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European Journal of Heart Failure 2007 9(4):424-428; doi:10.1016/j.ejheart.2006.10.020
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© 2007 European Society of Cardiology

Self-assessed symptoms in chronic heart failure — Important information for clinical management

Inger Ekmana,*, Ewa Kjörkb and Bert Anderssonc

a Institute of Health and Care Sciences, The Sahlgrenska Academy at Göteborg University Box 457, SE 405 30 Göteborg, Sweden
b Department of Cardiology, Sahlgrenska University Hospital Sweden
c Department of Cardiology, Sahlgrenska University Hospital The Sahlgrenska Academy at Göteborg University Göteborg, Sweden

* Corresponding author. Fax: +46 317736050. E-mail address: inger.ekman{at}fhs.gu.se


   Abstract
Top
 Abstract
1. Introduction
 2. Methods
 3. Statistical analysis
 4. Results
 5. Discussion
 6. Conclusion
 References
 
Aim: To compare the patients' self-assessment of the severity of their symptoms with a physicians assessment and to evaluate the ability of self-assessed symptoms and ejection fraction (EF) to predict long-term survival in heart failure patients.

Method: Patients (n=332) evaluated symptoms using a self-administered functional classification scale (Specific Activity Scale, SAS), which is equivalent to the NYHA scale. EF and NYHA functional class was also recorded. All patients were followed over a 3-year period.

Results: Approximately 50% of patients classified themselves into SAS class I. In contrast, the cardiologists classified only 9% of the patients as NYHA class I. In patients with severe left ventricular dysfunction (EF≤0.35) SAS score (HR 1.48, 95% CI [1.03–2.12] p=0.03) and ACE inhibitor treatment (0.23 [0.11–.51], p=0.0003) independently predicted 3-year mortality in a multivariable analysis. EF was not predictive of mortality in the low EF group. Only age predicted long-term outcome in patients with preserved systolic function.

Conclusion: Patients' self-assessed symptoms and NYHA classification are not coherent. Left ventricular EF is of less importance in comparison with symptoms in chronic heart failure. Patients reporting less severe symptoms had a favourable 3-year prognosis, regardless of EF.

Key Words: Symptoms • Heart failure • Mortality • SAS • NYHA

Received June 1, 2006; Revised September 14, 2006; Accepted October 30, 2006


   1. Introduction
Top
 Abstract
 1. Introduction
2. Methods
 3. Statistical analysis
 4. Results
 5. Discussion
 6. Conclusion
 References
 
As recognised by the European Society of Cardiology (ESC), the European agency for the evaluation of medical products (EMEA) and the American Food and Drug Administration (FDA), relief of symptoms is an important target of therapy in patients with chronic heart failure (CHF) [1,2]. More importantly, symptom relief is one of the most important targets of care and treatment for the patients themselves [3,4]. Assessing symptoms, however, is considered a difficult task for clinicians. Furthermore, poor reproducibility of symptom assessment has been documented [5,6]. The New York Heart Association (NYHA) classification is an attempt to systematise, neutralise and structure symptom assessment in patients with heart failure [7,8]. However, the NYHA classification does not seem to be useful for clinicians in daily practice, the IMPROVEMENT survey found that only 9% of Swedish physicians in primary care knew what the classification system meant, and of these, only 48% actually used it [9]. Instead, clinicians elect to group patients with CHF as mild, moderate or severe [9]. This way of classifying heart failure is a mixture of the physician's knowledge of the severity of cardiac dysfunction, prior medical history and the physician's perception of the condition of the patient. Furthermore, the clinicians' NYHA assessment does not correlate with the patients' self-assessment of their symptoms [10]. In several studies, left ventricular ejection fraction (LVEF) has been found to be related to the risk of hospitalisation and death [1,11]. In clinical management, LVEF is an important and widely used prognostic variable. In the COMET study, we used a 5-point scale for patients to rate their perception of the severity of their symptoms, such as breathlessness and fatigue. These subjective and simple measurements predicted five-year morbidity and mortality [10].

Further studies are needed to explore the relationship between the pathology of heart failure and patient self-assessed symptoms.

Therefore, the aim of this study was to compare the patients' self-assessment of the severity of their symptoms with a physicians assessment and to evaluate the ability of self-assessed symptoms and ejection fraction (EF) to predict long-term survival in chronic heart failure patients.


