The prognostic significance of lung function in stable heart failure outpatients

Abstract

Background

This study investigated the impact on all‐cause mortality of airflow limitation indicative of chronic obstructive pulmonary disease or restrictive spirometry pattern (RSP) in a stable systolic heart failure population.

Hypothesis

Decreased lung function indicates poor survival in heart failure.

Methods

Inclusion criteria: NYHA class II‐IV and left ventricular ejection fraction (LVEF) < 45%. Prognosis was assessed with multivariate Cox proportional hazards models. Two criteria of obstructive airflow limitation were applied: FEV₁/FVC < 0.7 (GOLD), and FEV₁/FVC < lower limit of normality (LLN). RSP was defined as FEV₁/FVC > 0.7 and FVC<80% or FEV₁/FVC > LLN and FVC <LLN.

Results

There where 573 patients in the cohort (85% of eligible patients in study period). Median follow‐up was 4.7 years and 176 patients died (31%). Age, NYHA class, smoking, body mass index and LVEF were independent prognostic factors (p<0.01). Obstructive airflow limitation increased mortality using both criteria (HR_GOLD 2.07 [95% CI 1.45–2.95] p<0.01 and HR_LLN 2.00 [1.40–2.84] p<0.01) and was an independent marker when using LLN criteria (HR 1.74 [1.17‐2.59] p=0.006). RSP was independently associated with mortality when defined as FVC < LLN (HR 1.54 [1.01–2.35] p=0.04) but not as FVC < 80%. Multivariate hazard ratios for a 10% decrease in predicted value of FEV1 or FVC were 1.42 (p<0.001) and 1.33 (p<0.001) in patients exhibiting airflow obstruction, and 1.36 (p=0.031) and 1.38 (p=0.041) in RSP.

Conclusions

Presence of obstructive airflow limitation indicative of COPD or RSP were associated with increased all‐cause mortality, however only independently when using the LLN definition.

1. INTRODUCTION

Heart failure (HF) and chronic obstructive pulmonary disease (COPD) are worldwide leading causes of morbidity and mortality.1, 2, 3 Due to the similarity in symptoms, it is difficult clinically to diagnose COPD in patients with HF, and spirometry is required to confirm the diagnosis.4 Previous studies of spirometry in HF patients have shown that COPD according to Global Initiative for Chronic Obstructive Pulmonary Disease (GOLD) criteria has a high prevalence and a negative impact on outcome.5 The American Thoracic Society and European Respiratory Society recommend the use of lower limit of normal (LLN) for diagnosing COPD.6 The application of the LLN criteria in HF results in a decreased prevalence of COPD,7, 8 but the impact on prognosis is unknown. A lung function with a restrictive spirometry pattern (RSP) is associated with diabetes mellitus, hypertension, and cardiovascular disease (CVD)9 and is an independent predictor of death and hospitalization in patients age > 65 years.10 The prognostic importance of a RSP in HF outpatients is currently unknown.

There were 2 main objectives of this study: to investigate the prognostic impact of obstructive airflow limitation indicative of COPD with both the GOLD and LLN criteria and of a RSP in stable patients with systolic HF.

2. METHODS

2.1. Study design

All HF patients (New York Heart Association [NYHA] functional class II–IV and left ventricular ejection fraction [LVEF] <45%) referred to 10 outpatient HF clinics for medical optimization between January 1, 2009, and November 1, 2011, were offered a spirometry examination at the first visit to the HF clinic and at the last visit, where maximal possible doses of HF medication were achieved.8 Baseline demographic data, smoking history, and previous medical history were registered. Follow‐up information on mortality was obtained on January 20, 2015. The study complied with the Helsinki Declaration II and was approved by the local ethics committee (the Committees on Health Research Ethics for the Capital Region of Denmark). Informed consent was obtained from all patients.

