Patients with heart failure (HF) have poorer health-related quality of life (HRQOL) than do healthy people and patients with other chronic diseases1,2 and higher rates of hospitalizations, which account for the high costs of HF.3,4 Physical symptoms can affect both HRQOL and hospitalization. Approximately 90% to 100% of HF patients experience dyspnea,5 and 91% have multiple physical symptoms.6 Physical symptoms are 1 of the factors most strongly associated with HRQOL.1,7,8 In addition, approximately 90% to 100% of HF patients who visit emergency departments or are hospitalized experience physical symptoms.5,9 Thus, improvement in physical symptoms in this population may lead to improvement in HRQOL and reduction of hospitalization rates. To manage and improve physical symptoms effectively, the first step is to assess physical symptoms using a reliable and valid instrument.
Several instruments have been used to assess physical symptoms in patients with HF: the Memorial Symptom Assessment Scale (MSAS),10 the MSAS-Short Form,11 the MSAS-HF,12 the Heart Failure Somatic Perception Scale,13,14 the Dyspnea-Fatigue Index,15 and the Kansas City Cardiomyopathy Questionnaire (KCCQ).16 The MSAS was developed to assess multidimensional information on 32 physical and psychological symptoms with some additional open-ended questions for other symptoms, and the reliability and validity of this instrument have been supported in cancer patients.17,18 The MSAS-HF is the modified version of the MSAS to use for patients with HF and includes 32 physical and psychological symptoms.12 In patients with HF, number of symptoms, symptom prevalence, and symptom burden were associated with HRQOL.10–12 However, these instruments assess not only common HF symptoms but also psychological and other physical symptoms. Thus, it is difficult to evaluate the unique effects of common HF symptoms on patient outcomes using these instruments. The Heart Failure Somatic Perception Scale is used to assess the presence and severity of 18 common physical signs, symptoms, and the effects of dyspnea on daily activities in patients with HF.14 The Dyspnea-Fatigue Index has also been used to evaluate symptoms in patients with HF.15 It consists of 3 questions that assess only dyspnea and fatigue related to functional status.8,15 It is difficult to assess physical symptoms independently from functional impairment in the former and latter instruments, and the latter instrument does not cover some common HF symptoms. The Symptom and Symptom Stability subscales of the Kansas City Cardiomyopathy Questionnaire are used to measure the frequency, burden, and stability of physical symptoms but cover only swelling, fatigue, and dyspnea and do not include assessment of severity of symptoms.16 Thus, a reliable and valid physical symptom instrument is needed to assess and manage important common physical symptoms in patients with HF and examine their unique effects on patient outcomes.
Therefore, we developed the Symptom Status Questionnaire–Heart Failure (SSQ-HF), which is a modified version of the MSAS-HF.12 The authors of the current study selected the most common HF-related physical symptoms reported in the literature.6,12 The following items were selected because they have been noted to occur most frequently, with greatest severity, and cause the most distress among patients with HF: dyspnea during the day time, dyspnea when lying down, fatigue, chest pain, edema, sleeping difficulty, and dizziness or loss of balance.6,12 As in the MSAS-HF, the SSQ-HF measures the frequency, severity, and distress of each physical symptom.12
The current study was conducted to test the reliability and validity of the SSQ-HF. The first aim was to test the reliability and item homogeneity of the SSQ-HF using Cronbach’s α, item-total correlations, and interitem correlations. The second aim was to test construct validity using factor analysis and examine the hypothesized relationships between physical symptoms as measured by the SSQ-HF and depressive symptoms, HRQOL, and event-free survival. Depressive symptoms have been associated with physical symptoms in patients with HF. For instance, 2 recent studies have shown that higher levels of depressive symptoms were predictive of poor physical symptom status.8,19 Another study demonstrated a positive association between number of depressive symptoms and number of physical symptoms.11 Event-free survival was defined as the time from enrollment to first hospitalization, emergency department visit, or death. Most patients who were admitted to hospitals had physical symptoms.5 Therefore, hypothesis 1 was that the depressed group would