Prevalence and Prognostic Implications of Longitudinal Ejection Fraction Change in Heart Failure

JACC: HEART FAILURE

VOL.

-, NO. -, 2019

ª 2018 PUBLISHED BY ELSEVIER ON BEHALF OF THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION

Prevalence and Prognostic Implications of Longitudinal Ejection Fraction Change in Heart Failure Gianluigi Savarese, MD, PHD,a,* Ola Vedin, MD, PHD,b,c,* Domenico D’Amario, MD, PHD,d Alicia Uijl, MD, PHD,a,e Ulf Dahlström, MD, PHD,f Giuseppe Rosano, MD, PHD,g Carolyn S.P. Lam, MD, PHD,h Lars H. Lund, MD, PHDa

ABSTRACT OBJECTIVES This study sought to evaluate the incidence, the predictors, and the associations with outcomes of changes in ejection fraction (EF) in heart failure (HF) patients. BACKGROUND EF determines therapy in HF, but information is scarce about incidence, determinants, and prognostic implications of EF change over time. METHODS Patients with $2 EF measurements were made in the Swedish Heart Failure Registry were categorized as heart failure with preserved ejection fraction (HFpEF) (EF $50%), heart failure with midrange ejection fraction (HFmrEF) (EF 40% to 49%), or heart failure with reduced ejection fraction (HFrEF) (EF <40%). Changes among categories were recorded, and associations among EF changes, predictors, and all-cause mortality and/or HF hospitalizations were analyzed using logistic and Cox regressions. RESULTS Of 4,942 patients at baseline, 18% had HFpEF, 19% had HFmrEF, and 63% had HFrEF. During follow-up, 21% and 18% of HFpEF patients transitioned to HFmrEF and HFrEF, respectively; 37% and 25% of HFmrEF patients transitioned to HFrEF and HFpEF, respectively; and 16% and 10% of HFrEF patients transitioned to HFmrEF and HFpEF, respectively. Predictors of increased EF included use of angiotensin-converting enzyme inhibitors and angiotensin receptor blockers, female sex, cases of less severe HF, and comorbidities. Predictors of decreased EF included diabetes, ischemic heart disease, and cases of more severe HF. Increased EF was associated with a lower risk (hazard ratio [HR]: 0.62; 95% confidence interval [CI]: 0.55 to 0.69) and decreased EF with a higher risk (HR: 1.15; 95% CI: 1.01 to 1.30) of mortality and/or HF hospitalizations. Prognostic implications were most evident for transitions to and from HFrEF. CONCLUSIONS Increases in EF increase occurred in one-fourth of HFrEF and HFmrEF patients, and decreases occurred in more than one-third of patients with HFpEF and HFmrEF. EF change was associated with a wide range of important clinical, treatment, and organizational factors as well as with outcomes, particularly transitions to and from HFrEF. (J Am Coll Cardiol HF 2019;-:-–-) © 2018 Published by Elsevier on behalf of the American College of Cardiology Foundation.

From the aDepartment of Medicine, Karolinska Institutet and Department of Cardiology, Karolinska University Hospital, Stockholm, Sweden; bDepartment of Medical Sciences, Uppsala University and Uppsala Clinical Research Center, Uppsala, Sweden; c

Boehringer Ingelheim AB, Stockholm, Sweden; dInstitute of Cardiology, Fondazione Policlinico Universitario A. Gemelli Institute

of Scientific Research and Treatment, Università Cattolica del Sacro Cuore, Rome, Italy; eJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; fDepartment of Cardiology and Department of Medical and Health Sciences, Linkoping University, Linkoping, Sweden; gDepartment of Medical Sciences, IRCCS San Raffaele Hospital, Rome, Italy; and the hNational Heart Centre Singapore, Duke-NUS Medical School, and University Medical Centre Groningen, Groningen, the Netherlands. *Drs. Savarese and Vedin are joint first authors. Supported by grants 2013-23897104604-23 and 523-2014-2336 to Karolinska Institutet from the Swedish Research Council, grants 20120321 and 20150557 from the Swedish Heart Lung Foundation, and grant 20110120 from the Stockholm County Council. No funding agency had any role in the design or conduct of the study, or collection, management, analysis, or interpretation of the data, or in the preparation or approval of the manuscript. Dr. Savarese has received honoraria from Vifor, AstraZeneca, Roche, and Servier; and has received grants from Boehringer Ingelheim, and Merck Sharp & Dohme. Dr. Lam is a paid consultant for National Heart Centre, National Medical Research Council of Singapore, Abbott Diagnostics, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific, Coarvia, Janssen Research & Development LLC, Medtronics, Menarini, Merck Sharpe & Dohme,

ISSN 2213-1779/$36.00

https://doi.org/10.1016/j.jchf.2018.11.019

2

Savarese et al.

JACC: HEART FAILURE VOL.

H

ABBREVIATIONS

-, NO. -, 2019 - 2019:-–-

Ejection Fraction Change in Heart Failure

eart failure (HF) phenotyping and

inclusion criterion was the clinician judged the pa-

treatment

pro-

tient had HF. Approximately 80 variables were

foundly on the assessment of ejec-

entered at hospital discharge or after an outpatient

tion fraction (EF), categorizing patients as

clinic visit to complete the Internet-based case report

having heart failure with reduced ejection

form. The Uppsala Clinical Research Center (Uppsala,

blocker

fraction (HFrEF) (EF <40%), heart failure

Sweden) manages the database. The prevalence of HF

EF = ejection fraction

with midrange ejection fraction (HFmrEF)

in the SwedeHF study was 54% (15), but the first HF

(EF 40% to 49%), or heart failure with pre-

onset incidence was only 10% (16).

