Heart failure (HF) is the leading cause of multimorbidity, mortality, and health care costs worldwide (Go et al., 2013). HF is expected to become more prevalent as the population ages and advanced therapies increase survival rates. Importantly, approximately 80% of patients with HF are older than 65 (Go et al., 2013), and the incidence of HF doubles in each decade of life and eventually rises to 20% in patients older than 80 (Bui, Horwich, & Fonarow, 2011). Despite advances in diagnosis and management of HF, the HF prevalence in South Korea is estimated to double, increasing from 1.6% in 2015 to 3.35% in 2040 (Lee, Lim, Cho, & Park, 2016). Therefore, the aging HF population needs more attention with respect to management of prognosis and outcomes.
Frailty is a highly prevalent condition among older adults and specifically among those with cardiovascular disease (CVD; Denfeld, Winters-Stone, Mudd, Gelow, et al., 2017). Frailty is considered a biological syndrome associated with multisystem deterioration in physiological reserve (Song, Mitnitski, & Rockwood, 2010). Physical frailty proposed by Fried et al. (2001) has shown to be predictive of major negative health-related outcomes, including disability in activities of daily living, hospitalization, and mortality in older adults with HF (Goldfarb, Sheppard, & Afilalo, 2015; Rodríguez-Pascual et al., 2017). Furthermore, physical frailty manifests slowness and activity intolerance, which mirror the symptoms of HF (Joyce, 2016). Because of similarities in their manifestation, a common pathophysiological mechanism that links HF and physical frailty is thought to exist, such as pro-inflammatory state, although the relationship between HF and physical frailty remains unclear (Jha et al., 2015; Joyce, 2016). In fact, the constellation of muscle loss, weakness, and exhaustion has been a long-recognized component of HF (Joyce, 2016). In a study of 200 patients with HF with New York Heart Association (NYHA) classification II to III, 19% showed muscle wastage in a dual-energy X-ray absorptiometry scan (Fülster et al., 2013). However, according to a recent meta-analysis, physical frailty is not necessarily associated with aging or NYHA functional classification of HF (Denfeld, Winters-Stone, Mudd, Gelow, et al., 2017). Therefore, much information about risk factors and clinical consequences related to frailty has yet to be elucidated, although it is an important component in HF prognosis.
The combination of depressive symptoms and CVD in chronic diseases was the most widespread disease pattern identified in frail older adult women (Chang, Weiss, Xue, & Fried, 2012). As HF is one of the major CVDs, depressive symptoms can be a pivotal clinical characteristic for determining the vulnerability of physical frailty in older adults with HF. Depressive symptoms occurred more commonly in patients with HF during their illness and were reported as the key comorbidity that affected the prognosis and outcomes in older adults with HF (Gathright, Goldstein, Josephson, & Hughes, 2017; Rutledge, Reis, Linke, Greenberg, & Millis, 2006). On the other hand, depressive symptoms and physical frailty are prevalent reciprocally among community-dwelling older adults (Buigues et al., 2015; Collard, Comijs, Naarding, & Oude Voshaar, 2014; Freitag & Schmidt, 2016). Recent studies have revealed that the interaction between depressive symptoms and physical frailty in older adults can lead to adverse health outcomes such as lower quality of life, increased reliance on health care services, and increased morbidity and mortality (Lohman, Mezuk, & Dumenci, 2017; Soysal et al., 2017). Many previous studies have reported that depressive symptoms and physical frailty alone are associated with HF (Denfeld, Winters-Stone, Mudd, Hiatt, et al., 2017; Gathright et al., 2017; Hwang & Choi, 2016; Jha et al., 2015). However, simultaneous depression and physical frailty have not been studied in populations with HF. Therefore, an empirical study on depressive symptoms and physical frailty in older adults with HF as a vulnerable population is needed to identify the interaction between depressive symptoms and physical frailty based on the conceptual framework that depressive symptoms could be a predisposing characteristic of frailty (Chang et al., 2012; Collard et al., 2014; Jha et al., 2015).
