Introduction
Dyspnoea and congestion are the most common clinical features of acute heart failure (AHF), and both have strong pathophysiological backgrounds in the development of the disease. As a result, they have become therapeutic targets and relief of dyspnoea and congestion during the treatment of AHF events are favourable clinical signs.1 2 Residual congestion is a well-documented predictor of poor prognosis, but there are limited data available on residual dyspnoea at discharge and its clinical implications.3–7 Dyspnoea in AHF has complex and multifactorial aetiology, and therefore, its development goes far beyond ‘simple’ pulmonary congestion.8–10 In HF, several pathophysiological pathways that lead to dyspnoea sensation are activated, some may be congestion related, but most of them are congestion independent.11 The latter ones are represented by overactivity of the sympathetic nervous system that modulate the activity of the peripheral chemoreceptors located in the carotid bodies. It is additionally intensified by the stimulation of mechanoreceptors located in the respiratory tract, that is, lung stretch receptors, as well as those present in the respiratory and skeletal muscles of the chest. Another important factors of dyspnoea development in HF are disruptions in central haemodynamics (even if not leading to congestion), arterial dysfunction with microcirculation disorders, neurohormonal drive, anaemia, iron deficiency, ageing, frailty and malnutrition.12 13
In this article, we analyse the impact of residual dyspnoea assessed at discharged from the hospital on clinical characteristics, laboratory profile and prognosis in patients with AHF. Our study highlights the significance of residual dyspnoea in predicting adverse clinical outcomes and provides insights for managing patients with AHF.
Materials and methods
This is a single-centre, observational study. The study population consists of patients who were admitted to the Centre of Heart Diseases at fourth Military Hospital in Wroclaw, Poland, between January 2016 and September 2017.14 To be included in the study, patients had to be adults (>18 years old), have AHF as the main reason for their hospitalisation, receive intravenous furosemide on admission and provide written consent. The exclusion criteria were cardiogenic shock, acute coronary syndrome, severe liver disease or end-stage renal disease requiring renal replacement therapy. AHF was defined using the criteria established by the European Society of Cardiology guidelines.1 15
Study procedures
After being admitted to the hospital, the patients underwent a clinical examination, during which detailed information about their demographics (including their history of HF), comorbidities, previous treatment and physical examination findings were recorded. This analysis presents only patients, who survived the hospitalisation and had the dyspnoea assessed at discharge.
Laboratory tests
At each predefined time point, patient’s blood and urine samples were taken for analyses. The study measured various laboratory parameters using standard methods in the local laboratory. Plasma N-terminal pro-B-type natriuretic peptide (NTproBNP) and cardiac troponin levels were also measured using immunoenzymatic methods from plasma samples. The renin and aldosterone system activation were measured using chemiluminescent immunoassay-CLIS, LIASON from initially frozen samples.
Dyspnoea assessment
During the hospitalisation, at predefined time points, each patient was asked to provide information about the presence or absence of dyspnoea at rest and during exertion. The severity of dyspnoea (difficulty breathing) was assessed using a self-reported 10-point Likert scale. This scale ranged from 0 (indicating no dyspnoea) to 10 (indicating the most severe dyspnoea possible). The dyspnoea was assessed at admission, day 1, day 2 and discharge.
Categorisation
The study population was divided based on the presence or absence of resting dyspnoea at discharge, as well as based on the severity of exertional dyspnoea reported at discharge using a cut-off score of 5 points (<5 points vs ≥5 points—moderate/severe dyspnoea).
Study outcomes
The clinical endpoints of the study were:
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One-year all-cause mortality.
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Composite endpoint of 1-year all-cause mortality and rehospitalisation for the HF.
Clinical follow-up
Patients who were discharged from the hospital were closely monitored as per the protocols of the HF clinic for a minimum of 1 year. Multiple sources were used to gather information regarding patients’ survival status and readmission to the hospital, including patient feedback, interviews with their family members over the phone, relevant clinic databases and/or the national register of citizens. No patient was lost from follow-up.