AND ACRONYMS ACE = angiotensin-converting enzyme

ARB = angiotensin receptor

HF = heart failure

decisions

rely

served ejection fraction (HFpEF) (EF $50%)

The Swedish Board of Health and Welfare admin-

midrange ejection fraction

(1). In addition, EF is not only a marker of

isters the Population Registry that provided date of

HFmrEF = heart failure with

HFpEF = heart failure with

cardiac function but also retains indepen-

death, and the Patient Registry that supplied baseline

preserved ejection fraction

dent prognostic information (2). Thus, EF

comorbidities, beyond those available in the Swe-

HFrEF = heart failure with

has become a fundamental part of daily clin-

deHF cohort, and the outcome HF hospitalization

reduced ejection fraction

ical protocol and an inclusion criterion and

were defined according to International Statistical

surrogate endpoint in trials (1,3).

Classification of Diseases and Related Health Prob-

For purposes of diagnosis, prognostication, and

lems (revision 10) (ICD-10) codes in the first position.

treatment assignment, a baseline EF assessment is

ICD-10 coding has been validated in Sweden. The

mandatory in every HF patient (1,2). However, EF is

positive predictive value for most diagnoses is 85% to

not a static measurement but may increase or

95% (17). Diagnosis of HF was verified in 86% to 91%

decrease over time (4–6), warranting renewed classi-

of cases (18).

fication and prognostic evaluation. Furthermore, in-

Socioeconomic data were provided by Statistics

dications for HF therapy may arise with deteriorating

Sweden SCB (Stockholm, Sweden). All permanent

EF, whereas data for benefits and risks of continua-

residents of Sweden, regardless of citizenship, have

tion versus withdrawal of therapy with improving EF

unique personal identification numbers that allow

are lacking. Given these important implications,

linking of disease-specific health registries and

comprehensive assessments of changes in EF in large

governmental health and statistical registries.

HF

populations

most

Establishment of the HF registry and this analysis

contemporary studies focus solely on recovery of

with linking of the above registries were approved by

EF (7–13) and do not evaluate the whole spectrum of

a multisite ethics committee. Individual patient con-

EF

sent was not required, but patients were informed of

change

are

across

warranted.

all

EF

However,

categories,

including

determinants of change and associated prognosis.

entry into national registries and allowed to opt out.

The current study was undertaken, therefore, to

In the current study, patients with at least

assess: 1) the incidence and type of EF change (in-

2 consecutive EF assessments were enrolled. When

crease or decrease); 2) the predictors associated with

the same patient reported more than 2 EF assess-

different types of EF change; and 3) the prognostic

ments, the first and last assessments were considered

implications of different types of EF change in the

in order to calculate the change in EF. EF data were

large contemporary and unselected SwedeHF (Swed-

collected, categorized, and defined as HFpEF $50%,

ish Heart Failure) study population.

HFmrEF 40% to 49%, and HFrEF <40%. Transitions from HFpEF to HFmrEF, HFpEF to HFrEF, and

METHODS

HFmrEF to HFrEF were pooled and defined as EF decrease. Transitions from HFrEF to HFmrEF, HFrEF

STUDY PROTOCOL AND SETTING. The SwedeHF

to HFpEF, and HFmrEF to HFpEF were pooled and

study was described previously (14). The only

defined as EF increase. The absence of any changes

Novartis, Stealth BioTherapeutics, and Vifor Pharma; has received grants from National Medical Research Council of Singapore, Boston Scientific, Bayer, Roche Diagnostic, Medtronics, and Vifor Pharma; and is a paid adviser for Roche Diagnostic, AstraZeneca, Movartis, Amgen, Boehringer Ingelheim, and Abbott Diagnostics. Dr. Lund is a consultant for and has received grants from AstraZeneca, Boehringer Ingelheim, Relypsa, Novartis, and Vifor Pharma; a consultant for Sanofi and Bayer; and has received speaker honoraria from Abbott, Novartis, and Vifor Pharma. Dr. Vedin is an employee of Boehringer Ingelheim; and is a paid consultant for and has received speaker fees from Alnylam, Boehringer Ingelheim, Fresenius Medicare, Merck Sharpe & Dohme, Novartis, Orion Pharma, and Servier. Dr. Dahlström has received a research grant from AstraZeneca; and has received consulting and speaker fees from AstraZeneca and Novartis. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose. Manuscript received November 10, 2018; revised manuscript received November 17, 2018, accepted November 26, 2018.

JACC: HEART FAILURE VOL.

-, NO. -, 2019

Ejection Fraction Change in Heart Failure

among EF groups was defined as stable EF. Primary outcome of the analysis was a composite of all-cause

T A B L E 1 Baseline Characteristics

EF Increases (n ¼ 1,027) (21%)

No Changes in EF (n ¼ 3,226) (65%)

EF Decreases (n ¼ 689) (14%)

Male

687 (67)

2,283 (71)

433 (63)

Female

340 (33)

943 (29)

256 (37)

67 (13)

70 (12)

74 (10)

Internal medicine/geriatrics

537 (54)

1,469 (47)

305 (48)

Cardiology

466 (46)

1,627 (53)

334 (52)

Inpatient

418 (41)

1,762 (55)

427 (62)

Outpatient

609 (59)

1,464 (45)

262 (38)

Specialty care

830 (83)

2,364 (76)

415 (62)

Primary care/other

172 (17)

759 (24)

253 (38)

mortality and HF hospitalization. STATISTICAL

ANALYSIS. Baseline

characteristics.

Baseline characteristics of patients according to increasing, decreasing, or stable EF were compared test for continuous variables and by chi-square test for categorical variables. Missing data were managed

Age, yrs* Specialty*

method (n ¼ 20). Variables noted in Table 1 were for

the

imputation

procedure.