2.2. Spirometry examination

Forced expiratory volume in 1 s (FEV₁) and forced vital capacity (FVC) were measured (MicroLab 3300; Micro Medical, Rochester, England, UK) in a seated position without prior administration of a bronchodilator. Trained study nurses performed spirometry; and ≥3 acceptable spirometric measurements were taken, and the highest values were used. Measurements with a variation of FEV₁ < 10% between the 2 highest recordings were accepted. Two investigators (KI and MD) reviewed all the spirometry tracings and excluded those with signs of suboptimal performance (eg, short exhalation time and uneven tracings) before proceeding with further data analyses.

2.3. Variable definition

Lung function was characterized using 2 different criteria: the GOLD criteria, which state that airflow limitation is present with a FEV₁/FVC ratio < 0.7³; and the LLN criteria, in which COPD is present when the FEV₁/FVC ratio is <LLN (ie, below the lower fifth percentile of a healthy age‐, height‐, and sex‐matched population).6 With both criteria, we defined mild obstructive airflow limitation as FEV₁ ≥ 80% of predicted, moderate as FEV₁ < 80% and ≥50% of predicted, and severe as FEV₁ < 50%. RSP has been defined in 2 ways in previous literature. The majority of studies define RSP as FEV₁/FVC > 0.7 and FVC < 80% (fixed cutoff), but other studies have defined RSP as FEV₁/FVC > LLN and FVC < LLN (LLN cutoff).9 In this study, both methods were applied. International recommendations were used to calculate predicted values of FEV₁ and FVC,11 and reference values from a large Danish study were used for LLN calculations.12 Estimated glomerular filtration rate was calculated using the Modification of Diet in Renal Disease Study equation.

2.4. Statistical analysis

Mean values of continuous variables were compared using 1‐way ANOVA with post hoc Bonferroni correction (normally distributed data), and categorical values using the χ² test. Baseline continuous variables are stated as mean with SD and categorical variables as percentages. Baseline variables with univariate association to mortality were entered in multivariate Cox proportional hazards models. Separate models were performed where either FEV₁, FVC, or presence of airflow limitation was added. This was done to avoid collinearity between spirometry parameters. The spirometry from the first visit was used. Body mass index (BMI) was treated as a continuous variable. Outcomes of Cox regression analyses are presented as hazard ratio (HR) with 95% confidence interval in brackets. A P value <0.05 was considered statistically significant. All analyses were made with SPSS version 22 (IBM Corp., Armonk, NY).

3. RESULTS

The present study population consisted of 573 patients (97% of the included 590 patients where spirometry was performed) where follow‐up information on mortality was achieved (median follow‐up time, 4.7 years; range, 3.2–7.1 years).

Mean patient age was 69 (11) years, 26% were female, baseline mean FEV₁ was 78% (19.7) of expected, mean FVC was 85% (17.9) of expected, and mean FEV₁/FVC was 0.72 (0.11). Lung volumes were normally distributed in the population. Baseline characteristics of patients according to the spirometry results using the GOLD criteria are given in Table 1. There were no patients undergoing long‐term oxygen treatment for COPD. Obstructive airflow limitation indicative of COPD was found in 222 patients (39%); of these patients, 92 had a mixed obstructive and restrictive spirometry pattern. There were 129 (22.5%) with RSP, and 222 (39%) had a normal lung function.

Table 1.

Clinical variables and presence of obstructive airflow limitation or restrictive spirometry pattern (GOLD criteria)