Recently, a study reported the impact of frailty, anxiety, and depressive symptoms on the quality of life of older adults with HF in the Netherlands using a small sample and multidimensional frailty scale (Uchmanowicz & Gobbens, 2015). However, the relationship between depressive symptoms and physical frailty has not yet been determined in older adults with HF. As most of the studies to date have focused on biomedical factors associated with physical frailty in HF in the view of frailty as a geriatric syndrome (Denfeld, Winters-Stone, Mudd, Gelow, et al., 2017; Denfeld, Winters-Stone, Mudd, Hiatt, et al., 2017), there is a need to examine depressive symptoms as a psychological predictor to understand the relationship between depressive symptoms and physical frailty.
Based on previous studies, the current researchers hypothesized that depressive symptoms would be significantly associated with physical frailty in older adults with HF. The current study aimed to (a) identify the prevalence of depressive symptoms and physical frailty in older adults with HF within a cross-sectional investigation period, and (b) examine the impact of depressive symptoms on physical frailty in older adults with HF after adjusting for sociodemographic and clinical characteristics.
Study Design and Participants
The current study adopted a cross-sectional research design to describe the relationship between depressive symptoms and physical frailty in Korean older adults with HF. A convenience sample of patients with HF was recruited from the outpatient clinic of a general hospital in South Korea.
Between November 2016 and March 2017, patients who received post-discharge follow-up visits in the outpatient clinic were included in the study. Inclusion criteria for older adults with HF were: (a) age ≥60 years; (b) fluent in Korean; (c) diagnosed with HF by a cardiologist based on clinical history, echocardiographic findings, and the presence of symptoms/diagnosis for ≥6 months; and (d) alertness and willingness to participate in the study. Exclusion criteria were: (a) previously diagnosed with dementia or major depressive disorder, (b) being paralyzed or having physical impairment, and (c) life expectancy of ≤6 months.
Initially, researchers recruited 204 eligible patients because dropout was expected. Of the 204 patients, 12 participants declined to participate due to lack of time, and two faced language difficulties before consenting to participate. Consequently, 14 patients were excluded, and final data analysis included 190 patients.
To determine the appropriate sample size for the current study, a power analysis was performed using G*power 3.1 (Faul, Erdfelder, Buchner, & Lang, 2009) based on a previous study on frailty in older adults with depression (Soysal et al., 2017). It was determined that 186 patients were needed for a two-tailed analysis using logistic regression with a 0.05 alpha level, 90% power, and 2.64 odds ratio; therefore, the sample size was sufficient.
Sociodemographic and Clinical Characteristics. Based on previous studies (Son & Kim, 2017; Uchmanowicz & Gobbens, 2015), the current researchers chose to collect data on sociodemographic and clinical characteristics. Sociodemographic data (i.e., age, gender, education level, marital status, employment status) were obtained from standardized questions in a structured questionnaire. Clinical information was obtained from electronic medical records and included body mass index, duration of HF diagnosis, NYHA functional classification, physician-diagnosed comorbidities (i.e., hypertension, diabetes, cancer, heart attack, angina, asthma, chronic lung disease, arthritis, stroke, chronic renal failure), prescribed medication, and ejection fraction (EF). Prior to enrollment of participants, researchers identified patients with a history of depression before HF diagnosis.