All

formed using imputed data.

logistic

regression

models

were

applied,

including EF increase or decrease as a dependent

<0.001

<0.001

Follow-up referral specialty*

dent predictors of EF increase or decrease, multivar-

<0.001

Follow-up referral to outpatient HF nurse clinic*

variable, all the variables reported in Table 1 and

No

377 (38)

1,588 (51)

450 (68)

Online Tables 1 and 2 as covariates with the addition

Yes

621 (62)

1,520 (49)

216 (32)

0 (0)

539 (17)

344 (50)

of HF type at baseline, the time between EF measurements, and the year of registration. Because

<0.001 0.003

Caregiver*

analyses, except for descriptive statistics, were perP r e d i c t o r s o f E F c h a n g e s . To assess the indepen-

<0.001

Sex*

by multiple imputation, using the chained equations considered

p Value

Demographics and organization

by using Student’s t-test or Wilcoxon-Mann-Whitney

iate

3

Savarese et al.

- 2019:-–-

Clinical <0.001

HF type* HFpEF

predictors of EF increase or decrease were mostly

HFmrEF

231 (22)

359 (11)

345 (50)

unknown and because the sample size was suffi-

HFrEF

796 (78)

2,328 (72)

0 (0) <0.001

ciently large, variables for the multivariate models

Duration of HF*

were not selected according to any stepwise variable

<6 months

633 (62)

1,450 (45)

293 (43)

>6 months

391 (38)

1,771 (55)

392 (57)

I

106 (13)

205 (9)

64 (14)

II

428 (52)

1,053 (44)

231 (50)

III

274 (33)

1,072 (45)

151 (33)

IV

11 (1)

73 (3)

15 (3)

28 (5)

27 (5)

28 (6)

0.076

128 (21)

125 (21)

132 (22)

<0.001

selection but rather included all variables from the SwedeHF study and the National Patient Registry and Statistics Sweden that were clinically relevant and that could potentially affect EF over time. Outcome

a n a l y s e s . Kaplan-Meier

curves

<0.001

NYHA functional class*

and

multivariate Cox regression models including the

BMI, kg/m2*

same covariates as in the multivariate logistic

Systolic BP, mm Hg

regression model were fitted to evaluate the associa-

Diastolic BP, mm Hg

75 (13)

73 (12)

73 (12)

<0.001

tion among EF changes (increase, decrease, or stable)

Arterial BP, mm Hg*

92 (14)

90 (13)

93 (13)

<0.001

Heart rate, beats/min*

74 (16)

73 (15)

73 (14)

0.31

and outcomes. The index date was defined as the date

Continued on the next page

of the follow-up EF assessment. The end of follow-up was December 31, 2012. The same models were

[interquartile range (IQR): 0.5 to 3.0 years), and

applied including EF changes categorized as pEF to

follow-up was $1 day. Overall, 1,027 patients (21%)

pEF, pEF to mrEF, pEF to rEF, mrEF to pEF, mrEF to

reported increased EF; 689 (14%) reported decreased

mrEF, mrEF to rEF, rEF to pEF, rEF to mrEF, and rEF

EF; and 3,226 (65%) reported unchanged EF. Specif-

to rEF.

ically, 21% and 18% of baseline HFpEF patients tran-

Statistical analyses were performed by using Stata

sitioned to HFmrEF and HFrEF, respectively; 37% and

version 14.2 software (StataCorp, College Station,

25% of baseline HFmrEF patients transitioned to

Texas). A p value <0.05 was considered statistically

HFrEF and HFpEF, respectively; and 16% and 10% of

significant.

baseline HFrEF patients transitioned to HFmrEF and

RESULTS

HFpEF, respectively (Figure 1). BASELINE CHARACTERISTICS BY EF PATTERN OF

SAMPLE SIZE AND EF CHANGE PATTERNS. Between

CHANGE. In the overall population, the mean age

May 11, 2000, and December 31, 2012, 51,060 patients

was 72  12 years of age, 31% were female, 18% had

were

HFpEF, 19% had HFmrEF, and 63% had HFrEF. Table 1

included.

Of

these,

4,942

patients

had

undergone at least 2 consecutive EF assessments

lists

(median time between EF assessments was 1.4 years

decrease, or no change in EF. Those patients with

characteristics

according

to

an

increase,

Savarese et al.

4

JACC: HEART FAILURE VOL.

-, NO. -, 2019 - 2019:-–-

Ejection Fraction Change in Heart Failure

decreasing EF were among the oldest. Patients with

T A B L E 1 Continued

decreasing EF had lower estimated glomerular filtraEF Increases (n ¼ 1,027) (21%)

No Changes in EF (n ¼ 3,226) (65%)

EF Decreases (n ¼ 689) (14%)

p Value

eGFR, ml/min per 1.73 m2*

69 (23)

63 (22)

59 (22)

<0.001

duration. Patients with increasing EF had fewer

Hemoglobin, g/l

136 (18)

134 (17)

130 (17)

<0.001

comorbidities (e.g., hypertension, diabetes, ischemic

1,890 (904–3,908)

2,695 (1,280–5,642)

2,650 <0.001 (1,274–4,463)

heart disease) than those with stable or decreasing

<0.001

more likely to receive specialized rather than primary

tion rates and hemoglobin levels, whereas those with

NT-proBNP, pg/ml* Treatments ACE inhibitor or ARB* No

97 (9)

321 (10)

121 (18)

Yes

926 (91)

2,896 (90)

564 (82)

Mineralocorticoid receptor antagonist* 678 (66)

2,050 (64)

472 (69)

Yes

346 (34)

1,165 (36)

211 (31)

Digoxin* 832 (81)

2,676 (83)

576 (84)

Yes

192 (19)

539 (17)

110 (16)

No

246 (24)

569 (18)

92 (13)

Yes

779 (76)

2,648 (82)

595 (87)

hibitors and angiotensin receptor blockers (ACE

No

909 (89)

2,676 (83)

563 (82)

Yes

116 (11)

535 (17)

124 (18)

EF increased or did not change, whereas diuretics

No

587 (57)

1,569 (49)

336 (49)

Yes

436 (43)

1,646 (51)

351 (51)

Oral anticoagulant* 571 (56)

1,828 (57)

395 (57)

Yes

454 (44)

1,384 (43)

293 (43)

No

556 (54)

1,464 (46)

311 (45)

Yes

468 (46)

1,750 (54)

376 (55)

Beta-blocker* 117 (11)

379 (12)

104 (15)

Yes

907 (89)

2,842 (88)

582 (85)

differences in Table 1 are unadjusted. Adjusted odds multivariate logistic regression are shown in Figure 2.

duration (<6 vs. >6 months); absence of ischemic heart disease and coronary revascularization; lower New York Heart Association functional classes (I to II vs. III to IV); lower NT-proBNP levels; higher estimated glomerular filtration rates; higher mean arte-

<0.001

HF device*

PREDICTORS OF EF INCREASE AND DECREASE. The

included no use of ACE inhibitors/ARBs; shorter HF

0.034

No

was highest in those with stable EF.