have more severe physical symptoms than the nondepressed group would, controlling for age,8 gender,20 body mass index (BMI),21 comorbidities,22 and use of angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin II receptor blockers (ARBs), β-blockers, and diuretics.23,24 Hypothesis 2 was that physical symptoms would be associated with HRQOL, controlling for age,1 gender,25 comorbidities,26 New York Heart Association (NYHA) functional class,26 and depressive symptoms.27 Hypothesis 3 was that physical symptoms would predict event-free survival, controlling for age, gender, BMI,28 comorbidities,29 NYHA functional class,30 left ventricular ejection fraction (LVEF),30 medications (ACEIs or ARBs, β-blockers, and diuretics),31–33 and depressive symptoms.34
Design, Setting, and Sample
This was a prospective, observational study.27,35 Patients who met the following inclusion criteria were enrolled: (1) had a confirmed diagnosis of HF with preserved or nonpreserved systolic function, (2) stable doses of cardiac-related medications for 3 months or for 2 clinic visits, and (3) ability to speak and read English. Patients were excluded if they had any of the following: (1) HF originating from valvular heart disease, rheumatic disease, or pregnancy, (2) myocardial infarction or stroke within the past 3 months, or (3) other comorbid conditions that could considerably affect morbidity and mortality. Patients with severe cognitive impairment or psychiatric problems as determined by referring physicians or through medical record review were excluded because of potential difficulties with data collection. Sample size was calculated based on the recommendations (at least 10–15 subjects per item) by Nunnally and Bernstein36 and Pett and colleagues.37
Institutional review board approval for the study was obtained from appropriate institutions. Patients were enrolled from outpatient clinics in academic health centers or community hospitals in 3 Southern and Midwestern cities in the United States. Signed informed consent was obtained from all subjects. Data on physical and depressive symptoms, demographic and clinical characteristics, and HRQOL were collected at patients’ houses, clinics, or places that patients wanted to meet a research team member. Data on event-free survival were collected using monthly telephone calls with patients and verified using medical record review when possible. The mean (SD) follow-up time for the sample was 571 (347) days. When necessary, clinical characteristics were confirmed using medical record reviews by research team members.
Symptoms referred to patients’ perceptions of physical HF symptoms and were measured by the SSQ-HF. The instrument consists of 7 questions used to assess the presence, frequency, severity, and distress of common physical HF symptoms, including daytime dyspnea, dyspnea when lying down, fatigue, chest pain, edema, difficulty sleeping, and dizziness or loss of balance. Patients are asked to indicate the presence of each symptom during the past 4 weeks. If no symptom, the score is 0. If a patient has experienced a symptom, the patient is asked about the frequency, severity, and distress of the symptom. Responses on frequency range from 1 (less than once per week) to 4 (nearly daily); severity responses range from 1 (slight) to 4 (very much); and distress responses range from 0 (not at all) to 4 (very much). The total score for each physical symptom is calculated by summing the ratings for the symptom; scores range from 0 to 12. The total score on the instrument is calculated by summing the total scores of all the symptoms. Possible total scores range from 0 to 84, with higher scores indicating more severe symptoms.
Depressive symptoms were defined as cognitive, affective, and somatic depressive mood and were assessed using the Beck Depression Inventory II.38,39 The instrument consists of 21 items with 4 response options. Scores from 14 to 19 indicate mild depression; scores from 20 to 28, moderate depression; and scores from 29 to 63, severe depression.39 In the current study, patients were divided into 2 groups using a cut point of 14 (the depressed group, with a score ≥14, vs the nondepressed group, with a score <14); this cut point indicates at least mild depressive symptoms and has been used as a cut point for depressive symptoms.40 Internal consistency reliability has been supported in psychiatric outpatients.39 Validity has been supported by hypothesized relationships between the scores on this instrument and scores on other depression instruments in patients with HF41 and by factor analysis in college students.38 Cronbach’s α in the current study was .91.