Statistical analysis
Continuous variables with a normal distribution were presented as mean±SD, while variables with a skewed distribution were described using medians with (upper and lower quartiles). Categorical variables were presented as numbers and percentages. Statistical analyses between study groups were performed using the t-test, Mann-Whitney U-test or χ2 as appropriate. Cox proportional hazards models were used to calculate the HR with corresponding 95% CIs for all-cause mortality. The multivariable analysis was adjusted for confounding variables including systolic blood pressure at admission, creatinine at admission, ejection fraction, age, bilirubin at discharge, NTproBNP discharge. The missing data in the multivariable model were imputed by mean value, for categorical variables missing values were replaced with the most frequent category. The Kaplan-Meier survival curves were used to visualise the survival analysis. A p<0.05 was considered statistically significant. The statistical analysis was performed using STATISTICA V.13 (StatSoft).
Results baseline characteristics
The study population included 202 patients admitted to the hospital due to AHF. Most of them were male (74%) with a mean age of 71±13 years. Among the subjects under investigation, 115 (57%) were individuals afflicted with decompensated chronic HF, whereas the remaining 87 (43%) were patients who received a de novo diagnosis of the condition. The ischaemic aetiology was predominant (n=103, 51%), with a mean left ventricle ejection fraction (LVEF) of 37%±13%. Mean systolic and diastolic blood pressure and heart rate at admission were 135±32 mm Hg, 79±16 mm Hg and 92±24 beats per minute, respectively. The median (lower and upper quartile) plasma concentrations of NTproBNP and troponin I were 5731 (3395–12081) pg/mL and 0.06 (0.03–016) ng/ mL, respectively. Detailed data on the baseline characteristics of patients are provided in table 1.
Baseline characteristics
The trajectory of dyspnoea during hospitalisation
Among the patients on admission, 159 (78.7%) presented dyspnoea at rest. The number of patients reporting resting dyspnoea decreased on subsequent days of hospitalisation day 1: 67 (33%) and day 2: 40 (20%). At discharge, 16 patients (7.9%) still presented resting, residual dyspnoea (figure 1).
The number of patients reporting dyspnoea at rest in subsequent days of hospitalisation.
The median dyspnoea reported by the patients at admission was 8.0 (8.0–10.0) points. With each day of hospitalisation, the intensity of the reported dyspnoea decreased, reaching day 1: 6.0 (4.0–8.0) points, day 2: 5.0 (2.0–6.0) points. The median discharge dyspnoea was: 2.0 (0.0–4.0) points (online supplemental figure 1).
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Analogically, a number of patients with moderate/severe dyspnoea (≥5 points) at admission, day 1 and day 2 were: 187 (93%), 135 (67%) and 109 (54%), respectively. There were 48 (24%) patients with moderate/severe dyspnoea at discharge (online supplemental figure 2).
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Comparison of patients with different dyspnoea severity at discharge
Patients with moderate/severe dyspnoea at discharge (≥5 points) were older, their mean age was 74±11 vs 70±13.2 years, when compared with the lower dyspnoea severity group, p=0.05. There was no difference between both groups in regard to LVEF and systolic blood pressure 40±14.3 vs 36±13.4, p=0.1; 129.5±27.7 vs 137±32.6, p=0.17, respectively. Interestingly, both populations did not differ in terms of possible dyspnoea triggers such as anaemia, for example, haemoglobin 132±22 vs 133±19.9, p=0.59, inflammation markers, for example, leucocytes 9.32±5.2 vs 9.3±4.3, p=0.97, C reactive protein 9.4 (5.0–29) vs 7.2 (3.4–17.8), p=0.14, hypoxaemia, for example, sO2 92±4.9 vs 92±6.1, p=0.8, hypoperfusion lactate 2.2±1.0 vs 2.4±1.5, p=0.19. There was also no statistically significant difference in blood gas parameters at admission (pH 7.44±0.07 vs 7.43±0.07, p=0.33; pCO2 34.8±5.4 vs 35.8±6.98, p=0.35; pO2 68±11.4 vs 69.9±22.8, p=0.63, HCO3− 23.3±3.6 vs 23.25±3.8, p=0.94). Neither there was a difference in blood gas parameters assessed at discharge (see table 2). Patients with moderate/severe residual dyspnoea had significantly higher NTproBNP levels at admission 7616 (4344–13211) vs 5297 (3119–11579), p=0.05, but the drop of NTproBNP and discharge NTproBNP levels did not differ between both groups (table 2). Moreover, the distribution of pulmonary congestion based on clinical assessment did not differ between both groups.