Variables independently associated with increased EF <0.001

Statin*

therapy and implantable cardioverter defibrillator

ratios (ORs) for EF increase and decrease after 0.74

No

were more likely to be used in patients with worsening EF, and use of cardiac resynchronization

<0.001

Platelet inhibitor*

inhibitor/ARB), beta-blockers, and mineralocorticoid receptor blockers was highest among patients whose

<0.001

Nitrate*

to have the highest education level and annual income. Use of angiotensin-converting enzyme in-

<0.001

Diuretic*

CRT/ICD

clinic follow-up, to be married or cohabitating, and

0.25

No

EF. Additionally, patients with increasing EF were care follow-up, to receive scheduled HF nurse-led

0.019

No

None

increasing EF had lower N-terminal pro–B-type natriuretic peptide (NT-proBNP) and shorter HF

Laboratory values

rial pressures; higher body mass indexes; being

979 (96)

2,995 (93)

671 (98)

married or cohabitating versus living alone; history of

42 (4)

214 (7)

15 (2)

hypertension; higher income; history of anemia;

Comorbidities

planned follow-up in an HF nurse-led clinic; history

Smoking*

0.28

Never

354 (41)

1,060 (40)

241 (43)

Previous

383 (44)

1,213 (46)

252 (45)

Current

127 (15)

390 (15)

64 (11)

No

467 (45)

1,404 (44)

230 (33)

Yes

560 (55)

1,822 (56)

459 (67)

pulmonary disease; being an outpatient versus an inpatient; and female sex. On the other hand, vari<0.001

Hypertension*

No

791 (77)

2,204 (68)

427 (62)

Yes

236 (23)

1,022 (32)

262 (38)

an outpatient; male sex; no history of anemia; no

No

538 (56)

1,237 (40)

260 (38)

Yes

426 (44)

1,889 (60)

418 (62)

No

774 (75)

1,996 (62)

Yes

253 (25)

1,230 (38)

disease and diabetes. Variables not associated with EF increase or decrease (including beta-blocker and cardiac resynchronization therapy) are reported in

<0.001

Coronary revascularization*

planned follow-up in an HF nurse-led clinic; higher NT-proBNP levels; and a history of ischemic heart

<0.001

Ischemic heart disease*

ables predicting a decrease in EF included no history of peripheral artery disease; being an inpatient versus

<0.001

Diabetes*

of atrial fibrillation; history of chronic obstructive

Online Tables 1 and 2.

420 (61) 269 (39) Continued on the next page

OUTCOME ANALYSIS. Unadjusted event rates for the

composite outcome were 18.0 (95% confidence

JACC: HEART FAILURE VOL.

-, NO. -, 2019

Ejection Fraction Change in Heart Failure

interval [CI]: 16.2 to 19.9) per 100 patient-years in those who experienced an increase in EF, 43.1

T A B L E 1 Continued

EF Increases (n ¼ 1,027) (21%)

(95% CI: 41.2 to 45.1) per 100 patient-years in those who showed no change in EF, and 57.8 (95% CI: 52.6 to

63.4)

per

5

Savarese et al.

- 2019:-–-

100

patient-years

in

those

with

No Changes in EF (n ¼ 3,226) (65%)

EF Decreases (n ¼ 689) (14%)

decreasing EF (log-rank p < 0.0001). After adjust-

No

965 (94)

2,869 (89)

622 (90)

ments, compared with stable EF, an increase in EF

Yes

62 (6)

357 (11)

67 (10)

No

914 (89)

2,762 (86)

557 (81)

Yes

113 (11)

464 (14)

132 (19)

No

499 (49)

1,573 (49)

250 (36)

Yes

528 (51)

1,653 (51)

439 (64)

No

741 (72)

2,168 (67)

429 (62)

Yes

286 (28)

1,058 (33)

259 (38)

No

767 (76)

2,312 (73)

464 (68)

Yes

237 (24)

855 (27)

215 (32)

was associated with statistically significant reduced 0.62; 95% CI: 0.55 to 0.69), whereas a decrease in EF was associated with an increase in risk (HR: 1.15; 95%

Atrial fibrillation*

CI: 1.01 to 1.30) (Figure 3). Event rates for all types of transitions are shown in ence, HRs for all types of transition were calculated,

to stable HFmrEF (HR: 0.73; 95% CI: 0.62 to 0.85) and

<0.001

Valvular intervention*

from HFrEF to HFmrEF (HR: 0.55; 95% CI: 0.47 to 0.64) or to HFpEF (HR: 0.42; 95% CI: 0.33 to 0.53) or

<0.001

Anemia*

Table 2. Additionally, using stable HFrEF as refershowing improved outcomes only for the transition

<0.001

Stroke or TIA*

risk of the composite outcome (hazard ratio [HR]:

0.001

Chronic obstructive pulmonary disease or bronchitis*

0.27

were associated with improved outcome, whereas all

No

842 (82)

2,650 (82)

548 (80)

other transitions in EF were not (Table 2).

