructive sleep apnea
29 (30)
31 (31)
0.90
lower HF-specific (according to KCCQ) and general
Chronic kidney disease
25 (26)
41 (41)
0.027
QoL (by EQ-5D-5L) scores. General QoL was reduced
Stroke
18 (19)
14 (14)
0.37
Arthritis/connective tissue disease
40 (41)
53 (53)
0.11
Cancer
17 (18)
24 (24)
0.28
in frail patients in multiple domains including mobility, usual activities, and higher pain/discomfort
Dementia/cognitive impairment
levels (Table 2). Furthermore, there was a trend for
Depression
higher prevalence of depression among frail partici-
Total comorbidities
pants, with 53% frail and 40% pre-frail patients
Current medications
1 (1)
3 (3)
0.33
13 (13)
20 (20)
0.23
5.8 1.9
6.5 2.2
0.013
demonstrating a GDS score of 5 or higher, suggestive
Loop diuretic
91 (95)
93 (92)
0.44
of depression (p ¼ 0.06). The associations between
Beta blocker
80 (83)
85 (84)
0.88
ACE or ARB
61 (63)
64 (63)
0.82
Aldosterone antagonist
21 (22)
15 (15)
0.20
8 (8)
5 (5)
0.34
frailty and impairment in physical function (6-MWT distances), lower QoL measurements, and higher burden of depression were also consistent in adjusted analysis accounting for age, sex, race, total comorbidities, and body mass index (Table 3). Among the individual components of the Fried phenotype, slowness, as determined by gait speed, was strongly
Digoxin
Values are mean SD or n (%). *n ¼ 4 participants (2%) were classified as non-frail (met 0 criteria). ACE ¼ angiotensin-converting enzyme; ARB ¼ angiotensin II receptor blocker; BMI ¼ body mass index; CAD ¼ coronary artery disease; CABG ¼ coronary artery bypass graft; HF ¼ heart failure; MI ¼ myocardial infarction; PCI ¼ percutaneous coronary intervention.
associated with physical function measurements, and exhaustion and physical activity were associated with QoL and depression burden (Online Table 2). ASSOCIATION OF GAIT SPEED AND HANDGRIP
result) and low physical activity (by SF-12 PCS scores) had the highest discrimination (C-statistic ¼ 0.73 for each) in distinguishing frail from pre-frail patients
STRENGTH WITH OUTCOMES. Higher gait speed and
with ADHF based on the full, standard 5-item Fried
handgrip strength were both significantly associated
criteria for frailty (Table 4). Combined, the C-statistic
with higher 6-MWT and better cognitive function in
of slow gait speed and the low physical activity was
adjusted analyses. Higher gait speed, but not hand-
0.85 0.02. The 4-m walk test alone, using a cutoff
grip strength, was associated with higher HF-specific
value of 0.8 m/s, was highly sensitive for identifying
and overall QoL based on KCCQ physical limitation
frailty (sensitivity ¼ 0.98; specificity ¼ 0.37) (Table 4).
and EQ-5D-5L scores (Table 3).
Combined with low physical activity, a gait speed
SIMPLIFIED FRAILTY ASSESSMENT. Among individ-
cutoff value of 0.8 m/s had a C-statistic value of 0.83
ual frailty criteria, slow gait speed (by 4-m walk test
0.03.
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JACC: HEART FAILURE VOL. 7, NO. 12, 2019 DECEMBER 2019:1079–88
Frailty in Older Patients With ADHF
good discrimination of frail versus pre-frail (C-statis-
T A B L E 2 Physical Function, Quality of Life, and Cognition by Frailty Status of
tic: 0.85).