Health-related quality of life was defined as an individual’s perception of how his/her clinical condition or treatment affected various aspects of daily life42 and was measured by the Minnesota Living With Heart Failure Questionnaire.43 This instrument was selected because it is the most commonly used to measure HRQOL in patients with HF, has well-established reliability and validity,43 and has been shown to be predictive of hospitalization and death in patients with HF.44,45 It consists of 21 items with 6 response options from 0 (no impact) to 5 (very much impact). The total score is calculated by summing all of the ratings; possible total scores range from 0 to 105, with higher scores indicating poorer HRQOL. Cronbach’s α values in several studies have been greater than .70, indicating acceptable internal-consistency reliability.43,46,47 In the current study, Cronbach’s α was .93. Construct validity has been supported by significant relationships to NYHA functional class and symptoms.46,47
Event-free survival was defined as the time from enrollment in the study to any first event of hospitalization, emergency department visit, or death due to any cause. A research team member called each patient by telephone monthly to collect data on hospitalization and emergency department visits. In addition, patients were given a hospitalization diary so that they could record hospitalizations before they forgot. Patients were asked to record information on hospitalizations and emergency department visits, including admission date, discharge date, hospital name, and the reason(s) for the events. If patients were admitted to recruitment hospitals, their hospitalization data were verified through medical record review. If patients were admitted to hospitals or visited emergency departments other than the recruitment sites, discharge notes from the hospitals, when available, were used to collect data on hospitalization and emergency department visit in addition to patient interviews. A trained research associate clarified, organized, and verified hospitalization data.
Data on death from any cause were collected using several methods, including medical record review and interviews with the patient’s family members or healthcare providers. The research team asked patients to provide 1 or 2 contact numbers to use if the team was unable to contact them after the patients gave written consent for the study. During monthly follow-ups, if the research team could not contact the patient, the team checked medical records to determine whether the patient had died. If the research team could not determine the patient’s death through medical record review, the team contacted 1 of the numbers that the patient provided to determine the patient’s event.
Data on sociodemographic characteristics (age, gender, and BMI) and clinical characteristics (comorbidities, NYHA functional class, LVEF, and medication) were collected using standard Sociodemographic and Clinical Questionnaires by patient interviews or in medical record review. New York Heart Association functional class was determined by trained research team members in in-depth face-to-face patient interviews.48 Comorbidities were assessed using the Charlson Comorbidity Index, which was included in the Clinical Questionnaire.49
Cronbach’s α was used to assess the internal consistency reliability of the SSQ-HF. An acceptable coefficient for Cronbach’s α is greater than .70.50 Item-total correlations and interitem correlations were used to assess item homogeneity.51 An acceptable coefficient for item-total correlations is greater than .30, indicating contribution of the item to the measure.51 Acceptable coefficients for interitem correlations are greater than .30 and less than .70.51 Items with coefficients of .30 or less mean lack of contribution of the item, and items with coefficients .70 or greater mean redundancy.
Common factor analysis was conducted because we assumed that variance in symptoms could be explained by the combination of the underlying common factors and the variance unique to symptoms.37 Factors were extracted based on the results of a scree plot, eigenvalues, and total variance.37 A loading score greater than 0.40 was used as a cut point.37
General linear model analysis and t test were used to test hypothesis 1, that the depressed group would have more severe symptoms than the nondepressed group would after controlling for age, gender, BMI, comorbidities, and medications. Hierarchical multiple regression analysis with enter method was used to test hypothesis 2, that physical symptoms would be associated with HRQOL after controlling for age, gender, comorbidities, NYHA functional class, and depressive symptoms. Cox regression analysis with enter method was used to test hypothesis 3, that physical symptoms would predict event-free survival after controlling for age, gender, BMI, comorbidities, NYHA functional class, LVEF, medications, and depressive symptoms. In Cox regression analysis, patients were divided into 2 groups based on their mean score on physical symptoms (a less severe physical symptom group, ≤24, and a more severe physical symptom group, >24). We used the mean because the data showed normal distribution.