Depressive Symptoms. Researchers used the Patient Health Questionnaire-9 (PHQ-9) to identify depressive symptoms in older adults with HF. The PHQ-9 is a self-report scale for screening depressive symptoms, and its validity in patients at primary care clinics in the United States has been established (Kroenke, Spitzer, & Williams, 2001). The scale has nine items based on Diagnostic and Statistical Manual of Mental Disorders criteria. Patients were asked to rate how often they experienced each symptom during the past 2 weeks on a scale from 0 (not at all) to 3 (nearly every day). The total scores range from 0 to 27, with higher scores indicating more severe depressive symptoms. PHQ-9 scores of 5, 10, 15, and 20 represent valid and easy-to-remember thresholds demarcating the lower limits of mild, moderate, moderately severe, and severe depression, respectively (Kroenke et al., 2001). Han et al. (2008) translated the PHQ-9 into Korean and standardized the Korean version (internal consistency: Cronbach's alpha = 0.86; test–retest reliability: r = 0.79 and p < 0.001; validity: correlation r = 0.74 and p < 0.01 [Geriatric Depressive Scale], and r = 0.77 and p < 0.01 [Beck Depression Inventory]). Furthermore, the PHQ-9 has been proposed as a valuable tool for screening depressive symptoms among Korean older adults with medical illness in a primary health care setting (Han et al., 2008). In addition, there is strong evidence for the PHQ-9 as a simple and useful questionnaire that can be self-administered or administered to older adults by health care professionals (Yoon, Lim, & Han, 2012). The current study calculated the distribution of PHQ-9 scores, with 0 to 4 indicating normal and >5 indicating depressive symptoms, as a score of 5 is the optimal cutoff for Korean older adults (Han et al., 2008; Yoon et al., 2012). Cronbach's alpha for the sample was 0.712.
Physical Frailty. To assess the status of physical frailty, researchers adopted the Korean version of the FRAIL (Fatigue, Resistance, Ambulation, Illness, and Loss of weight) scale (K-FRAIL; Jung et al., 2016). The K-FRAIL scale, based on the original FRAIL scale (Morley, Malmstrom, & Miller, 2012), was translated into Korean, and its validity was evaluated through the positive association with the number of items indicating impairment in the K-FRAIL and Frail Index (FI) as an assessment for frailty used the most (Jung et al., 2016). The K-FRAIL also includes five items and assigns scores from 0 to 5, with 1 point per item. Fatigue is assessed by asking patients the number of times they felt tired in the past 4 weeks, with responses of “most of the time” or “all of the time” scored as 1. Resistance is measured by asking if patients had any difficulty climbing 10 steps without resting or using aids. Ambulation is assessed by asking if patients had any difficulty walking several hundred yards alone and without aids. Responses of “yes” to questions on resistance and ambulation were each scored as 1. Patients were considered to have multiple illnesses if they reported a history of five or more of 11 total illnesses (i.e., hypertension, diabetes, cancer, heart attack, HF, angina, asthma, chronic lung disease, arthritis, stroke, chronic renal failure). Weight loss based on self-report was scored as 1 for patients with a weight decline of ≥5% within the past 12 months. The scale focuses on physical frailty, but does not require physical examination by a physician. The K-FRAIL originally classifies patients with a score of 0 as robust, pre-frail with a score of 1 to 2, and frail with a score ≥3. However, a previous study on frailty screening in community-dwelling older adults showed that the optimal cutoff point that achieved the maximum sensitivity and specificity for screening frailty in older Korean adults was ≥1 point on the K-FRAIL scale (Jang et al., 2017). Accordingly, the current study's researchers set the cutoff point at ≥1 to classify patients as robust (if the score was 0) or vulnerable (if the score was ≥1).
Data Collection and Ethical Considerations
The study protocol was reviewed and approved by an institutional review board. Patients were invited to participate in the study through telephone recruitment prior to follow up at the outpatient clinic. Written informed consent was obtained from patients who agreed to participate in the study at the outpatient clinic visit. Information included details about study aim, confidentiality and anonymity of information, and voluntary participation.
Collected data were analyzed using SPSS Statistics version 23. Descriptive statistics were used to summarize data for patient characteristics. Continuous data were presented as means with standard deviations. Categorical data were expressed as numbers with percentages. Chi-square and independent t tests were also performed. Multiple logistic regression was performed to identify the effect of depressive symptoms on physical frailty after adjusting for patients' baseline characteristics. All tests were performed at a statistical significance level of p = 0.05.