	GOLD Criteria			P Value 1 vs 2	P Value 1 vs 3	P Value 2 vs 3
	1) Obstructive Airflow Limitation, n = 222	2) Normal Spirometry, n = 222	3) RSP, n = 129
Age, y (SD)	72 (9)	66 (12)	68 (11)	<0.01	<0.01	0.68
Female sex	54 (24)	68 (31)	27 (21)	0.14	0.37	0.04
NYHA class III–IV	65 (29)	27 (12)	38 (29)	<0.01	0.94	<0.01
Self‐reported COPD	46 (21)	7 (3)	15 (12)	<0.01	0.03	<0.01
BMI, kg/m2
>30	38 (17)	54 (24)	41 (32)	0.10	<0.01	0.33
<20	17 (8)	7 (3)	7 (5)	0.04	0.28	0.29
Previous smoking	124 (57)	90 (40)	70 (54)	<0.01	0.15	<0.01
Active smoking	62 (28)	49 (22)	25 (19)	<0.01	<0.01	0.09
SBP, mm Hg (SD)	131 (22)	131 (24)	128 (20)	1.00	0.98	0.82
DBP, mm Hg (SD)	77 (15)	78 (13)	75 (10)	0.98	0.97	0.47
Heart rate, bpm (SD)	74 (16)	74 (14.2)	76 (16.1)	0.99	1.00	0.81
LVEF, % (SD)	30 (9.6)	31 (9.4)	31 (9.4)	0.98	0.95	1.00
eGFR, mL/min/1.73 m2 (SD)	62 (29)	77 (24)	75 (22)	<0.01	0.02	0.97
Medical therapy
ACEI/ARB	195 (88)	208 (94)	119 (92)	0.03	0.19	0.61
β‐Blocker	166 (75)	173 (78)	102 (79)	0.42	0.45	0.94
Loop diuretic	142 (64)	106 (48)	89 (69)	<0.01	0.37	<0.01
Spironolactone	35 (16)	42 (19)	33 (26)	0.37	0.03	0.18
FEV1, % of predicted (SD)	65.9 (16.3)	95.5 (12.7)	68.9 (11.8)	<0.01	0.17	<0.01
FVC, % of predicted (SD)	83.4 (17.9)	97.2 (11.9)	68.4 (9.8)	<0.01	<0.01	<0.01
FEV1/FVC ratio (SD)	0.61 (0.08)	0.77 (0.05)	0.79 (0.07)	<0.01	0.47	<0.01

Abbreviations: ACEI, angiotensin‐converting enzyme inhibitor; ARB, angiotensin II receptor blocker; BMI, body mass index; COPD, chronic obstructive pulmonary disease; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; FEV₁, forced expiratory volume at 1 second; FVC, forced vital capacity; GOLD, Global Initiative for Chronic Obstructive Lung Disease; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association; RSP, restrictive spirometry pattern; SBP, systolic blood pressure; SD, standard deviation.

Data are presented as n(%) unless otherwise noted. Obstructive airflow limitation: FEV₁/FVC < 0.7. RSP: FEV₁/FVC > 0.7 and FVC < 80%. All reported variables were obtained at the first visit to the outpatient clinic (ie, before optimal therapy of HF medication).

Using LLN, the equivalent numbers were 176 (30%), 145 (25%), and 256 (45%). We did not assess mixed spirometry pattern using LLN. Compared with patients with a normal spirometry, patients with obstructive airflow limitation were older, had a higher prevalence of active and previous smoking, more often had self‐reported COPD, had a decreased estimated glomerular filtration rate, had higher NYHA class, and had a lower BMI. Patients with RSP were more often male, more likely previous smokers, and showed a higher prevalence of NYHA III–IV and self‐reported COPD when compared with patients with a normal spirometry. There were insignificant differences in sex, smoking prevalence, LVEF, BMI, and NYHA class between obstructive and restrictive spirometry patterns using the 2 criteria (for LLN data, see Supporting Information, Table S1, in the online version of this article). However, obstructive and restrictive patients were slightly younger with the LLN than the GOLD criteria and had a slightly lower FEV₁. Patients with obstructive airflow limitation according to GOLD, but not according to LLN (n = 54), had a higher mean age of 75.1 years.

During follow‐up, 176 patients died (31%). The following clinical factors were predictors of mortality: age per year (HR: 1.07, 95% CI: 1.05‐1.08, P < 0.001), active smoking (HR: 1.64, 95% CI: 1.10‐2.43, P = 0.014), NYHA class III–IV (HR: 2.08, 95% CI: 1.54‐2.78, P < 0.001), and LVEF per percent increase (HR: 0.97, 95% CI: 0.96‐0.98, P < 0.001). Higher BMI was overall linked to a better prognosis (BMI per kg/m² increase [continuous variable]: 0.95, 95% CI: 0.92‐0.97, P < 0.001).