Yes

185 (18)

576 (18)

141 (20)

No

916 (89)

2,859 (89)

585 (85)

Yes

111 (11)

367 (11)

104 (15)

Living alone

452 (44)

1,526 (47)

346 (50)

Married or cohabitating

574 (56)

1,693 (53)

342 (50)

The effects of change from and to each EF category

Cancer in the last 3 yrs*

were also assessed, using no change as the reference. Compared with stable HFpEF, downward transition from HFpEF to HFrEF but not to HFmrEF was asso-

0.013

Socioeconomic Family type*

ciated with harm, whereas transitions to HFpEF from HFrEF but not from HFmrEF were associated with benefit (Figures 1, 4A, and 4D). Compared with stable

0.034

Education*

0.011

HFmrEF, both transitions from HFmrEF to HFpEF and

Compulsory school

432 (43)

1,487 (47)

332 (49)

to HFrEF were associated with increased risk,

Secondary school

399 (39)

1,249 (39)

247 (36)

University

184 (18)

454 (14)

102 (15)

Below median

424 (42)

1,655 (52)

378 (55)

Above or equal to median

597 (58)

1,556 (48)

310 (45)

whereas transitions to HFmrEF from HFpEF were associated with increased risk and from HFrEF a

<0.001

Income*

decreased risk (Figures 1, 4B, and 4E). Compared with stable HFrEF, both transitions from HFrEF to HFmrEF

Number of children*

0.63

and to HFpEF were associated with a reduced risk,

#2

718 (70)

2,238 (69)

467 (68)

whereas transition to HFrEF from HFpEF but not from

>2

309 (30)

988 (31)

222 (32)

HFmrEF was associated with increased risk (Figures 1, 4C, and 4F). COMPARISON WITH PREVIOUS STUDIES. The fea-

tures and findings from the present study in relation to those from previous studies of EF changes and EF recoveries are presented in Online Table 3.

DISCUSSION

p Value

<0.001

Peripheral artery disease*

Values are n (%), mean  SD, or median (interquartile range). *These variables were included in the multiple imputation model together with the primary outcome, the time between the 2 EF assessments, and the year of registration. ACE ¼ angiotensin-converting enzyme; ARB ¼ angiotensin receptor blocker; BMI ¼ body mass index; CRT ¼ cardiac resynchronization therapy; eGFR ¼ estimated glomerular filtration rate; HF ¼ heart failure; HFmrEF ¼ heart failure with midrange ejection fraction; HFpEF ¼ heart failure with preserved ejection fraction; HFrEF ¼ heart failure with reduced ejection fraction; ICD ¼ implantable cardioverter defibrillator; NT-proBNP ¼ N-terminal pro–B-type natriuretic peptide; NYHA ¼ New York Heart Association; TIA ¼ transient ischemic attack.

concomitant diabetes and ischemic heart disease,

In this large, contemporary and unselected HF cohort,

lack

EF change over time was a common occurrence across

NT-proBNP levels. Overall, increased EF was associ-

of

specialized

HF

follow-up,

and

higher

all EF groups. Important factors associated with

ated with a more favorable outcome, whereas

increasing EF included use of ACE inhibitors/ARBs,

decreased EF portended a poor prognosis. The prog-

female sex, indicators of less severe HF, specialized

nostic differences were most evident for transitions

HF follow-up, absence of ischemic heart disease but

to and from HFrEF.

presence of several other modifiable comorbidities

EF CHANGE IS A COMMON OCCURRENCE. Although

(e.g., anemia and atrial fibrillation), and preserved

an initial EF assessment remains a fundamental tool

renal function. Predictors of decreasing EF included

with which to define, prognosticate, and guide

6

Savarese et al.

JACC: HEART FAILURE VOL.

-, NO. -, 2019 - 2019:-–-

Ejection Fraction Change in Heart Failure

F I G U R E 1 Proportions of and Risks Associated With EF Changes Over Time by Baseline EF Category

Each bar segment shows the proportion (%) of patients with changes and the associated hazard ratios (95% CI) for the primary outcome, with stable EFs in each category as references. EF ¼ ejection fraction; HFmrEF ¼ heart failure with midrange ejection fraction; HFpEF ¼ heart failure with preserved ejection fraction; HFrEF ¼ heart failure with reduced ejection fraction.

treatment in HF, the implications of longitudinal EF

and downward EF transition in HFpEF was conse-

change are becoming increasingly recognized. How-

quently observed in approximately 10% of patients.

ever, the extent to which EF assessment occurs in

Thus, selection bias likely exaggerated the high

real-world HF populations remains insufficiently

proportion of transition from HFpEF, and although it

covered, and hitherto published reports have almost

might not have constituted a static HF entity in

exclusively focused on EF improvement in HFrEF.

some, downward transition is in reality probably less

In the SwedeHF cohort, changes to and from all EF

common than observed here. The two-thirds of all

categories were assessed, and it was observed that

HFmrEF patients who transitioned either to HFrEF

approximately 25% of patients with HFrEF at base-

(37% of patients) or to HFpEF (25% of patients)

line transitioned to a higher category and that 10%

partly supports the hypothesis that HFmrEF repre-

of patients showed complete recovery. The pro-

sents a transitional state (6,19). Although such a high

portions of patients with EF improvement in HFrEF

proportion of transition may partly result from the

in the present study are either similar to (7,13) but

intermediate and narrow 40% to 49% EF interval

mostly lower than (6,8–10) those in previous reports,

and interexamination variability, it could also indi-

possibly reflecting an older population and more

cate a multitude of phenotypes with various back-

severe HF syndrome and comorbidities, all of which

ground factors and disease severity contained in the

may contribute to a lower potential for improve-

HFmrEF category, which may in turn warrant more

ment. Surprisingly, 39% of HFpEF patients transi-

careful

tioned to lower EF categories, a finding almost

because

identical that from the study by Dunlay et al. (4),

HFpEF, particularly regarding ischemic causes and

where similar to the present study, echocardiograms

risk of incident ischemic events (5,20), transition

were performed at the clinician’s discretion, pre-

from HFmrEF to HFpEF may reflect recovery after

sumably often following episodes of deterioration.

myocardial infarction, whereas downward transition

However, in a study by Tsuji et al. (6), echocardi-

to HFrEF may indicate progressive HF or a new

ography was performed at pre-specified time points,

ischemic event, unlike EF deterioration from HFpEF.

assessment HFmrEF

and

monitoring.

resembles

HFrEF

Moreover, more

than

JACC: HEART FAILURE VOL.