Prevalence of Depressive Symptoms and Physical Frailty by Patients' Characteristics
The mean age and duration of HF diagnosis of participants was 70.3 years (SD = 7.7 years) and 5.1 years (SD = 4.6 years), respectively. The prevalence of depressive symptoms was 30% (n = 57). A higher proportion of patients were significantly depressed if they had higher NYHA classification (p = 0.022), hypertension (p = 0.031), or diabetes (p = 0.009). The prevalence of physical frailty in the current sample with HF was 61.6% (n = 117). Patients were significantly more likely to be frail if they were older patients (p < 0.001), were women (p = 0.004), had a lower educational level (p = 0.001), were not married (p = 0.007), and were unemployed (p = 0.001). In addition, the following clinical categories had a higher proportion of frail patients: shorter duration of HF diagnosis (p = 0.034), higher NYHA classification (p = 0.020), and taking diuretics (p = 0.035). However, no differences were found in terms of their level of left ventricle EF and comorbidity (Table 1).
Depression and Physical Frailty Status by Patients' Characteristics (N = 190)
Differences in Physical Frailty Between Groups With or Without Depressive Symptoms
The mean score on the PHQ-9 in the current study was 3.77 (SD = 3.30). The mean scores of groups of individuals who were depressed and those who were not were 2.10 (SD = 1.43) and 7.68 (SD = 3.12), respectively.
The prevalence of physical frailty depending on depressive symptoms was 51.9% (n = 69) for the group of individuals who were not depressed, and 84.2% (n = 48) for the group of individuals who were depressed, which was a significantly different proportion (p < 0.001). The most prevalent component of frailty was fatigue (48.9%). The proportion of patients with one of the frailty items except for illness was significantly high in the group with depressive symptoms (Table 2).
Comparison of Physical Frailty Between Groups With and Without Depressive Symptoms (N = 190)
Impact of Depressive Symptoms on Physical Frailty
The logistic regression results predicting the presence of physical frailty are presented in Table 3. The unadjusted logistic analysis revealed that patients who were older, were women, had an educational level lower than middle school, were not married, were unemployed, had a shorter duration of HF diagnosis and higher NYHA classification, took diuretics, and had depressive symptoms were significantly more likely to be physically frail.
Predictors of Physical Frailty in Older Adults With Heart Failure (N = 190)
After adjusting for these characteristics, depressive symptoms strongly and only predicted an increased risk of physical frailty (adjusted odds ratio [OR] = 4.789, 95% confidence interval [1.996, 11.491], p < 0.001) compared to the absence of depressive symptoms.
To the best of the researchers' knowledge, the current study is the first to determine whether depressive symptoms predict the risk of physical frailty after adjusting for sociodemographic and clinical factors in Korean older adults with HF.
The study showed the prevalence of physical frailty to be approximately 61.6% in older adults with HF. This finding was higher than that of a previous review indicating the prevalence of frailty to be 4% to 59.1% in community-dwelling older adults (Collard, Boter, Schoevers, & Oude Voshaar, 2012) and that of a review indicating the prevalence of frailty to be 15% to 51% in older adults with HF who were referred to clinics (Afilalo et al., 2014). However, the identified frailty in the current study was lower than that in a previous study, which reported 89% frailty in older adults with HF in the Netherlands (Uchmanowicz & Gobbens, 2015). The varied prevalence rates of frailty may be due to different inclusion criteria for participants and different assessment tools of frailty for older adults with HF with diverse sociodemographic backgrounds (Jha et al., 2015). Despite the high prevalence of frailty as well as prognostic issues in older adults with HF, physical frailty has not been extensively studied worldwide (Afilalo et al., 2014). A critical cause of this circumstance may be the connection to aging and the complexity of the relationship between HF and physical frailty (Jha et al., 2015). Therefore, a validated and standardized physical frailty assessment tool is needed to clarify the concept of physical frailty and HF based on the diverse background of patients with HF (Denfeld, Winters-Stone, Mudd, Hiatt, et al., 2017; Joyce, 2016; McDonagh et al., 2018).
In the current study, 30% of older adults with HF exhibited depressive symptoms. According to existing literature, the prevalence of depression ranged from 24% to 68% in outpatients or inpatients with HF from Korea (Hwang & Choi, 2016), and from 13% to 77.5% among outpatients or inpatients with HF from several countries (Thomas et al., 2008). For older adults in general, rates of geriatric depression varied from 10% to 50% depending on primary care, institutional, or long-term care settings (Park & Unützer, 2011). These varying rates of depression may be due to the use of different screening tools, diverse settings, and inconsistent application of a scale.
