Τhe association of heart failure across left ventricular ejection fraction with mortality in atrial fibrillation

Abstract

Aims

The aim of this study is to investigate the prognostic implications of the presence of heart failure (HF) across the range of left ventricular ejection fraction (LVEF) in patients with comorbid atrial fibrillation (AF).

Methods and results

We conducted a retrospective cohort study of 1063 patients (median age 76 years), discharged from the cardiology ward with a primary or secondary diagnosis of AF between 2015 and 2018. We used Cox proportional‐hazards and spline models to examine the association of the presence of HF, across the range of LVEF, with the primary outcome of all‐cause mortality. HF was documented in 52.9% of patients at baseline. During a median follow‐up of 31 months (interquartile range 10 to 52 months), 37.3% of patients died. The presence of HF was associated with a significantly higher risk of mortality [adjusted hazard ratio (aHR) 2.17; 95% confidence interval (CI), 1.70 to 2.77; P < 0.001], which was evident across HF with reduced (aHR 3.03; 95% CI 2.41 to 4.52), mid‐range (aHR 2.08; 95% CI 1.47 to 2.94), and preserved LVEF (aHR 1.94; 95% CI 1.47 to 2.55). Among patients with HF, the spline curve depicted a non‐linear association between LVEF and the risk of death, in which there was a steep and progressive increase in mortality for every 5% reduction in LVEF below 25% (aHR 1.97, 95% CI 1.04 to 3.73, P = 0.04).

Conclusions

In patients with AF who were discharged from the hospital, the presence of HF at baseline was independently associated with a twofold risk of death, which was significant across LVEF‐classified HF subtypes. Among patients with AF and HF, the risk of death rose significantly as LVEF was reduced below 25%.

Introduction

Atrial fibrillation (AF) is among the most common comorbidities found in hospitalized patients, and its prevalence keeps rising.¹ Heart failure (HF) occurs in more than one-third of patients with AF.² These entities are closely interrelated and have been designated as modern cardiovascular epidemics.^2,3 AF has been associated with significant mortality and morbidity, which rise steeply when HF coexists.^2–4

The latest European Society of Cardiology Guidelines classified HF into three distinct subtypes, namely, HF with reduced (HFrEF), mid-range (HFmrEF), and preserved (HFpEF) left ventricular ejection fraction (LVEF).⁵ Ejection fraction is the principal determinant of this classification; it is still the most widely reported index in echocardiography,⁵ and historically related with the risk of mortality and cardiovascular morbidity.⁶ To date, scarce data exist on the prognostic implications of the triad of LVEF-classified HF subtypes in patients with AF. On the other hand, LVEF is measured as a continuum and can have infinite strata instead of only three. Hence, a risk stratification model incorporating continuous LVEF values would improve our understanding regarding the prognosis of patients with AF and HF. As of 2020, there is no data on the association of HF, stratified across the LVEF continuum, with the clinical course of patients with AF following acute hospitalization.

Against this background, we undertook a post hoc analysis of data from a cohort of well-characterized, unselected patients with comorbid AF who were discharged from the cardiology ward of a tertiary centre. LVEF was measured during the index hospitalization, and patients were followed-up after discharge. Our main aim was to evaluate the association of the presence of HF at baseline, further analysed by LVEF, with all-cause mortality during follow-up.

Methods

Study design

This is a retrospective cohort analysis of the MISOAC-AF (Motivational Interviewing to Support Oral AntiCoagulation Adherence in patients with non-valvular Atrial Fibrillation; ClinicalTrials.gov identifier: NCT02941978) randomized trial. The trial design and main results have been reported previously.^7,8 Briefly, MISOAC-AF demonstrated benefit from a motivational-educational intervention in improving adherence to oral anticoagulation among patients with AF, as compared with patients who had been randomly assigned to usual care. The trial conformed to the Declaration of Helsinki, and written informed consent was obtained from the participants. The first author wrote the first draft of the present manuscript and vouches for the completeness and accuracy of the analyses; all the authors participated in revisions.