-, NO. -, 2019

- 2019:-–-

Savarese et al. Ejection Fraction Change in Heart Failure

F I G U R E 2 Predictors of EF Increases and Decreases

ACEI ¼ angiotensin-converting enzyme inhibitor; ARB ¼ angiotensin receptor blocker; BMI ¼ body mass index; COPD ¼ chronic obstructive pulmonary disease; EF ¼ ejection fraction; eGFR ¼ estimated glomerular filtration rate; FUP ¼ follow-up; HF ¼ heart failure; MAP ¼ mean arterial pressure; NT-proBNP ¼ N-terminal pro–B-type natriuretic peptide; NYHA ¼ New York Heart Association; OR ¼ odds ratio.

Continued on the next page

7

8

Savarese et al.

JACC: HEART FAILURE VOL.

-, NO. -, 2019 - 2019:-–-

Ejection Fraction Change in Heart Failure

F I G U R E 2 Continued

PREDICTORS OF EF INCREASE AND DECREASE.

of EF increase, which could be explained by previous

Predictors of increases in EF included characteristics

data showing that treatment of anemia can lead to EF

linked to less severe HF, fewer co-morbidities, and

improvement (25). Atrial fibrillation was also associ-

shorter HF duration, the last characteristic possibly

ated with improved EF. One explanation for that may

indicating patients in whom HF treatments were

be residual confounding from temporal variations in

recently initiated, with less remodeling and thus a

EF resulting from paroxysmal atrial fibrillation at the

greater

those

baseline measurement or successful rate or rhythm

predictors, including female sex, nonischemic cause,

control achieved in patients with persistent atrial

higher blood pressure, and shorter HF duration

fibrillation at the follow-up measurement. Notably,

have been reported previously in smaller populations

the present authors observed that ACE inhibitors/ARB

(21–23). Female sex was associated with both an in-

therapy were a major determinant of EF increase,

potential

for

recovery.

Some

of

crease in EF and less likelihood of decrease. This as-

consistent with the beneficial effects of these drugs

sociation is concordant with findings from both

on left ventricular remodeling and on hard outcomes

animal and human studies reporting less remodeling

shown in previous studies (26). Surprisingly, therapy

and left ventricular dilation as a result of volume and

with beta-blockers or mineralocorticoid receptor an-

pressure overload, less severe necrosis and apoptosis

tagonists did not predict EF improvement, in contrast

following ischemia, and enhanced infarct healing and

to several previously published analyses (4,26–29).

myocardial recovery in females compared to that in

However, understanding the impact of medications in

males. Indeed, the observed less-prominent adverse

real-world settings is difficult due to confounding by

remodeling could constitute an important determi-

indication and reverse causation. The absent associ-

nant of the improved prognosis observed among

ations may also be explained by the very high use of

women with HF compared to men with HF (24). Our

beta-blockers (z90%) or the very low use of miner-

analysis found concomitant anemia to be a predictor

alocorticoid receptor antagonists (z30%), which may

JACC: HEART FAILURE VOL.

-, NO. -, 2019

Savarese et al.

- 2019:-–-

Ejection Fraction Change in Heart Failure

F I G U R E 3 Risk of All-Cause Mortality or HF Hospitalization Related to EF Changes for the Whole Study Population

Abbreviations as in Figure 2.

result in insufficient discrimination. Finally, it is of

inpatient versus an outpatient. Notably, an important

course also plausible that these drugs are ineffective

predictor was history of ischemic heart disease,

in HFmrEF, although posthoc analysis from random-

confirming previous unadjusted findings from the

ized trials suggest that at least ARBs and possibly

SwedeHF study of more prevalent and incident

beta-blockers improve outcomes in HFmrEF but not

ischemic heart disease in patients with EF deteriora-

in HFpEF (20,29).

tion (5). Surprisingly however, the strongest predictor

Consistent with the associations observed between

of EF decrease was the absence of peripheral artery

factors representing a milder HF syndrome and

disease, which is difficult to explain other than as a

increasing EF, some of the variables associated with

chance finding. The central role of diabetes in

decreasing EF signified a more severe HF state,

HF once again receives confirmation in the present

including higher NT-proBNP levels and being an

study.

Interestingly,

although

the

association

between diabetes and HFrEF in previous studies has T A B L E 2 Event Rates for All-Cause Mortality and HF

Hospitalizations According to the Different Transitions in EF

HFpEF

determined

mainly

by

coexisting

persistent association indicates a more complex relationship. Furthermore, the potential contribution

and No Changes in EF From

been

ischemic heart disease, which was adjusted for, the

To HFpEF

To HFmrEF

To HFrEF

313/539 (58)

126/183 (69)

112/161 (70)

HFmrEF

117/231 (51)

175/359 (49)

209/345 (61)

HFrEF

77/310 (25)

174/486 (36)

1,399/2,328 (60)

of diabetes itself to HFpEF is becoming increasingly recognized (30). EF

CHANGES

AND

OUTCOMES. EF

change was

inversely associated with risk of adverse outcome, with the most prominent associations apparent for EF

Values are number of events/n (%). Abbreviations are as in Table 1.

increase, which resulted in a 39% lower risk of death or HF hospitalization. Although the unadjusted event

9

10

Savarese et al.

JACC: HEART FAILURE VOL.