The comparison between patients with different reported dyspnoea severity at discharge
The impact of dyspnoea assessed during hospitalisation on 1-year mortality
In the univariable model, only dyspnoea assessed at discharge had prognostic significance, while dyspnoea assessed at earlier time points of hospitalisation had no impact on mortality (online supplemental table 1). The discharge dyspnoea at rest had strong prognostic significance, HR with 95% CI 5.8 (3.0 to 11.3), p<0.0001. Analogically, the discharge dyspnoea assessed on a continuous scale was related to poor outcome, HR (95% CI) 1.2 (1.1 to 1.4), p<0.0001. Moreover, patients with moderate/severe dyspnoea had an almost threefold higher risk of 1- year mortality when compared with the rest of the population, HR (95% CI) 2.9 (1.7 to 4.9), p=0.0001. The Kaplan-Meier curves for 1-year mortality by residual dyspnoea at discharge are presented in figure 2. To provide broader perspective, we have also run the sensitivity analyses, in which models were also adjusted for gender, comorbid conditions and concomitant medication (online supplemental tables 2–4). Residual dyspnoea has persistently emerged as an independent predictor of unfavourable outcomes in the population.
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The Kaplan-Meier curves for 1-year mortality by residual dyspnoea at discharge. Log rankp=0.0001. Red line—patients without dyspnoea at discharge. Blue line—patients with dyspnoea at discharge.
The discharge dyspnoea as an independent maker of the unfavourable outcomes
In the multivariable model (after adjustments for systolic blood pressure at admission, creatinine at admission, ejection fraction, age, bilirubin at discharge, NTproBNP discharge) residual dyspnoea at discharge was an independent predictor of poor outcomes. The resting residual dyspnoea at discharge was related to a higher risk of both 1-year mortality and composite outcome, with HR (95% CI) 8.0 (3.7 to 17.3) and 5.1 (2.6 to 10.2), respectively, both p<0.0001. Moderate or severe dyspnoea at discharge was related to the heightened risk of study outcomes, with HR (95% CI) 3.1 (1.8 to 5.4) and 1.8 (1.1 to 2.9), respectively, p<0.01 (table 3). Analogically, after adjustments for gender, comorbid conditions and medication (online supplemental tables 2–4) the residual dyspnoea remained an independent maker of poor outcome.
The impact of residual dyspnoea at discharge on outcomes
Discussion
The major message of our paper is that residual dyspnoea (assessed at discharge) is unexpectedly frequent and associated with poor prognosis in patients with AHF. Patients who reported resting residual dyspnoea had a 5–8 fold higher risk of clinical events during the upcoming year. Analogically, individuals who still experienced moderate/severe exertional dyspnoea at discharge had a threefold higher risk of death during follow-up. Importantly, the residual dyspnoea was an independent risk factor of poor outcome even after adjustment for several different variables, including blood pressure, renal function, ejection fraction, age, NTproBNP gender or comorbidities. Residual congestion (one of the potential mechanisms that could explain the residual dyspnoea) is a well-known marker of unfavourable outcomes in HF.3 5 However, we believe that our study provides a broader perspective on persistent dyspnoea and demonstrates that this phenomenon is not a substitute for persistent congestion. The residual dyspnoea was surprisingly frequent in the population, reaching 8% (if defined by dyspnoea at rest) or even one-fourth of the population (if defined as more than moderate dyspnoea reported by the patient at discharge). The pathomechanism of shortness of breath development in HF is complex and goes beyond the reflection of congestion status.11
Dyspnoea represents one of the prevailing symptoms encountered in AHF patients that defines a subjective perception of respiratory discomfort, and its manifestation varies among individuals. The multifaceted nature of this perception is underpinned by intricate interactions involving physiological, psychological, sociological and environmental factors. There are several independent pathophysiological pathways that may lead to lower the dyspnoea threshold and most of them are present in HF patients. The most straightforward explanation of the symptom in some (but most likely minority of chronic heart failure) patients is ‘simply’ a pulmonary congestion. Next, the disrupted central haemodynamics including elevation of intracardiac and pulmonary pressures as well as low cardiac output contribute to the development of dyspnoea even without overt congestion. The symptom may also