Data and population sources

We used prospective data from the MISOAC-AF trial from December 2015 through June 2018. The database provided baseline clinical profiles, medical history, laboratory, and echocardiographic data relevant to the index date of hospital discharge, as well as discharge diagnoses and follow-up data on clinical outcomes. Data were manually abstracted on the basis of patient interviews, electronic hospital records, and insurance claims records by independent trained investigators.⁸

The source population included patients who participated in the MISOAC-AF trial. Patients were 18 years or older and had been discharged from the cardiology ward of an urban academic hospital in Thessaloniki, Greece, with any diagnosis, having comorbid AF. Exclusion criteria were valvular AF (moderate-to-severe mitral valve stenosis or mechanical valves), terminal illness, or conditions that could interfere with follow-up procedures. For the purposes of this study, patients whose LVEF had not been evaluated by echocardiography during the index hospitalization were also excluded.

Definition of covariates

Atrial fibrillation was defined as previously documented in the patient's history or new-onset AF during hospitalization. The latter was identified by a 12-lead electrocardiogram or a 24 h Holter monitor as irregular heart rhythm, without detectable P waves, lasting more than 30 s. A history of HF was verified by trained personnel using all available data from the patient's records and the in-person interview, according to the 2016 European Society of Cardiology Guidelines for the diagnosis and treatment of acute and chronic HF.⁵ New diagnoses of HF denoted by the attending physician at discharge were incorporated into the analyses. During the index hospitalization, a routine echocardiographic exam was performed. Echocardiographic images were analysed offline by an independent investigator with the use of dedicated software (EchoPAC, GE, USA). The biplane Simpson's method of disks was used to calculate LVEF, corresponding to the subtraction of the end-systolic volume from the end-diastolic volume and the difference divided by the end-diastolic volume. Values of cardiac cycles with at least two similar preceding RR intervals were chosen. In case of poor image quality, LVEF estimation was based on visual assessment. Patients with HF and an LVEF of 50% or higher were classified as having HFpEF, those with an LVEF of 40% to 49% as HFmrEF, whereas those with an LVEF of less than 40% were classified as having HFrEF.

Study outcomes and follow-up

The primary outcome was all-cause mortality, which was defined as death from any cause. The secondary outcome was the composite of cardiovascular mortality or any hospitalization during follow-up. All outcomes were adjudicated by independent physicians in the MISOAC-AF trial.⁸ All deaths were additionally verified by querying the Greek web-based national general health insurance scheme.

Follow-up regarding the primary and secondary outcomes occurred annually from the index date of hospital discharge, via telephonic or in-person interviews. The follow-up period was extended for the purposes of this study and was ended in May 2020.

Statistical analysis

Characteristics of the study patients, grouped as AF without HF, and AF with HF are presented as frequencies or percentages for dichotomous variables and medians with interquartile ranges or means and standard deviations for continuous variables. Between-group comparisons were conducted using the Pearson χ² or Fisher's exact test for categorical variables and the Wilcoxon rank-sum or Student's t-test test for continuous variables, depending on the normality of data distributions. Time-to-event outcomes are presented with the use of Kaplan–Meier plots and compared among groups by the log-rank test. In patients with AF and HF, changes in the hazard ratio (HR) for the study outcomes across the continuous spectrum of LVEF values were investigated by fitting a spline curve. A value of LVEF, whereby HR equalled one, was derived for each plot. Using regression analyses, we reported the hazard associated with each 5% change in LVEF, given a linear association with the outcome existed for the respective LVEF range. Survival analyses were adjusted by Cox proportional-hazards regression, limited by a ratio of one additional covariate per 10 events of interest. The Cox-models included up to 14 clinically relevant baseline variables: intervention/control group assignment, age, sex, AF type, the presence or absence of chronic coronary syndrome, diabetes, hypertension, the use or non-use of a beta-blocker, angiotensin-converting–enzyme inhibitor, mineralocorticoid-receptor antagonist, oral anticoagulation, and the levels of N-terminal pro-BNP (NT-proBNP), high-sensitivity cardiac troponin T and estimated glomerular filtration rate. Schoenfeld residuals were examined to confirm no violation of the assumptions of the Cox proportional hazards regression model. Follow-up data on patients were censored in the event of death. Death was categorized as cardiovascular or non-cardiovascular, based on pre-specified definitions in the MISOAC-AF trial. All outcomes are reported with 95% confidence intervals (CIs) for HF subtypes, without adjustment for multiplicity. This overall false-positive rate was kept at 5% on two-sided tests. Missing data were handled by multiple imputations by chained equations. We imputed five complete data sets; a list of the variables used in the imputation model and the missing rates before and after the imputation is provided in Supporting Information, Table S1. For the regression analyses, we pooled the results across all five imputed data sets into one point-estimate using Rubin's rule. A sensitivity analysis was performed on the complete-case data set. All analyses were performed with the use of Stata software, Version 13.1 (StataCorp) and R Version 3.4.4 (R Foundation for Statistical Computing, Vienna, Austria) by the first author and an author who is a statistician in an academic clinical trials unit (Clinical Trials Unit Thessaloniki, Aristotle University of Thessaloniki, Greece).