Sociodemographic and Clinical Characteristics and Symptoms
A total of 249 patients with HF participated in the study (Table 1). More whites than nonwhites belonged to the more severe physical symptom group. The more severe symptom group also had a lower educational level, higher BMI, more comorbidities, more impaired functional status, and more depressive symptoms than did the less severe physical symptom group. There were 105 patients (42%) who experienced an adverse event during the follow-up period: 91 of the first events were hospitalizations, 8 were emergency department visits, and 6 were deaths. The mean (SD) score on the SSQ-HF was 24 (16).
Reliability and Item Homogeneity
Cronbach’s α for the instrument was .80, indicating adequate internal consistency. In the item-total correlation analysis, the correlation coefficients of all the items were greater than .30, indicating adequate contribution of all items to the measure (Table 2). The results of the interitem correlations are presented in Table 2. At least half of the correlation coefficients between all individual items and all other items were greater than .30 and less than .70, and all the correlation coefficients were less than .70.
In common factor analysis, the scree plot showed that the eigenvalue of 1 component was greater than 1.00, and 1 component was extracted and explained 46% of the total variance (Table 3). All of the items demonstrated moderate to strong loadings (>0.40), indicating acceptable construct validity.
Hypothesis 1 was supported: The depressed group had more severe physical symptoms than the nondepressed group did after controlling for age, gender, BMI, comorbidities, and medications (Table 4). Among the covariates, BMI and comorbidities were significantly associated with physical symptoms. Patients with depressive symptoms, greater BMI, and more comorbidities had more severe physical symptoms.
Hypothesis 2 was also supported: Physical symptoms were associated with HRQOL after controlling for age, gender, comorbidities, NYHA functional class, and depressive symptoms (Table 5). Among the covariates, age and depressive symptoms were associated with HRQOL. Patients with more severe physical symptoms, younger age, and depressive symptoms had poorer HRQOL.
Finally, hypothesis 3 was supported: Physical symptoms predicted event-free survival after controlling for age, gender, BMI, comorbidities, NYHA functional class, LVEF, medications, and depressive symptoms (Table 6). Among the covariates, comorbidities, LVEF, and ACEIs or ARBs predicted event-free survival. More severe physical symptoms, more comorbidities, lower LVEF, and not taking ACEIs or ARBs were associated with shorter event-free survival. The Figure shows the survival curves for prediction of event-free survival between less and more severe physical symptom groups.
This study supported the reliability and validity of the SSQ-HF. The findings of Cronbach’s α and item analyses showed acceptable internal consistency reliability and item homogeneity. All of the items contributed to the measure, and there was no redundancy among the items. Factor analysis and hypothesis tests strongly supported the construct validity of the instrument. Unlike the MSAS, the MSAS–short form, and the MSAS-HF,10–12 this instrument includes only common HF-related physical symptoms, but not psychological symptoms and other symptoms that are not common in this population. Thus, this instrument is relatively short compared with the instruments, but physical symptoms measured by this instrument were strongly associated with HRQOL and predicted event-free survival. Physical symptoms alone explained 56.4% of the variance in HRQOL in the current study. In this population, psychological symptoms, including depressive symptoms, are commonly included in studies and are measured by several reliable and valid instruments such as the Beck Depression Inventory II and the Patient Health Questionnaire-9.27,38,39,41 Thus, it is beneficial to provide a reliable and valid instrument to measure only physical symptoms. Compared with the Dyspnea-Fatigue Index,8,15 this instrument is relatively long but covers important common HF-related physical symptoms and can measure only physical symptoms separated from functional impairment. Functional impairment is commonly measured using NYHA functional class in HF studies and clinics.12,48 The SSQ-HF allows clinicians and researchers to assess the status of common physical symptoms and the unique effects on patient outcomes, including HRQOL and hospitalizations, among patients with HF.