   2. Methods
Top
 Abstract
 1. Introduction
 2. Methods
3. Statistical analysis
 4. Results
 5. Discussion
 6. Conclusion
 References
 
From 1995 onwards, a data protocol and a software program were used for registration of all patients referred to the nurse-monitored outpatient heart failure clinic in our hospital, for titration of heart failure drugs. All patients referred to the clinic using a simple admission protocol were first seen by a cardiologist. The protocol included data on the most recent ejection fraction (EF), the principal diagnosis, NYHA functional class and requested treatment and dosage. At the following nurse visits, signs and symptoms were recorded and blood pressure and heart rate were measured. Blood chemistry and ECG were taken when necessary. Data from these investigations were entered into the database. Further visits to perform dose titration of heart failure medication, were arranged by the responsible nurse as previously described [12].

At the first and last (when the target dose was reached) visits to the clinic, patients were asked to assess their symptoms using a questionnaire for self-administered functional classification (Specific Activity Scale, SAS) The SAS classification is similar to the four grades of the NYHA scale, but based on the most strenuous activity performed during a time when the patient estimated his or her functional level. The metabolic cost of specific physical activities was estimated. SAS I: ≥7 metabolic equivalents could be performed; SAS II: ≥5 and less than 7 metabolic equivalents could be performed; SAS III: ≥2 and less than 5 metabolic equivalents could be performed; SAS IV: less than 2 metabolic equivalents could be performed. [13] All patients who completed the SAS recordings between January 1995 and January 2001 were included in the study. All patients were followed-up until April 2004 and 3-year overall survival is reported. No patients were lost to follow-up. During the study period, measurement of BNP (Shionogi) was introduced as a routine method; data are therefore only available for a subset of the patients. Normal values<18.4 ng/L. [14]


   3. Statistical analysis
Top
 Abstract
 1. Introduction
 2. Methods
 3. Statistical analysis
4. Results
 5. Discussion
 6. Conclusion
 References
 
Data are presented as mean values (±standard deviation) or with 95% confidence intervals (CI). Survival curves were constructed using the Kaplan-Meier method while survival effects were assessed using a multivariable Cox regression analysis, with entry criteria set at p<0.05. Gender, age, EF, systolic blood pressure, heart rate and symptom scoring according to SAS classification at baseline (I to IV), and treatment with ACE inhibitors and beta-blockers at discharge, were entered into the equation. As drug treatment has a profound impact on outcome, we entered treatment at discharge instead of baseline into the equation. A main concept of this study was that NYHA is not an objective assessment of patients' symptoms, and therefore, NYHA class was not used in the survival equation. For further evaluation of the degree of left ventricular dysfunction, the study group was divided into two sub-groups based on the median EF, i.e. a low (≤0.35) and a high EF (>0.35) group. Regarding these sub-groups, survival curves were constructed comparing asymptomatic (SAS I) and symptomatic (SAS II-IV) patients. BNP data were not normally distributed, and the Kruskal-Wallis One Way Analysis of Variance on Ranks was used to test differences between groups, followed by pairwise comparisons using the Dunn's test. Statistics were calculated with SPSS for windows (version 12.0.1, Chicago, IL, USA).


   4. Results
Top
 Abstract
 1. Introduction
 2. Methods
 3. Statistical analysis
 4. Results
5. Discussion
 6. Conclusion
 References
 
During the study period, the clinic received 362 referrals for drug titration, of these, 332 patients completed the questionnaire on symptom assessment. Baseline characteristics of the patients according to EF are given in Table 1. Eight patients had no recent EF data and are therefore excluded from the survival analysis which included 324 patients. Patients with a higher EF were more likely to be women, were older, had higher systolic blood pressure and included fewer patients with ischaemic heart disease and dilated cardiomyopathy. Fewer patients in the high EF group were treated with beta-blockers at discharge from the clinic. Symptom assessment was similar between the two groups. Patients' self-assessment of their symptoms differed markedly from the NYHA classification (which was available in 307 patients) performed by the referring cardiologists (Fig. 1 and Table 2). Fifty-one percent of the patients in the low EF group and 52% in the high EF group classified themselves as SAS I. The cardiologists, on the other hand, classified only 6% of the patients in the low EF group and 12% of the patients in the high EF group as NYHA class I. NYHA-class estimation, as determined by the referring cardiologist, was performed a mean of 20±21 days prior to the first self-assessment. The mean time between the first and second self-assessment was 61±47 days. There were only minor changes in SAS scores between baseline and the last visit, with 81% vs. 74% of patients (p=0.58) considering themselves in functional class I-II respectively. Thus, despite the drug titration performed between the first and last visits, symptoms remained relatively stable.