Results

Study population

A total of 1063 patients with AF (median age 76 years, interquartile range 63 to 89 years, 54.6% male) were included during the study period, after excluding 57 with unavailable data on echocardiography during the index hospitalization (Figure S1). Of the included AF patients, 562 (52.9%) had concomitant HF. In general, patients with AF and HF were older, had more comorbidities (hypertension, diabetes mellitus, chronic kidney disease, & coronary artery disease), and more often had a prior history of stroke or transient ischemic attack, compared with patients with AF alone (Table 1). Patients with HF had a mean LVEF of 45 ± 13% with a normal distribution (Figure S2). Most patients had HFpEF (25.7%), followed by HFrEF (16.3%) and HFmrEF (10.9%). In the lower LVEF categories, the proportion of male patients; coronary artery disease; and treatment with digitalis, amiodarone, antiplatelet, mineralocorticoid-receptor antagonist, and statin increased, whereas age, body mass index, arterial hypertension, and CHA₂DS₂-VASc decreased (Table S2). By the end of the study, information regarding the primary and secondary outcomes was available for all patients.

Table 1 Characteristics of the patients at baseline

Characteristic	Overall (N = 1063)	AF-no HF (N = 501, 47.1%)	AF-HF (N = 562, 52.9%)	P
Demographics
Age (years), median (IQR)	76 (13)	73.5 (16)	78 (12)	<0.001
Male sex	580 (54.6%)	263 (52.5%)	317 (56.4%)	0.2
BMI (kg/m2), median (IQR)	28.1 (6.1)	28 (5.9)	28.1 (6.5)	0.09
AF type				<0.001
First diagnosed	114 (11.2%)	75 (15.6%)	39 (7.2%)
Paroxysmal	376 (36.8%)	233 (48.4%)	143 (26.5%)
Persistent or permanent	531 (52%)	173 (36%)	358 (66.3%)
HF type
New-onset HF	40 (3.8%)	—	40 (3.8%)
Pre-existing HF	522 (49.1%)	—	522 (49.1%)
Medical history
Stroke/TIA	193 (18.5%)	69 (13.9%)	124 (22.7%)	<0.001
Stroke under OAC	70 (6.8%)	21 (4.3%)	49 (9.1%)	0.002
Major bleeding	151 (14.5%)	73 (14.8%)	78 (14.3%)	0.81
Arterial hypertension	840 (81%)	379 (77.3%)	461 (84.3%)	0.005
Dyslipidaemia	494 (47.9%)	234 (47.8%)	260 (48.1%)	0.92
Diabetes mellitus	344 (33.2%)	133 (27.1%)	211 (38.6%)	<0.001
Coronary artery disease	409 (41.1%)	157 (33.3%)	252 (48.1%)	<0.001
Chronic kidney disease	154 (15%)	43 (8.8%)	111 (20.5%)	<0.001
Stroke—bleeding risk
CHA2DS2-VASc score	4.4 ± 1.9	3.5 ± 1.8	5.2 ± 1.7	<0.001
HAS-BLED score	1.8 ± 1.0	1.6 ± 1.0	1.9 ± 1.0	0.001
Main diagnosis at discharge				<0.001
Acute coronary syndrome	104 (10.7%)	65 (14%)	39 (7.7%)
AF	380 (39.1%)	280 (60.4%)	100 (19.7%)