reflect the disease severity itself and neurohormonal drive in each patient. One of the mechanisms contributing to this symptom is the activation of chemoreceptors and baroreceptors in response to fluctuations in the concentration of respiratory gases (both CO2 and O2). The sensation of breathlessness is further heightened by stimuli arising from mechanoreceptors situated directly within the respiratory tract, such as lung stretch receptors, as well as those present in the respiratory and skeletal musculature of the thoracic region, known as ergoreceptors. In HF patients, muscles (including the diaphragm, smooth and skeletal muscles) are notably susceptible to fatigue, primarily due to a combination of factors such as reduced cardiac output, malnutrition, systemic arterial dysfunction, microcirculatory disturbances, anaemia and depleted iron levels. Lastly, the general physical frailty, advanced age, comorbidities, chronic inflammation leading to peripheral vascular dysfunction and low general physical exercise tolerance are other common causes of dyspnoea in HF population.12 13
Taking all the data together it is not surprising that this symptom is manifested significantly more frequently in the elderly HF population that is prone for future adverse events, which has been also demonstrated in our cohort. The other vital but usually overlooked issue is the fact that hospitalisation per se is related with physical deconditioning related with resting at hospital bed, and therefore, patients need significant physical rehabilitation before discharge, which importantly was shown to be safe and feasible in that vulnerable population. Considering the escalating challenge posed by an ageing population of HF patients, it has been well established that initiating rehabilitation at an early stage, implementing effective dietary and nutritional management, and ensuring the stability of cognitive function all contribute positively to long-term prognosis.16–18
In our study potential, congestion-related triggers of dyspnoea (pulmonary congestion on clinical assessment, discharge NTproBNP) did not differ significantly between those with and without residual dyspnoea. Moreover, the drop of NTproBNP during hospitalisation was the same in both study groups (~2000 pg/mL). This observation appears to provide indirect substantiation for the intricate nature of the pathomechanism governing dyspnoea. Nevertheless, it is essential to acknowledge the constraints associated with the assessment of the NTproBNP biomarker itself. It is pertinent to note that, physiologically, NTproBNP levels exhibit elevation in women, rise with advancing age (regardless of gender), in contrast to the values that are notably lower in individuals with obesity. The natriuretic peptides are also very sensitive to disruptions related to many comorbidities.19–21 This underscores the imperative need to interpret biomarker data within the context of the patient’s clinical presentation.
Surprisingly, the residual dyspnoea was neither related to markers of neurohormonal activation (renin/aldosterone) nor to iron metabolism biomarkers (Fe, TSAT, sTfR). Each AHF episode is related to multiorgan dysfunction, and that peripheral hypoperfusion, may potentially trigger the dyspnoea, but this was not a cause in the population either.22–24 Finally, the patients who reported persistent dyspnoea had the same pO2, O2 saturation and pCO2 as those without the dyspnoea, which supports the concept that desaturation is not a major driver of dyspnoea in HF. This is in line with our recent study, in which we demonstrated that hyperventilation and subsequent hypocapnia is an ominous sign of HF but was not related to subjective dyspnoea perception.25
In the general population, the perceived dyspnoea significantly decreased during hospital stay from the median of 8 points at admission to 2 points at discharge, which corresponds to previous reports.26 27 Interestingly, the prognostic significance of dyspnoea assessed in the early days of hospitalisation was completely different from that of discharge. The dyspnoea reported within the first days of the hospitalisation did not identify patients at higher risk of subsequent events, in contrast to discharge assessment. Moreover, the residual dyspnoea was an independent marker of poor outcome even after adjustments for well-known risk factors, including discharge NTproBNP and systolic blood pressure. This again confirms that the interpretation of a biomarker’s clinical meaning should not be based on its value only, but also on the clinical context and the stage of the natural history of the disease.27
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