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  		Table 1 Baseline characteristics

 


Figure 01
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  		Fig. 1 Functional classification in patients with high versus low EF admitted to the heart failure clinic, according to the referring physician (NYHA functional classification), and according to the patient's self-assessed symptoms (Specific Activity Scale, SAS). In both EF groups, there was a statistically significant difference in the proportions between grades of NYHA and SAS.

 


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  		Table 2 Patients self-assessment of symptoms (SAS) in relation to NYHA functional classification

 
In the total group of 324 patients increasing age (HR 1.04 [1.01-1.07], p=0.004), EF (0.98 [0.96-0.99], p=0.004) and treatment with ACE inhibitors (0.44 [0.23-0.81] p=0.009) independently predicted 3-year mortality. SAS score was not significantly associated with mortality in the total group. In patients with severe left ventricular dysfunction (EF≤0.35) SAS score (HR 1.48, 95% CI [1.03-2.12], p=0.03) and ACE inhibitor treatment (0.23 [0.11-0.51], p<0.001) independently predicted 3-year mortality in the multivariable analysis (Fig. 2). Three-year mortality in patients with a low EF was related to the SAS score: 17% (SAS I), 27% (SAS II), 32% (SAS III) and 50% (SAS IV). EF was not predictive of mortality in the low EF group (0.98 [0.92-1.03], p=0.42). In patients with preserved systolic function (EF>0.35) only age (HR 1.06, 95% CI [1.02-1.11], p=0.008) predicted long-term outcome. Three-year mortality in this group was low: 16 of 83 patients (SAS score I) and 13 of 76 patients (SAS score II-IV). SAS score (HR 0.80 [0.48-1.34], p=0.39) (Fig. 3) and EF (HR 0.97 [0.93-1.01], p=0.11) were not significantly associated with mortality.


Figure 02
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  		Fig. 2 Three-year total survival in patients with EF≤0.35, according to self-assessed symptoms. Curves are shown for asymptomatic patients (SAS I) versus patients with symptoms (SAS II-IV). There was a significant difference between the curves (log rank, p=0.043).

 


Figure 03
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  		Fig. 3 Three-year total survival in patients with EF>0.35, according to self-assessed symptoms. Curves are shown for asymptomatic patients (SAS I) versus patients with symptoms (SAS II-IV). There was no difference between the curves (log rank, p=0.72).

 
BNP data were available in 131 patients and was equally distributed between patients with SAS score I (n=65) and SAS scores II-IV (n=66). There was a significant difference between the four groups of patients: EF≤0.35 and SAS I; EF≤0.35 and SAS II-IV; EF>0.35 and SAS I; EF>0.35 and SAS II-IV, as assessed by ANOVA (p=0.009). As was noted in patients with low EF, patients with more severe symptoms (SAS II-IV) had higher BNP concentrations (Table 3). In the total group, more severe symptoms were associated with higher BNP values: SAS I, 152 (59-268) ng/L, n=65; SAS II, 178 (96-297) ng/L, n=42; SAS III-IV, 308 (136-485) ng/L, n=24, p=0.02 between groups.


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  		Table 3 BNP in relation to left ventricular function (EF) and symptom score (SAS)

 

   5. Discussion
Top
 Abstract
 1. Introduction
 2. Methods
 3. Statistical analysis
 4. Results
 5. Discussion
6. Conclusion
 References
 