Hospitalized Patients With Acute Decompensated Heart Failure
Our study findings add significantly to prior
Pre-Frail (n ¼ 97)
Frail (n ¼ 101)
p Value
SPPB total score
7.0 2.4
5.0 2.2
<0.001
Balance score
2.9 1.2
2.4 1.3
0.001
population of older patients hospitalized for ADHF
4-m walk score
2.7 1.0
1.8 0.8
<0.001
(2). The patient-centered outcomes associated with
Chair stand score
1.4 1.2
0.8 0.9
<0.001
frailty in the present analysis, such as impaired
SPPB score <10
82 (85)
100 (99)
<0.001
physical function and QoL, have independent clinical
Male, n ¼ 89
30.0 7.9
27.8 9.1
0.21
Females, n ¼ 105
23.2 7.4
18.1 5.8
<0.001
0.70 0.22
0.50 0.16
<0.001
221 99
143 79
<0.001
KCCQ overall summary score
46 21
35 19
<0.001
tance of <150 m; a SPPB score of <6; collective
KCCQ physical limitation score
53 23
42 23
<0.001
assessment of endurance, balance, mobility, and
Short Form-12 MCS
44 15
44 14
0.78
strength) and QoL (KCCQ score of <40; global visual
Mobility
2.3 1.0
2.7 1.0
0.008
Self-care
1.6 0.8
1.8 0.9
0.14
Usual activities
2.5 1.2
2.9 1.2
0.018
placement in a nursing or rehabilitation facility were
Pain/discomfort
2.1 1.0
2.7 1.1
0.001
excluded (6). Among individual components of the
Anxiety/depression
1.7 0.9
1.9 1.0
0.09
Fried frailty phenotype, low gait speed on the 4-m
62 21
53 24
0.008
walk test appeared to primarily account for the as-
4.2 3.3
5.5 3.5
0.009
sociation of frailty with 6-MWT, and the physical
39 (40)
54 (53)
0.06
22.0 4.5
21.4 4.5
inactivity and exhaustion components of the Fried
0.94
73 (75)
83 (82)
0.23
Physical Function Variable
Grip strength, kg
Gait speed, m/s 6MWD, m
knowledge regarding the importance of frailty in patients with HF and particularly the large, important
importance in addition to also being strong, independent predictors of rehospitalization, loss of independence,
and
all-cause
mortality
(2,14).
Furthermore, among frail older patients with ADHF, the impairments of physical function (6-MWT dis-
Quality of life
EQ-5D-5L components
Thermometer/VAS, 0–100 GDS score GDS score $5 MoCA total score MoCA <26 Values are mean SD or n (%).
6MWD ¼ 6-minute walk distance; EQ-5D-5L ¼ EuroQol; GDS ¼ Geriatric Depression Screen; KCCQ ¼ Kansas City Cardiomyopathy Questionnaire; MCS ¼ mental composite score; PCS ¼ physical composite score; SPPB ¼ Short Physical Performance Battery; VAS ¼ visual analog scale; MoCA ¼ Montreal Cognitive Assessment.
analog scale score of <55) were strikingly broad and severe, especially considering that patients requiring
frailty phenotype appeared to primarily account for associations with QoL and higher depression burden. Taken together, findings from the present study suggest that distinct aspects of frailty in older patients with ADHF may identify impairments across specific domains including functional status, mood, and quality of life, and inform caregivers and facili-
DISCUSSION
tate design of novel interventions to address these impairments.
Several important findings were observed in this
Frailty prevalence in the present cohort of older,
study. First, female sex, prior HF hospitalization, and
hospitalized patients with HF (50% frail; 98% meeting
total comorbidity burden were independently asso-
at least 1 frailty criterion) was at least double that
ciated with frailty status, whereas age and individual
observed among older outpatients with HF (15% to
comorbidities were not. Second, frailty, as defined by
25%) (3). Consistent with the current observations,
the well-accepted and validated Fried criteria, was
Vidan et al. (2) also reported a high prevalence of
independently associated with worse physical per-
frailty (w75%) in the FRAIL-HF trial, which studied an
formance across all domains (balance, mobility,
older cohort (>70 years of age; mean: 80 years of age)
strength, and endurance), lower HF-specific and
of 450 hospitalized patients with HF from Europe.
general QoL, and higher burden of depressive symp-
The present study builds upon the study by Vidan
toms but not with cognitive impairment. Finally, we
et al. (2) and adds to our understanding of frailty in
explored simplified, more efficient frailty assessment
ADHF by evaluating the associations between frailty
strategies for older patients hospitalized with ADHF.
measurements and other patient-centered outcomes
Gait speed, assessed by a simple 4-m walk test, was a
in a cohort of not quite as old (mean: 72 years of age)
highly sensitive and meaningful single-item assess-
patients with ADHF from the United States with
ment, retaining most associations with physical per-
higher burden of comorbidities and higher proportion
formance, QoL, and depression seen with the full
of patients with symptoms of New York Heart Asso-
Fried frailty criteria. Combined with self-reported
ciation functional classes III/IV. The present study
physical activity easily and quickly obtained from
also explored a potentially more efficient, simpler
the SF-12, this simple 2-item assessment provided
means of identifying frailty in patients with ADHF
Pandey et al.