-, NO. -, 2019 - 2019:-–-

Ejection Fraction Change in Heart Failure

F I G U R E 4 Risk of All-Cause Mortality and HF Hospitalizations Related to EF Change Patterns

From (A) HFpEF, (B) HFmrEF, and (C) HFrEF to (D) HFpEF, (E) HFmrEF, and (F) HFrEF. adj HR ¼ adjusted hazard ratio; HFpEF ¼ heart failure with preserved ejection fraction; HFmrEF ¼ heart failure with midrange ejection fraction; HFrEF ¼ heart failure with reduced ejection fraction.

rates in stable HFpEF were similar to those in stable

The prognostic implications of EF change between

HFrEF rates, patients with HFpEF and decreasing EF

HFmrEF and HFpEF were less evident. The absent or

had the highest unadjusted event rates, whereas

sometimes

HFrEF patients with increasing EF had the lowest

observed for EF change between HFmrEF and HFpEF

even

conflicting

risk

associations

rates, clearly acknowledging the clinical implications

could have resulted from the lower number of pa-

of EF change over time and also the prognostic

tients in these categories and/or by the lack of a linear

distinction between HF with recovered EF and HFpEF

relationship between EF and risk of outcomes in

(8,11–13).

higher EF segments, as shown in the CHARM (Can-

Little is known from published studies about the

desartan in heart failure—assessment of reduction in

prognostic impact of EF deterioration from HFmrEF

mortality and morbidity) study (2,20). With particular

and HFpEF. In the study by Dunlay et al. (4), a 7%

reference to the dubious prognostic power of EF in

increased adjusted mortality risk was observed for

the upper EF ranges, other more precise measure-

every 5% EF decrease among HFpEF patients (4), and

ment of cardiac function could possibly have more

although EF was categorized in the present study, the

future clinical potential. For instance, the use of

findings appear comparable. The most substantial

global longitudinal strain and global circumferential

impact of EF change, however, was evident in pa-

strain have proven their superiority compared with

tients transitioning to and from HFrEF, particularly in

EF in several settings (31,32), and implications of

those whose EF improved. Partial or complete re-

changes in these parameters over time, particularly

covery from HFrEF portended a significantly better

relating to prognostic accuracy in chronic HF, warrant

prognosis than static HFrEF, HFmrEF, and HFpEF,

further investigation.

indicating a more benign HF phenotype with revers-

STUDY

ible causes amenable to treatment and, in some cases,

study is subject to confounding. Indeed, although

perhaps alleviated altogether. Similarly, deterioration

extensive adjustments were performed, the authors

from HFpEF to HFrEF resulted in worse outcomes

cannot rule out potential residual confounding. The

than static HFrEF, possibly reflecting a more vulner-

follow-up EF measurement was not performed at pre-

able phase in the course of HF and more progressive

determined time points. Thus, patients with EF as-

disease with associated complications.

sessments within a short time period might have been

LIMITATIONS. The

present

observational

JACC: HEART FAILURE VOL.

-, NO. -, 2019

Savarese et al.

- 2019:-–-

Ejection Fraction Change in Heart Failure

less likely to exhibit a change in EF category. Although all multivariate models were adjusted for

ADDRESS FOR CORRESPONDENCE: Dr. Ola Vedin,

the time between EF assessments, residual con-

Uppsala Clinical Research Centre, Uppsala Science

founding might have been a limitation. Bias by indi-

Park, Dag Hammarskjölds väg 38, 751 85 Uppsala,

cation due to HF deterioration has been discussed

Sweden. E-mail: [email protected].

extensively earlier. Finally, inclusion criterion for the SwedeHF study was HR judged by a clinician, thus,

PERSPECTIVES

the fact that a few patients with HFpEF might not COMPETENCY IN MEDICAL KNOWLEDGE: The

have had HF cannot be ruled out.

findings from this nationwide HF registry population

CONCLUSIONS

indicate that assessment of change in EF adds important prognostic information, as opposed to

In this nationwide HF cohort, EF increase over time

single measurements. Moreover, EF change is a

occurred in one-fourth of patients with HFrEF and

common occurrence and is determined by several

HFmrEF, and a decrease occurred in more than one-

clinical and organizational factors, some of which are

third of those with HFpEF and HFmrEF. EF changes

modifiable.

were associated with a wide range of important clinical, treatment, and organizational factors. Changes

TRANSLATIONAL OUTLOOK: Further studies are

in EF were independently associated with outcomes,

warranted to elucidate mechanisms behind EF

particularly in patients transitioning to and from

change, particularly for EF deterioration from HFpEF. Moreover, a better understanding of the efficacy and

HFrEF. ACKNOWLEDGMENTS The authors thank all local

investigators and the patients who participated in the

safety of continued or withdrawn HF therapies is needed in patients with EF improvement.

SwedeHF study.

REFERENCES 1. Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the task force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) developed with the special contribution of. Eur Heart J 2016;37:2129–200. 2. Solomon SD, Anavekar N, Skali H, et al. Influence of ejection fraction on cardiovascular outcomes in a broad spectrum of heart failure patients. Circulation 2005;112:3738–44. 3. Lund LH, Vedin O, Savarese G. Is ejection fraction in heart failure a limitation or an opportunity? How could clinicians understand HF and make adequate treatment. Eur J Heart Fail 2018;5:6–7. 4. Dunlay SM, Roger VL, Weston SA, Jiang R, Redfield MM. Longitudinal changes in ejection fraction in heart failure patients with preserved and reduced ejection fraction. Circ Heart Fail 2012; 5:720–6.

Prevalence, prognosis, and predictors of the complete clinical recovery with return of cardiac size and function to normal in patients undergoing optimal therapy. J Card Fail 2004;10:250–7.

14. Jonsson A, Edner M, Alehagen U, Dahlström U. Heart failure registry: a valuable tool for improving the management of patients with heart failure. Eur J Heart Fail 2010;12:25–31.

8. Punnoose LR, Givertz MM, Lewis EF, Pratibhu P, Stevenson LW, Desai AS. Heart failure with recovered ejection fraction: a distinct clinical entity. J Card Fail 2011;17:527–32.

15. Savarese G, Orsini N, Hage C, et al. Utilizing NT-proBNP for eligibility and enrichment in trials in HFpEF, HFmrEF, and HFrEF. J Am Coll Cardiol HF 2018;6:246–56.