Total mortality was higher in the presence of obstructive airflow limitation according to GOLD (87 deaths, 39%) or RSP (43 deaths, 33%) compared with a normal spirometry (46 deaths, 21%; P < 0.0001; similar percentages using LLN criteria). There were 49 deaths in the subgroup of 92 patients (53%) with mixed obstructive and restrictive spirometry pattern according to GOLD. Kaplan–Meier survival plots were made to illustrate the associations between severity levels of obstructive airflow limitation and of an RSP and mortality (Figure 1).

Figure 1.

Kaplan–Meier survival plots according to severity of airflow limitation using GOLD (left) and LLN (right) criteria. Results of pairwise comparisons using log‐rank test are shown in the figure. Abbreviations: LLN, lower limit of normal

Obstructive airflow limitation indicative of COPD was a significant predictor of all‐cause mortality compared with normal in univariate analyses (HR_GOLD: 2.07, 95% CI: 1.45‐2.95, P < 0.01 and HR_LLN: 2.00, 95% CI: 1.40‐2.84, P < 0.01, respectively). There was a difference in the prognostic impact between male (HR_GOLD: 1.96, 95% CI: 1.29‐2.96, P < 0.01 and HR_LLN: 1.18, 95% CI: 1.20‐2.71, P < 0.01) and female patients (HR_GOLD: 2.26, 95% CI: 1.09‐4.66, P = 0.03 and HR_LLN: 2.51, 95% CI: 1.20‐5.23, P = 0.01). In multivariate Cox regression analyses following inclusion of age, smoking, BMI, NYHA class, and LVEF, airflow obstruction according to GOLD lost its prognostic significance (HR_GOLD: 1.26, 95% CI: 1.85‐1.87, P = 0.26) but according to LLN criteria was still significant (HR_LLN: 1.74, 95% CI: 1.17‐2.59, P = 0.006). Figure 2 illustrates the multivariate HRs for mortality according to severity of airflow obstruction and to an RSP.

Figure 2.

Multivariate HRs for severity of obstructive airflow limitation and of RSP compared to patients with normal spirometry using GOLD and LLN criteria. Closed circles, GOLD criteria; open circles, LLN criteria. The model illustrated in the figure was adjusted for age, smoking, NYHA class, BMI, and LVEF. Abbreviations: BMI, body mass index; CI, confidence interval; GOLD, Global Initiative for Chronic Obstructive Pulmonary Disease; HR, hazard ratio; LLN, lower limit of normal; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association; RSP, restrictive spirometry pattern

RSP according to the fixed cutoff was associated with an increased risk in univariate analysis (HR: 1.67, 95% CI: 1.10‐2.53, P = 0.02) but not in the multivariate model. In the multivariate model, RSP according to the LLN cutoff remained significant (HR: 1.54, 95% CI: 1.01‐2.35, P = 0.04; Figure 2). Finally, the subgroup of patients with mixed obstructive and RSP according to GOLD showed an HR in multivariate regression analysis of 2.09 (95% CI: 1.30‐3.35, P < 0.01) compared with patients with a normal spirometry. Table 2 shows that FEV₁ and FVC (in % of predicted) were significant prognostic markers. Similar results were seen for LLN criteria (see Supporting Information, Table S2, in the online version of this article).

Table 2.

Prognostic value of FEV₁ and FVC in HF patients stratified according to lung function using GOLD criteria

		Univariate HR (95% CI)	P Value	Multivariate HR (95% CI)a	P Value
Obstructive airflow limitation, n = 222	FEV1% (per 10% decrease)	1.35 (1.18‐1.54)	<0.001	1.43 (1.21‐1.68)	<0.001
	FVC % (per 10% decrease)	1.29 (1.14‐1.46)	<0.001	1.33 (1.13‐1.55)	<0.001
Restrictive spirometry pattern, n = 129	FEV1% (per 10% decrease)	1.29 (1.00‐1.66)	0.050	1.36 (1.03‐1.80)	0.031
	FVC % (per 10% decrease)	1.39 (1.08‐1.79)	0.011	1.38 (1.01‐1.87)	0.041

Abbreviations: CI, confidence interval; FEV₁, forced expiratory volume at 1 second; FVC, forced vital capacity; GOLD, Global Initiative for Chronic Obstructive Lung Disease; HF, heart failure; HR, hazard ratio.