JACC: HEART FAILURE VOL. 7, NO. 12, 2019 DECEMBER 2019:1079–88
1085
Frailty in Older Patients With ADHF
that may be more amenable to routine clinical practice.
T A B L E 3 Adjusted Association of Frailty Phenotype, Gait Speed, and Grip Strength With
Measurements of Physical Function, Quality-of-Life, and Cognition
Several factors likely account for the high prevalence
of
frailty
in
older
Frail vs. Pre-Frail
patients with ADHF,
Gait Speed*
Grip Strength†
p Value
Parameter Estimate
of ADHF mediated through activation of inflamma-
6MWD, m
61 12
<0.001
28 2
<0.001
13 5
tory and neurohumoral pathways and hospital-
KCCQ overall score
12 3
<0.001
11
0.09
01
0.71
associated immobility, which contribute to the
KCCQ physical limitation score
11 3
0.002
31
0.007
11
0.67
“post-hospitalization syndrome” (15). Older frail pa-
SF-12 MCS
1 2
0.98
01
0.43
01
0.57
tients with ADHF may be especially vulnerable to
EQ-5D-5L components
including aging-related changes, the systemic effects
this phenomenon, associated with significant functional decline during hospitalization that persist following discharge when the risk of adverse clinical events is highest. Lingering adverse effects of prior HF hospitalization can persist for months following
0.3 0.1
0.051 0.1 0.0 <0.001 0.0 0.1
0.2 0.1
0.24
0.1 0.0 0.023 0.0 0.1
0.52
Usual activities
0.3 0.2
0.08
0.1 0.0
0.95
Pain/discomfort
0.5 0.2
0.001 0.1 0.0 0.025
0.0 0.1
0.57
Anxiety/depression
0.2 0.1
0.13
0.1 0.0
0.14
0.0 0.1
0.54
VAS, 0-100
9.0 3
0.008
0.6 0.8
0.42
3.0 1
1.3 0.5
0.009 0.2 0.1 0.044 0.4 0.2
rates of frailty among those hospitalized for HF
MoCA total score
significantly and independently to frailty. This is
0.4 0.7
0.54
0.4 0.2
0.08
0.012
0.0 0.1
0.5 0.3
Abbreviations as in Table 2.
cumulative tally of comorbid conditions in identifying frailty (10,18). Comorbid burden has been
impairments of physical function (25). Cognition
shown in other studies to contribute significantly to
impairment assessments provide independent prog-
adverse clinical outcomes in patients with HF (19). At
nostic value even after accounting for physical frailty
least 50% of rehospitalizations and deaths experi-
based on the Fried criteria (23), supporting the fact
enced by this population are attributable to noncar-
that HF care models should address both cognitive
diac causes, but no single comorbid condition is
and physical functional impairments (7).