The findings of the current study not only support the reliability and validity of this instrument but also demonstrate the importance of physical symptoms for patient outcomes. The findings of significant relationships between physical symptoms and depressive symptoms and between physical symptoms and HRQOL in the current study are consistent with the findings of previous studies.1,7,11,19 In patients with HF, poor HRQOL is an important issue and outcome.52 Some studies have examined physical symptoms after patients were hospitalized or visited emergency departments, and most hospitalized patients had common HF-related physical symptoms.5,9 For instance, 88% and 35% of patients who visited emergency departments had dyspnea and chest discomfort, respectively.9 In ambulatory and hospitalized HF patients, more than 90% had dyspnea.5 However, the predictive relationship of physical symptoms to hospitalization and mortality rates has rarely been examined in patients with HF. This study has shown that physical symptoms are a predictor of event-free survival. The findings of the relationships of physical symptoms to HRQOL and event-free survival imply that physical symptoms should be assessed and managed to improve HRQOL and event-free survival.
In this study, as expected, depressive symptoms are the strongest factor associated with physical symptoms. This finding was consistent with the findings of our previous and other stuies.8,11,19 Depressive symptoms measured by the Brief Symptom Invetory8,19 and the Geriatric Depression Scale–Short Form11 were associated with number of symptoms, overall symptom distress, and symptoms combined with functional impairment. These findings demonstrate that depressive symptoms are strongly associated with physical symptoms regardless of the instruments. Thus, depressive symptoms should be considered to manage physical symptoms properly.
Different types of interventions have been provided to improve depressive symptoms and physical symptoms, and the findings were inconsistent. Some interventions using a telehealth communication device, a small-group education program, including diet and exercise, or a comprehensive discharge program did not improve depressive symptoms.53–55 In contrast, a multidisciplinary comprehensive management program, including education about disease and symptom management, dietary counseling, adjustment of medications, and participation in an exercise program, improved depressive symptoms and reduced hospitalization rates.56 However, this study was not a randomized controlled trial. A home-based disease management program and a mindfulness-based psychoeducational program improved physical and depressive symptoms, but the effects were not profound.57,58 For instance, the home-based disease management program improved depressive symptoms, fatigue, and swelling but did not improve the prevalence of dyspnea.58 The mindfulness-based psychoeducational program improved physical symptoms and depressive symptoms, but the effects were not profound (P = .03 and .05, respectively).57 In the sessions of this study, mastering mindfulness skills and coping skills and group support were targeted. Various topics related to HF and its management, including diet, exercise, stress, communication, spirituality, health, and social support, were discussed during the sessions. The findings of these studies suggest that comprehensive management programs, including situational-specific education and counseling and psychological alternative therapy, may improve physical and depressive symptoms and, in turn, reduce hospitalization rates. However, further studies are needed to make more profound effects on physical and depressive symptoms.
Caution is needed in generalizing the findings of the current study to races other than whites because most of the participants were white. With other races, symptoms and the effects on HRQOL and event-free survival may be different from those reported in the current study. Also necessitating caution in interpretation of the data is the use of symptom recall during the past 4 weeks. Although this may present a difficulty for patients with HF, gathering data across a longer timespan can provide valuable data on symptom frequency.
In conclusion, the outcomes of our study provide preliminary evidence that clinicians and researchers who work with patients with HF can use the SSQ-HF to assess common HF-related physical symptoms and evaluate their effects on patient outcomes. Patients can easily fill out the questionnaire within 5 minutes after a brief explanation facilitating use during clinic visits. This instrument shows the presence, frequency, severity, and distress of 7 physical symptoms. Thus, it does not take much time for clinicians to review but provides more information about symptoms than NYHA functional class does. Further studies are needed to assess changes in symptoms over time and to determine whether these changes are associated with changes in HRQOL and event-free survival.
What’s New and Important
- This study presents a symptom instrument that clinicians and researchers can use to assess common physical symptoms in patients with HF.
- This study provides information about factors associating with physical symptoms in patients with HF.
- This study provides information about the predictive effects of physical symptoms on event-free survival.
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Keywords:Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved
heart failure; instrument; symptoms