Obstructive airflow limitation: FEV₁/FVC < 0.7. RSP: FEV₁/FVC > 0.7 and FVC < 80%.

^aMultivariate models included age, smoking, NYHA class, BMI, and LVEF. Separate model was made for each spirometric variable. Referent is highest value in obstructive and restrictive patients, respectively.

A secondary spirometry examination after up‐titration of HF medication was performed in 328 (57%) patients (at a median time of 177 days [interquartile range, 99–286 days]). The changes in FEV₁ or FVC divided by baseline FEV₁ or FVC showed no significant associations to mortality in univariate Cox regression analyses. There was no difference in spirometry parameters before and after up‐titration of HF therapy, yet there was a > 50% reduction of severe dyspnea (NYHA class III–IV).8

4. DISCUSSION

The coexistence of COPD and HF is likely multifactorial and mediated by shared risk factors and pathological pathways involving systemic inflammation.5 The present and several previous studies designate obstructive airflow limitation in spirometry as COPD. However, this is not entirely accurate, as HF can induce changes in spirometric parameters that reflect lung congestion and not necessarily pulmonary pathology.13 The age and the combined prevalence of active or previous smoking was high (84%) in patients designated as COPD in this study, but there are likely other mechanisms involved in the high prevalence of COPD. Lung congestion and bronchial hyper‐responsiveness likely contribute to the decreased pulmonary function seen in HF patients.14, 15 The HR of COPD in previous work varies depending on HF severity, follow‐up time, and COPD definition and is usually reported around 1.5 to 2.0.13, 16, 17, 18, 19, 20 In the present study, there was no increased mortality of mild COPD, which is in accordance with previous spirometry studies in HF.17, 19, 20

In the general population, subjects with obstructive airflow limitation identified by both the GOLD and LLN criteria have an increased mortality,21 as well as higher prevalence of chronic cough and dyspnea,22 than do subjects with COPD, according only to GOLD but not to LLN. There is no consensus on which of these criteria should be used to diagnose COPD in HF. The GOLD criteria carry a possibility of overdiagnosing lung disease in the elderly,23 and because HF is mainly a disease of the elderly, it is possible that some patients do not have pathological airflow obstruction but rather lowered FEV₁/FVC ratio due to age. In our study, we found similar survival curves for moderate to severe airflow limitation using either set of criteria, but slightly better prognostic information was obtained using LLN. Presence of COPD was only associated with mortality after multi‐adjustment using the LLN criteria, which suggests that the ability to predict death was confounded to a greater extent with the GOLD than the LLN cutoff, likely due to differences in age.

4.1. The prognosis of a restrictive spirometry pattern in HF

RSP has a prevalence of approximately 10% in the general population24, 25 and was much higher in this cohort (39%), suggesting an intimate relationship between HF and this spirometric pattern. The prevalence of active or previous smoking was high in this cohort but similar in patients with restrictive spirometry pattern and normal lung function. Previous research has shown patients with RSP to be particularly vulnerable to CVD and future cardiovascular events.9 In support of this notion, a population study found that a cardiothoracic ratio > 55% on chest x‐ray was associated with >4× increased risk of RSP,24 and the Jackson Heart Study found that a baseline RSP was more prevalent in patients subsequently hospitalized for HF.26 In a study by Johnston et al., RSP was a strong predictor of CVD; however, it was only significantly associated with death in the patients without previous CVD.25 The prevalence of an RSP is high in HF patients and a predictor of poor outcome in patients listed for heart transplantation.27, 28 The present results support that an RSP is associated with mortality in HF; however, there was only an independent association to mortality using the LLN definition (Figure 2).