dominant (20,21). Importantly, comorbid conditions also interact with HF and collectively increase the Surprisingly, age was not independently associated with frailty in the present cohort, despite a
T A B L E 4 Discriminative Ability of Individual Components of the
Frailty Criteria Based on the Fried Phenotype in Hospitalized Patients With Acute Decompensated Heart Failure
relatively low cutoff age used to define older adults ($60 years of age) and a wide range of ages repre-
C-Statistic‡ Sensitivity Specificity
Fried frailty criteria*
sented (range 60 to 92 years of age; mean: 72.4 7.8
Slowness, gait speed†
0.73 0.03
95
51
years of age). A similar finding has been reported
Weakness, handgrip strength
0.69 0.03
53
85
among frail patients with advanced HF considered
Weight loss
0.61 0.03
40
81
for left ventricular assist device implantation and
Exhaustion
0.65 0.03
92
37
heart transplantation (23,24). Such patients share
Low physical activity†
0.73 0.03
67
78
Slowness combined with low physical activity†
0.85 0.02
62
91
multiple characteristics with the present cohort, including recurrent HF hospitalizations, severely
Additional gait speed cutoff values
reduced QoL, and severe functional impairment, all
<1.0 m/s
0.54 0.01
100
7
independent predictors of adverse clinical events as
<0.8 m/s
0.68 0.03
98
37
previously noted. These findings support the need to
<0.7 m/s
0.69 0.03
88
50
<0.6 m/s
0.71 0.03
73
69
formally assess frailty in a broad age range of patients with ADHF, particularly among women, who were at more than double the risk of being frail than
<0.4 m/s Gait speed <0.8 m/s combined with low physical activity
0.61 0.28
31
91
0.83 0.03
65
89
men. Cognitive impairment, which is also highly prevalent in our cohort, did not appear associated with physical frailty. This may be related to the fact that the Fried frailty phenotype focuses primarily on
0.92
0.05 0.08 0.043
Values are median SD. Adjusted for age, sex, BMI, race, and comorbidities. *per 0.10 m/s change in gait speed. †per 6-kg change in handgrip strength.
consistent with frailty models that incorporate a
risk of HF-related events as well (22).
0.015
Self-care
GDS score
overall burden of comorbidities also contributed
p Value
Parameter Estimate p Value
Mobility
discharge (16,17) and may help account for the higher within the 6 months prior to study enrollment. An
Parameter Estimate
Values are mean SD or %. Low physical activity is based on the Physical Composite Score of the SF-12 questionnaire (see Online Table 1). Participants were identified as frail if they met 3 or more of the components of the Fried frailty criteria listed above. *The cutoff values for each component to meet the Fried frailty criteria are shown in Online Table 1. †Slowness is defined by using the 4m walk test according to the Fried frailty criteria cutoff. ‡Area under the curve.
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JACC: HEART FAILURE VOL. 7, NO. 12, 2019 DECEMBER 2019:1079–88
Frailty in Older Patients With ADHF
Despite the high prevalence and prognostic impli-
measurements of physical function, QoL, depression,
cations of frailty in this high-risk population, it is not
and cognition within a relatively large, diverse pop-
routinely assessed or addressed in current care
ulation of older patients with ADHF from across
models or disease management pathways for ADHF.
multiple sites and with uniform training in the
This has been largely attributed to the cumbersome
assessment of these outcomes. This study addresses a
and resource intensive nature of the most common
key knowledge gap: how different frailty assessments
frailty assessment methods. The current findings
or screening instruments perform among patients
suggest simplified and efficient frailty assessment
with ADHF; and it explores single, quick, and efficient
strategies that may be more easily integrated into
measurements of frailty status for use in this
routine clinical practice. Gait speed, as measured by
vulnerable population. Thus, this work makes several
the simple, quick 4-m walk test, was a highly effective
steps forward that are essential for the ultimate goal
screening test with 98% sensitivity using a cutoff
of identifying frailty in clinical practice and devel-
value of 0.8 m/s. Gait speed is also clinically mean-
oping and testing interventions to mitigate it.
ingful, retains associations with patient-centered outcomes, and has been strongly linked to adverse
STUDY LIMITATIONS. The study cohort was limited
clinical events (2). Furthermore, gait speed is time-
to participants who were eligible for enrollment in a
efficient, simple to measure, requires no special
clinical trial. However, the trial enrollment criteria
equipment, and thus can be obtained from most pa-
were broadly inclusive of older, sick patients with
tients, including older patients with ADHF, as shown
multiple comorbidities, wide range of functional
in this study. Combining gait speed with self-reported
performance, and a strong representation of HF with
physical activity added specificity such that this
both preserved and reduced ejection fraction, women
simple
high
and minorities, all typical of the general older ADHF
discriminative (C-statistic: 0.85) value for frailty
population. Second, due to exclusion of patients
versus pre-frailty as determined by the standard
whose treatment was planned for transition to reha-
Fried criteria. The credibility of our findings with re-
bilitation or skilled nursing facilities, the authors
gard to efficient strategies for identification of frailty
might
in older patients with ADHF is supported by reports
impairment in hospitalized older patients with ADHF.