9. Teeter WA, Thibodeau JT, Rao K, et al. The natural history of new-onset heart failure with a

16. Lund LH, Carrero JJ, Farahmand B, et al. Association between enrolment in a heart failure

severely depressed left ventricular ejection fraction: Implications for timing of implantable cardioverter-defibrillator implantation. Am Heart J 2012;164:358–64.

quality registry and subsequent mortality-a nationwide cohort study. Eur J Heart Fail 2017; 19:1107–16.

10. Agra Bermejo R, Gonzalez Babarro E, López Canoa JN, et al. Heart failure with recovered ejection fraction: clinical characteristics, determinants and prognosis. CARDIOCHUS-CHOP registry. Cardiol J 2018;25:353–62.

17. Ludvigsson JF, Andersson E, Ekbom A, et al. External review and validation of the Swedish national inpatient register. BMC Public Health 2011;11:450. 18. Ingelsson E, Arnlöv J, Sundström J, Lind L. The validity of a diagnosis of heart failure in a hospital discharge register. Eur J Heart Fail 2005;7:787–91.

11. Basuray A, French B, Ky B, et al. Heart failure with recovered ejection fraction clinical descrip-

19. Lam CSP, Teng T-HK. Understanding heart

tion, biomarkers, and outcomes. Circulation 2014; 129:2380–7.

failure with mid-range ejection fraction. J Am Coll Cardiol HF 2016;4:473–6.

12. Kalogeropoulos AP, Fonarow GC, Georgiopoulou V, et al. Characteristics and outcomes of adult outpatients with heart failure and improved or recovered ejection fraction. JAMA Cardiol 2016;1:510.

20. Lund LH, Claggett B, Liu J, et al. Heart failure with mid-range ejection fraction in CHARM: Characteristics, outcomes and effect of candesartan across the entire ejection fraction spectrum. Eur J Heart Fail 2018:1–10.

7. Cioffi G, Stefenelli C, Tarantini L, Opasich C.

13. Lupón J, Díez-López C, de Antonio M, et al. Recovered heart failure with reduced ejection fraction and outcomes: a prospective study. Eur J

21. Merlo M, Pyxaras SA, Pinamonti B, Barbati G, Di Lenarda A, Sinagra G. Prevalence and prognostic significance of left ventricular reverse

Chronic left ventricular failure in the community:

Heart Fail 2017:2–4.

remodeling in dilated cardiomyopathy receiving

5. Vedin O, Lam CSP, Koh AS, et al. Significance of ischemic heart disease in patients with heart failure and preserved, midrange, and reduced ejection fraction: a nationwide cohort study. Circ Heart Fail 2017;10:e003875. 6. Tsuji K, Sakata Y, Nochioka K, et al. Characterization of heart failure patients with mid-range left ventricular ejection fraction— a report from the CHART-2 Study on behalf of the CHART-2 Investigators. Eur J Heart Fail 2017:258–69.

11

12

Savarese et al.

JACC: HEART FAILURE VOL.

tailored medical treatment. J Am Coll Cardiol 2011;57:1468–76. 22. Binkley PF, Lesinski A, Ferguson JP, et al. Recovery of normal ventricular function in patients with dilated cardiomyopathy: predictors of an increasingly prevalent clinical event. Am Heart J 2008;155:69–74. 23. Wilcox JE, Fonarow GC, Yancy CW, et al. Factors associated with improvement in ejection fraction in clinical practice among patients with heart failure: findings from IMPROVE HF. Am Heart J 2012;163:49–56. 24. Piro M, Della Bona R, Abbate A, Biasucci LM, Crea F. Sex-related differences in myocardial remodeling. J Am Coll Cardiol 2010;55:1057–65.

-, NO. -, 2019 - 2019:-–-

Ejection Fraction Change in Heart Failure

26. Solomon SD, Skali H, Anavekar NS, et al. Changes in ventricular size and function in patients treated with valsartan, captopril, or both after myocardial infarction. Circulation 2005;111:

30. Seferovic PM, Petrie MC, Filippatos GS, et al. Type 2 diabetes mellitus and heart failure: a position statement from the Heart Failure Association of the European Society of Cardiology. Eur J

3411–9.

Heart Fail 2018;20:853–72.

27. van Campen LC, Visser FC, Visser CA. Ejection fraction improvement by beta-blocker treatment in patients with heart failure: an analysis of studies published in the literature. J Cardiovasc Pharmacol 1998;32 Suppl 1:S31–5.

31. Cho GY, Marwick TH, Kim HS, Kim MK,

28. Metra M, Nodari S, Parrinello G, Giubbini R, Manca C, Dei Cas L. Marked improvement in left ventricular ejection fraction during long-term beta-blockade in patients with chronic heart failure: clinical correlates and prognostic significance. Am Heart J 2003;145:292–9.

25. Silverberg DS, Wexler D, Blum M, et al. The use of subcutaneous erythropoietin and intravenous iron for the treatment of the anemia of severe, resistant congestive heart failure improves cardiac and renal function and functional cardiac class,

29. Cleland JGF, Bunting KV, Flather MD, et al. Beta-blockers for heart failure with reduced, mid-range, and preserved ejection fraction: an individual patient-level analysis of

and markedly reduces hospitalizations. J Am Coll Cardiol 2000;35:1737–44.

double-blind randomized trials. Eur Heart J 2018;39:26–35.

Hong KS, Oh DJ. Global 2-dimensional strain as a new prognosticator in patients with heart failure. J Am Coll Cardiol 2009;54:618–24. 32. Stanton T, Leano R, Marwick TH. Prediction of all-cause mortality from global longitudinal speckle strain: comparison with ejection fraction and wall motion scoring. Circ Cardiovasc Imaging 2009;2:356–64.

KEY WORDS ejection fraction, heart failure, predictors, prognosis

A PPE NDI X For supplemental tables, please see the online version of this paper.