Obesity can induce restriction in pulmonary function tests,29 and in our study it was evident that obese patients were more likely to have RSP. However, this was not responsible for the decreased outcome in RSP patients, as a high BMI was related to a good outcome. This paradoxical inverse relationship between body size and mortality in chronic patients has been earlier described in several patient populations, including chronic HF30 and patients with diabetes and cardiovascular morbidity.31 Previous investigations of HF patients have shown that a restrictive pattern might result from accumulated interstitial edema.32 However, pleural effusions, decreased respiratory muscle strength,33 and cardiomegaly32 may have contributed to the findings. The present study lacks natriuretic peptides and chest x‐ray, which could be helpful in understanding the complex pathology. It is possible that some patients with RSP might have true restrictive lung disease, but our study lacks measurement of total lung capacity, which is needed to make this diagnosis.6

4.2. Study strengths and limitations

The study population was large and heterogeneous, inclusion rate was high, follow‐up time was long, and the spirometry was performed in stable conditions to decrease confounding by lung congestion. Lung congestion negatively affects FEV₁ and FVC in overhydrated patients.14, 15 Hence, the increased mortality with lower values in spirometry might be partly explained by lung congestion due to worsened cardiac performance. Despite an increase in medical therapy of patients included in this study, there was no increase in lung volumes.8 This could be explained by patients already being in a stable condition at baseline and in agreement with the lack of prognostic information the changes in FEV₁ or FVC divided by baseline FEV₁ or FVC for patients having a second spirometry. However, because our study lacks an objective measure of volume state, we cannot accurately adjust for the degree of cardiac decompensation in the prognostic estimates. Some eligible patients were not included in the present analyses. A full description of patients who did not perform a spirometry examination has been described in earlier publications; only minor differences from the included patients were found.8 There was a lack of follow‐up on mortality in 13 patients (2%), and we find this number acceptable as to not bias our results. The prevalence of undiagnosed asthma in this study is unknown, and potentially some of the patients with airflow obstruction could have asthma and not COPD. No bronchodilator was administered before spirometry examination; however, a previous study of spirometry in HF patients showed no reversibility of lung‐function parameters.34 There are multiple biochemical markers with known prognostic impact in chronic HF, such as hemoglobin35 and natriuretic peptides,36 which were not adjusted for in the present analyses; this might have had an impact on our prognostic models.

4.3. Clinical implications

Accurate risk stratification is important, as it can help guide therapeutic decision‐making, and clinicians should routinely assess patient prognosis in the course of standard evaluation of HF. A recognition of a concomitant COPD in HF patients is important because these patients have lower exercise performance,37 increased rates of preventable hospitalizations,38 and increased risk of obstructive sleep apnea,39 and they may have extra benefit of a more vigilant monitoring program.40 An RSP was highly prevalent in this cohort of HF patients; the high prevalence of RSP implicates that COPD therapy should not be instituted before a spirometry is performed. Clinicians should be aware of both obstructive and restrictive spirometry patterns in regard to prognostication of patients, especially because patients with a mixed obstructive and restrictive pattern showed a particularly poor prognosis.

5. CONCLUSION

Presence of obstructive airflow limitation indicative of COPD or RSP was associated with an increased all‐cause mortality, although only independently when using the LLN definition. Spirometry parameters can be used to assess prognosis in stable HF patients.

5.1. Author contributions

L.P. wrote the manuscript and performed the statistical analyses. L.P., M.D., and K.I. participated in the acquisition of data. E.K., M.D., K.I., M.S., L.K., and J.V. participated in the interpretation of data. K.I. had the original idea for the study. All authors critically revised the manuscript for intellectual content and approved the final version.

Conflicts of interest

Aside from the funding grant from Pfizer and Boehringer‐Ingelheim, the authors declare no other potential conflicts of interest.

Supporting information

Table S1. Clinical variables and presence of obstructive airflow limitation or restrictive spirometry pattern (LLN criteria)

Table S2. Prognostic value of FEV₁ and FVC in HF patients stratified according to lung function using LLN criteria

Plesner LL, Dalsgaard M, Schou M, et al. The prognostic significance of lung function in stable heart failure outpatients. Clin Cardiol. 2017;40:1145–1151. 10.1002/clc.22802