Consistent with previous findings, our data show that patients' self-assessment of their symptoms predicts increased risk of death in CHF [10]. We also confirm findings from a previous study showing no association between the clinicians' assessment of patients NYHA classification and the patients' self-assessment of their functional ability [10]. This finding is probably related to the current basis of assessment and intervention from health providers, who assume that symptoms are signs of disordered somatic processes, despite the well-established fact that there is no correlation between, for example, left ventricular ejection fraction and symptoms [15,16]. Our finding that patients experiencing severe symptoms suggests poor outcome in patients with low EF, whereas the actual value of EF did not imply poor outcome, is another important piece in the puzzle of clinical assessment of patients with CHF. These results support the hypothesis that signs and symptoms do not always have a one-to-one relationship; for instance, in some patients severe ventricular dysfunction was established but no symptoms were observed, whereas other patients with ventricular dysfunction had severe symptoms. Similar results, in which it was difficult to show any relation between dyspnoea and pulmonary dysfunction in heart failure have also been reported [17,18]. The experience of symptoms might depend on several coexisting conditions and factors that could be of relevance for disease progression. For instance, depression is common in heart failure patients and has been associated with poorer outcome in cardiovascular disease [19]. Neurohormonal activation is complex and difficult to measure in individual patients. The degree of sympathetic or cytokine activation is an example of such systems that might produce adverse symptoms not directly observed in clinical investigations though known to be detrimental to long-term outcome. Although measurement of BNP was not the main focus of our study, the analysis of the natriuretic peptide BNP supports an association between biochemical alterations and symptoms. In the subset of patients in which BNP was measured, a clear trend was noted towards higher BNP levels in patients with more severe symptoms. This finding is in agreement with other studies in which natriuretic peptide levels have been shown to be related to NYHA class [20]. However, we are not aware of any study connecting BNP levels with patients' self-assessment of their symptoms. Measurement of BNP or Nt-proBNP is now routine in many institutions. It would therefore be of interest to evaluate the relationship between self-assessed symptoms and concentrations of natriuretic peptides. It is possible that additive information could be obtained from these two measurements, although self-assessed symptoms would be substantially cheaper and quicker to perform.

The recently published ACC/AHA Clinical Performance Measures for Adults with Chronic Heart Failure aim to enhance both objective and subjective measures in ways that reflect the complexity of the condition, to assist health providers in improving specific clinical care. Examples of suggested variables to be measured are symptoms such as fatigue and dyspnoea [21].

We are aware of several limitations to our study. Assessment of EF, NYHA, and SAS was not performed simultaneously. We did, however, have access to two SAS assessments, which were recorded approximately two months apart and which showed no difference, suggesting a remarkable stability. In addition, our study was performed as part of routine clinical procedure, in which results of EF and NYHA-assessment were available to the clinician when referral to the heart failure clinic was decided. Therefore, the results are applicable to normal clinical practice. Another limitation might be that our patients were recruited at a tertiary referral centre, and thus had a lower mean age than the general heart failure population, although older patients were also included.

We believe that in the clinical setting, our results could be important for individual patients. First, in patients with higher EF, neither symptoms nor EF correlated with outcome. This group had better survival, although elderly patients had poorer outcome. In contrast, patients with low EF and less severe symptoms had a favourable prognosis, suggesting that these patients could be told to expect a good prognosis. The most important finding in this study was that patients with low EF and severe symptoms could be expected to have a worse prognosis, indicating that these patients should be carefully monitored and that additional measures should be taken to improve outcome. More intense monitoring and medical treatment might be recommended, but also device therapy (such as ICD, CRT or heart transplantation) should be considered [1]. If such intensive measures are not applicable, terminal care might be planned that incorporates adequate health resources. A suggested algorithm for clinicians based ob SAS scores is depicted in Fig. 4.


Figure 04
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  		Fig. 4 Proposed algorithm for care and treatment of patients with chronic heart failure, before discharge from the hospital.

 

   6. Conclusion
Top
 Abstract
 1. Introduction
 2. Methods
 3. Statistical analysis
 4. Results
 5. Discussion
 6. Conclusion
References
 
Left ventricular EF is of less importance than self-assessed symptoms for predicting outcome in patients with CHF. That is, patients with either high or low EF with no symptoms fare equally well, whereas low EF in combination with symptoms is predictive of mortality within 3 years. These findings suggest that self-assessed symptoms should serve as the starting point when planning treatment and care for these patients.


   Acknowledgements
 
This study was partly financed by the Swedish Research Council and by grants from the Federal Government under the LUA/ALF agreement.


   References
Top
 Abstract
 1. Introduction
 2. Methods
 3. Statistical analysis
 4. Results
 5. Discussion
 6. Conclusion
 References
 

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