HF	273 (28.1%)	—	273 (53.8%)
Valvular heart disease	49 (5%)	22 (4.7%)	27 (5.3%)
Other	165 (17%)	97 (20.9%)	68 (13.4%)
Rate control medication at discharge			<0.001
Beta-blocker	733 (71.2%)	327 (67.4%)	406 (74.5%)
Beta-blocker + digitalis	54 (5.2%)	10 (2.1%)	44 (8.1%)
Rhythm control medication at discharge			<0.001
Amiodarone	178 (18.3%)	100 (21.7%)	78 (15.3%)
Sotalol	16 (1.6%)	10 (2.2%)	6 (1.2%)
Oral anticoagulation medication at discharge		<0.001
VKA	267 (28.8%)	83 (19.1%)	184 (37.3%)
NOAC	505 (54.4%)	255 (58.6%)	250 (50.7%)
Other medication at discharge
OAC + antiplatelet	131 (14.5%)	66 (15.6%)	65 (13.4%)	0.35
ACE inhibitor or ARB	455 (46.3%)	207 (45%)	248 (47.4%)	0.45
MRA	277 (26.4%)	54 (10.9%)	223 (40%)	<0.001
Statin	417 (42.6%)	185 (40.4%)	232 (44.4%)	0.20
Laboratory markers at discharge
eGFR (mL/min/1.73 m2)	59.5 (40)	75 (43)	53.8 (34)	0.002
NT-proBNP	315 (1882)	172.5 (1606)	727 (2500)	0.36
hs-cTnT	26 (39)	23 (40)	29 (38)	0.19

Outcomes

Overall, 396 patients (37.3%) died over a median follow-up of 31 months (interquartile range 10 to 52 months), at a rate of 14.4% per year. Of these deaths, 84.1% were due to cardiovascular causes (Table S3).

The primary outcome of death from any cause occurred in a significantly higher percentage of patients with HF [284 of 562 (50.5%)] than patients without HF [112 of 501 (22.4%)] (unadjusted HR, 2.89; 95% CI, 2.32 to 3.60, P < 0.001 by the log-rank test). After adjustment for baseline measures, HF remained a significant predictor of death (HR, 2.17; 95% CI, 1.70 to 2.77; P < 0.001) (Figure 1A). The secondary outcome of cardiovascular death or any hospitalization occurred more frequently in AF patients with HF than in AF patients without HF [384 patients (68.3%) vs. 232 patients (46.3%)] (unadjusted HR, 1.99; 95% CI, 1.69 to 2.35; P < 0.001 by the log-rank test). The adjusted HR was similar (1.66; 95% CI, 1.38 to 2.00; P < 0.001) (Figure 1B).

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Among LVEF-classified HF subtypes, both the unadjusted and adjusted HRs for the risk of the primary and secondary outcome were significantly higher compared with patients without HF (Figures S3 and 2). This increase in risk was evident across HFrEF (aHR 3.03; 95% CI 2.41 to 4.52, P < 0.001), HFmrEF (aHR 2.08; 95% CI 1.47 to 2.94, P < 0.001), and HFpEF (aHR 1.94; 95% CI 1.47 to 2.55, P < 0.001). A summary of the HRs of outcomes and the individual components of the secondary outcome in HF and HF subtypes, compared with the absence of HF, is presented in Table S4.

