Frailty Among Older Decompensated Heart Failure Patients

Frailty Among Older Decompensated Heart Failure Patients

JACC: HEART FAILURE VOL. 7, NO. 12, 2019 ª 2019 BY THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION PUBLISHED BY ELSEVIER Frailty Among Older Decompen...

305KB Sizes 0 Downloads 105 Views

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

1080

Pandey et al.

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

1081

1082

Pandey et al.

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.

1083

1084

Pandey et al.

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.

1086

Pandey et al.

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.

REFERENCES 1. Afilalo J, Alexander KP, Mack MJ, et al. Frailty assessment in the cardiovascular care of older adults. J Am Coll Cardiol 2014;63:747–62. 2. Vidan MT, Blaya-Novakova V, Sanchez E, Ortiz J, Serra-Rexach JA, Bueno H. Prevalence and prognostic impact of frailty and its components in non-dependent elderly patients with heart failure. Eur J Heart Fail 2016;18:869–75. 3. Yang X, Lupon J, Vidan MT, et al. Impact of frailty on mortality and hospitalization in chronic heart failure: a systematic review and meta-analysis. J Am Heart Assoc 2018;7:e008251. 4. U.S. Food and Drug Administration. Treatment for Heart Failure: Endpoints for Drug Development Guidance for Industry. June 2019. Available at: https://www.fda.gov/regulatory-information/searchfda-guidance-documents/treatment-heart-failureendpoints-drug-development-guidance-industry. Accessed October 22, 2019.

the geriatric patient: present and future. J Am Coll Cardiol 2018;71:1921–36. 8. Warraich HJ, Kitzman DW, Whellan DJ, et al. Physical function, frailty, cognition, depression, and quality of life in hospitalized adults >/¼ 60 years with acute decompensated heart failure with preserved versus reduced ejection fraction. Circ Heart Fail 2018;11:e005254. 9. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146–56.

15. Krumholz HM. Post-hospital syndrome–an acquired, transient condition of generalized risk. N Engl J Med 2013;368:100–2. 16. Sanders NA, Supiano MA, Lewis EF, et al. The frailty syndrome and outcomes in the TOPCAT trial. Eur J Heart Fail 2018;20:1570–7. 17. Gill TM, Allore HG, Holford TR, Guo Z. Hospitalization, restricted activity, and the development of disability among older persons. JAMA 2004; 292:2115–24.

10. McNallan SM, Chamberlain AM, Gerber Y, et al. Measuring frailty in heart failure: a community perspective. Am Heart J 2013;166:768–74.

18. Dunlay SM, Park SJ, Joyce LD, et al. Frailty and outcomes after implantation of left ventricular assist device as destination therapy. J Heart Lung Transplant 2014;33:359–65.

11. McNallan SM, Singh M, Chamberlain AM, et al. Frailty and healthcare utilization among patients

19. Ather S, Chan W, Bozkurt B, et al. Impact of noncardiac comorbidities on morbidity and mor-

with heart failure in the community. J Am Coll Cardiol HF 2013;1:135–41.

tality in a predominantly male population with heart failure and preserved versus reduced ejection fraction. J Am Coll Cardiol 2012;59: 998–1005.

5:359–66.

12. Guralnik JM, Ferrucci L, Pieper CF, et al. Lower extremity function and subsequent disability: consistency across studies, predictive models, and value of gait speed alone compared with the short physical performance battery. J Gerontol A Biol Sci Med Sci 2000;55:M221–31.

6. Reeves GR, Whellan DJ, Duncan P, et al.

13. Fritz S, Lusardi M. White paper: walking speed: the

21. Shah KS, Xu H, Matsouaka RA, et al. Heart

Rehabilitation Therapy in Older Acute Heart Failure Patients (REHAB-HF) trial: design and rationale. Am Heart J 2017;185:130–9.

sixth vital sign. J Geriatr Phys Ther 2009;32:46–9.

failure with preserved, borderline, and reduced ejection fraction: 5-year outcomes. J Am Coll Cardiol 2017;70:2476–86.

5. Reeves GR, Whellan DJ, O’Connor CM, et al. A novel rehabilitation intervention for older patients with acute decompensated heart failure: the REHAB-HF pilot study. J Am Coll Cardiol HF 2017;

7. Gorodeski EZ, Goyal P, Hummel SL, et al. Domain management approach to heart failure in

14. Hornsby WE, Sareini MA, Golbus JR, et al. Lower extremity function is independently associated with hospitalization burden in heart failure with preserved ejection fraction. J Card Fail 2019;25:2–9.

20. Dunlay SM, Redfield MM, Weston SA, et al. Hospitalizations after heart failure diagnosis a community perspective. J Am Coll Cardiol 2009; 54:1695–702.

22. Mentz RJ, Kelly JP, von Lueder TG, et al. Noncardiac comorbidities in heart failure with

1087

1088

Pandey et al.

JACC: HEART FAILURE VOL. 7, NO. 12, 2019 DECEMBER 2019:1079–88

Frailty in Older Patients With ADHF

reduced versus preserved ejection fraction. J Am Coll Cardiol 2014;64:2281–93. 23. Jha SR, Hannu MK, Chang S, et al. The prevalence and prognostic significance of frailty in patients with advanced heart failure referred for heart transplantation. Transplantation 2016;100: 429–36. 24. Joseph SM, Manghelli JL, Vader JM, et al. Prospective assessment of frailty using the fried

criteria in patients undergoing left ventricular assist device therapy. Am J Cardiol 2017;120: 1349–54. 25. Joyce E, Howell EH, Senapati A, Starling RC, Gorodeski EZ. Prospective assessment of combined handgrip strength and Mini-Cog identifies hospitalized heart failure patients at increased post-hospitalization risk. ESC Heart Fail 2018;5: 948–52.

26. Studenski S, Perera S, Patel K, et al. Gait speed and survival in older adults. JAMA 2011;305:50–8.

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.