from the chronic HF and general geriatric populations
However, the severity of the impairments in perfor-
that gait speed is a powerful predictor of a wide range
mance noted across multiple domains of physical
of outcomes, including mortality, hospitalization,
function and QoL as well as cognitive performance
and nursing home placement (26).
assessments support the robustness and generaliz-
2-item
assessment
demonstrated
have
underestimated
the
magnitude
of
Another potential barrier to the integration of
ability of these observations. Third, cross-sectional
frailty assessments into clinical practice is the limited
analyses don’t allow assessment of associations be-
evidence about the clinical benefit of targeting frailty.
tween frailty and clinical events. Fourth, our novel
The present study findings have important clinical
methods to detect frailty should be confirmed in a
implications in this regard, suggesting that frailty
separate prospective sample of patients with ADHF.
assessment among hospitalized patients with ADHF
Fifth, although the samples size provided 80% power
identifies those with significant functional impair-
to detect correlations as low as 0.20, the study
ment. Such impairments persist following discharge
may have missed weaker correlations although
when the risk of adverse clinical events is highest.
correlations #0.19 are usually regarded to be of
This phenomenon, referred to as the “post-hospital-
marginal clinical relevance. Sixth, although some of
ization syndrome,” has been the focus of recent
the measurements, such as the 6-MWT and 4-m walk
health policy initiatives undertaken to avoid reho-
tests, which are components of the Fried frailty
spitalization (15). Identifying patients who may be at
phenotype, may seem inherently related, correlations
the highest risk of disability and adverse events post-
are not predestined. For example, the 6-MWT is pri-
discharge can facilitate future efforts to develop
marily a measurement of endurance and is deter-
novel interventions to address the adverse impact of
mined by cardiovascular reserve and can be limited
frailty on outcomes (2,12).
by cardiovascular symptoms. In contrast, the 4-m including
walk test measures mobility and integrates balance,
comprehensive assessment of frailty by using the full
coordination, and neurosensory feedback and is
Fried criteria to compare with multiple detailed
rarely affected by endurance and cardiovascular
This
study
has
several
strengths,
Pandey et al.
JACC: HEART FAILURE VOL. 7, NO. 12, 2019 DECEMBER 2019:1079–88
Frailty in Older Patients With ADHF
symptoms. Finally, the MoCA test is a screening instrument for cognitive impairment and not a diag-
ADDRESS FOR CORRESPONDENCE: Dr. Gordon R.
nostic tool. More comprehensive neuropsychological
Reeves, Novant Health Heart & Vascular Institute,
testing is required to identify specific cognitive
1718 East 4th Street, Charlotte, North Carolina 28204.
deficits and the associated clinical implications.
E-mail:
[email protected].
Similarly, prevalence of depression may be underestimated by the GDS, which minimizes somatic symptoms of depression that may be confounded between depression and medical conditions common in older ages.
PERSPECTIVES COMPETENCY IN MEDICAL KNOWLEDGE: Among hospitalized patients with acute decompensated heart failure (ADHF), 98% met at least 1 of the Fried criteria of frailty and 50% met full criteria for frailty. These findings demonstrate the impor-
CONCLUSIONS
tance of frailty for functional and patient-reported outcomes,
Of the older hospitalized patients with ADHF, 98% met criteria for frailty or were pre-frail. In this population, frailty is independently associated with worse physical performance across all domains, lower quality-of-life, and higher burden of depression. Importantly, frailty can be quickly and efficiently identified in older patients with ADHF by a simplified screening tool that incorporates assessment of gait speed using a 4-m walk test and self-reported physical activity. Identification of frailty status in older patients with ADHF may help enhance care in this
identify risk factors for frailty specific to older patients with ADHF, and suggest a potential method for simplified, practical assessment of frailty that can be easily incorporated in clinical management of this high-risk patient population. TRANSLATIONAL OUTLOOK: Future studies are needed to confirm the novel, efficient methods to identify frailty in this population, and to prospectively evaluate how routine frailty assessment in patients with ADHF may help guide tailored approaches to the management of ADHF and to improve clinical outcomes.
high-risk population.
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KEY WORDS acute heart failure, aging, frailty, functional status, quality of life A PPE NDI X For supplemental tables, please see the online version of this paper.