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The unadjusted and adjusted spline curves depicting the risk of outcomes of AF patients with HF across the LVEF spectrum, compared with a reference LVEF value of approximately 50%, are presented in Figures S4 and 3, respectively. In the adjusted curve, a trend towards an elevated risk of mortality was observed below 30%. As LVEF further decreased beyond the threshold of 25% (n = 76 patients), a steeper and progressive increase in mortality was evident (Figure 3A). In a multivariable-adjusted model, the HR for mortality increased by 97% for every 5% reduction in LVEF below 25% (HR 1.97, 95% CI 1.04 to 3.73, P = 0.04) (Table S5). The risk of mortality was relatively flat for values between 30% and 55%. Above 55%, the risk slowly declined, which reached statistical significance within the LVEF range of 55–65%. The risk of the secondary outcome (cardiovascular death or hospitalization) showed a similar, albeit less pronounced pattern across LVEF, as compared with the primary outcome (Figure 3B). In the case of the secondary outcome, the spline curve and the limits of the CI included 1.00 for all LVEF values below 55%, which implies that the risk was similar below the 55% cut-off. The results of the analyses with the imputed data sets were virtually consistent with a complete-case analysis (Table S4, Figures S5 and S6).

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Discussion

This post-hoc analysis of a randomized clinical trial of AF patients being discharged from the hospital showed that the presence of HF at baseline was associated with an approximately twofold increase in the adjusted risk of death and the composite outcome of cardiovascular death or all-cause hospitalization. The risk of those outcomes was significantly increased across LVEF-classified HF subtypes. When LVEF was analysed as a continuous variable, the risk of mortality almost doubled for every 5% reduction in LVEF below 25%. To our knowledge, this is the first study to examine the relation of AF and comorbid HF along the continuum of LVEF with hard outcomes.

The observed two-fold increase in the adjusted risk for adverse outcomes in AF patients suffering from HF is in line with previous studies. Incident HF was first identified as an important modifier of survival in AF in a subanalysis of the Framingham Heart Study.³ At that time, OAC treatment was restricted to warfarin, whereas background HF therapy was inferior to modern standards. In both outpatients and newly diagnosed patients with AF, HF was a powerful independent predictor of death and hospitalizations.^9–11 Corroborating evidence on the role of HF in AF has accumulated mostly from retrospective analyses of the landmark novel oral anticoagulation trials: In ROCKET-AF, the adjusted HR for mortality for HF was 1.75 (95% CI 1.4–2.3)¹²; in RE-LY, it reached 3.02 (95% CI 2.5–3.7).¹³ The annual mortality rate in our study reached 14.4%, which is considerably higher compared with other studies.^11–15 This excess mortality could be attributed to several high-risk characteristics of our cohort. Advanced age (median of 76 years), hospitalization in an acute setting, often due to serious cardiovascular causes (38.8% myocardial infarction or acute HF), multiple coexisting conditions apart from HF, and a discordant to the high mean CHA₂DS₂-VASc score of 4.4 use of OAC (83.2%),¹⁶ collectively formulate a cohort more prone to complications, including mortality.

We found a consistently higher adjusted risk of the primary or secondary outcome among AF patients with HFrEF, HFmrEF, or HFpEF, compared with those without HF. Nevertheless, a trend was detected towards higher risk in AF with HFrEF. Outcomes in HFmrEF more closely resembled those of HFpEF rather than those of HFrEF, which was also the case in a study of ambulatory patients with HF.¹⁷ A meta-analysis of data from more than 50 000 patients identified a 24% increased relative risk of mortality in AF-HFrEF and similar risk of hospitalizations, compared with AF-HFpEF.¹⁸ The totality of the data suggests that development of effective targeted interventions towards major comorbidities such as HF is necessary to improve outcomes in AF, besides applying effective anticoagulation per se. Indeed, the strategy of cardiovascular and comorbidity optimization (‘C’ component of the holistic pathway) is fundamental in the 2020 European Society of Cardiology AF Guidelines.¹⁹

Our risk-adjusted analyses identified a strong inverse association between declining LVEF values in the severely depressed range (below 25%) and the risk of mortality, whereas the nadir of adverse outcomes lied at values within the normal range (55–65%). When comparing our results with similar studies, it seems plausible that the relation of LVEF and outcomes varies by clinical setting. In older studies of patients with coronary artery disease²⁰ or chronic HF,^6,21,22 low LVEF was generally associated with worse survival. In contrast, a recent retrospective study indicated a non-significant relation of LVEF with prognosis in patients admitted with de novo or non-ischemic acute HF.²³ In a population-wide study published in 2020, LVEF values outside the normal range were associated with poorer survival, which remained significant after adjustment for a series confounders, including AF and HF.²⁴ These findings were replicated in our study. The credibility of our findings is further heightened by adjusting for an extensive set of confounders. Our study stands out for adjusting for both N-terminal pro-BNP and high-sensitivity cardiac troponin T, which are known powerful prognostic biomarkers.

Although our findings should be interpreted in the context of our sample's moderate size, they support the view that challenges subdivision of HF by a single biomarker (i.e. LVEF) as artificial and of vague prognostic significance, merely limited to the severely depressed spectrum.²⁵ Notably, LVEF was not useful in further risk-stratification of patients with HF and an LVEF between 30% and 55%; a finding consistent in unadjusted and adjusted analyses. It is conceivable that the prognostic significance of LVEF might be blunted in a high-risk group at baseline, namely multi-morbid patients that have sustained an acute hospitalization. In this respect, it would be of interest to explore how novel echocardiographic biomarkers perform, especially left ventricular global longitudinal strain and myocardial work index. Ultimately, we feel that efforts for comprehensive risk assessment in AF using multiple-biomarker based scores are in the right direction, as exemplified by the study of Hijazi et al²⁶ and a recent analysis from our cohort.²⁷

Limitations

This analysis was not planned at the outset of the MISOAC-AF trial and is, therefore, both retrospective and non-randomized, confined to a single-centre data set. Accordingly, the associations of the various factors with the risk of adverse outcomes may suffer from unrecognized biases and unmeasured confounders, despite extensive adjustment for clinically relevant variables. Restricting our analysis to AF patients discharged from the hospital may limit the results' generalizability to AF outpatients, although it helped secure a more homogenous study population. The multivariable models were established based on demographics and characteristics of the patients measured at baseline. This approach could not account for newly ensuing comorbidities during follow-up or at the time of death, albeit it attenuated reverse causation in the interpretation of the results. Moreover, additional data of potential prognostic significance were unavailable, such as the duration or timing of AF and HF diagnosis prior to the index hospitalization, cardiac resynchronization therapy or implantable cardioverter defibrillator device, serial LVEF values post discharge and indices of OAC treatment quality (e.g. time in therapeutic range for vitamin-K antagonists).^28,29 A minority of cases in the database had to be excluded due to missing values on HF status or LVEF, possibly resulting in selection bias. Although assessment of LVEF was performed independently, reproducibility and validity of measurements are questionable in AF.³⁰ Furthermore, diagnosis of HFpEF in the context of AF may be challenging, due to the overlapping symptoms.³¹ Thus, differential misclassification could have influenced our results.

Conclusions

In patients discharged from the hospital with comorbid AF, the presence of HF was independently associated with an approximately two-fold increased risk of all-cause mortality and the composite of cardiovascular mortality or all-cause hospitalization. The risk remained significant across LVEF-classified HF subtypes (HFrEF, HFmrEF, & HFpEF). The discriminatory effect of LVEF for prediction of mortality was strongest for values lower than 25%, whereby the risk doubled for every 5% decrease in LVEF.

Acknowledgements

We want to acknowledge Dimitra Vasdeki, George Dividis, George Fotos, Eleni Paschou, Evropi Forozidou, Paraskevi Tsoukra, Eleni Kotsi, and Ioannis Goulas, who contributed in data collection during the conduction of the MISOAC-AF trial.

Conflict of interest

None declared.

Funding

Not applicable.

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