The current study revealed that older adults with HF with depressive symptoms had approximately five times higher risk of physical frailty than those without depressive symptoms after controlling for sociodemographic and clinical characteristics. In addition, depressive symptoms alone increased the risk of physical frailty, regardless of their severity. These findings are in line with those of previous studies that indicate frailty is associated with depressive symptoms in older adults (Lohman et al., 2017; Soysal et al., 2017). Individuals who are depressed may be more pessimistic about health problems during the illness trajectory, perceive less control over physical health, and foresee a poorer prognosis of their current health than those who are not depressed (Gathright et al., 2017). Furthermore, depressive symptoms may lead to disregard of physical health and possibly frailty (Alosco et al., 2012; Lohman et al., 2017). To date, despite the important issues of depressive symptoms and physical frailty among older adults, data on the association between depressive symptoms and physical frailty in older adults with HF are limited. This lack of data may be attributed to the misconception that depressive symptoms and physical frailty in older adults with HF may be considered natural geriatric issues (Murad & Kitzman, 2012; Stein et al., 2012). The current study showed the high prevalence of depressive symptoms and physical frailty in older adults with HF and also provided important information that depressive symptoms are the most critical predictor of physical frailty in older adults with HF. Therefore, depressive symptoms should be assessed and managed as a comorbid condition for monitoring physical frailty in older adults with HF. Older adults with HF should be provided with appropriate HF management through direct assessment for physical frailty.
The K-FRAIL is a self-report assessment tool and therefore not entirely objective, although it is a validated tool for the Korean population. Because it is not entirely objective, caution should be exercised when interpreting the rates of physical frailty and applying the result of physical frailty assessments into practice. For example, as patients with congestive HF commonly experience fluid retention, the weight loss resulting in muscle wastage is potentially masked in this population (Jha et al., 2015). On the other hand, performance assessment, such as using grip strength dynamometer results, enables clear reproducibility but has low clinical applicability and feasibility. Therefore, the selection of appropriate frailty assessment for purpose and context is important. According to the definition of frailty (Morley et al., 2012), the susceptibility to frailty at initial HF diagnosis might be high, because patients at the time of HF diagnosis experience weakness of muscle and energy caused by decreasing cardiac function (Go et al., 2013). In fact, a previous review reported that older adults with immediate prevalent HF had a high burden of functional impairment associated with increased mortality (Murad et al., 2015). Therefore, the current results suggest that the status of physical frailty should be identified at an earlier stage of HF to prevent negative health outcomes, and detection of depressive symptoms in older adults with HF is useful to identify the risk of physical frailty at an earlier stage. In the current study, the most prevalent item of frailty was fatigue, which can overlap with other causes of physical exhaustion common in HF or depression (Goldfarb et al., 2015). Consequently, the current study can encourage health care providers to attentively monitor the onset of depressive symptoms and physical frailty at an early stage following diagnosis. More studies are needed to identify risk factors of physical frailty based on patients' sociodemographic and disease-related factors using a large prospective cohort design.
The current study has several limitations. First, this cross-sectional study used a convenience sample. Therefore, the sample might be biased. Second, as only patients from the outpatient clinic at a tertiary care referral center were included, it might be difficult to generalize the results to other clinical settings. In addition, the presence of depressive symptoms and physical frailty was assessed only once after 6 or more months had passed following HF diagnosis. Repeated assessment is required to identify patterns or changes in the illness trajectory. Finally, the study population was relatively young (enrollment criteria for age ≥60 years). Although mean age of participants was >70, this might be a confounding variable influencing the results.
Despite the extensive literature on physical frailty, little research has been conducted on the impact of depressive symptoms on physical frailty in older adults with HF. The current study revealed that older adults with HF who have depressive symptoms are much more likely to be frail. Therefore, early detection of depressive symptoms in older adults with HF would be useful to identify the status of physical frailty at an earlier stage of the disease, precipitate the development of well-designed patient-centered care, and eventually prevent negative health outcomes.
Replication and extension of this study in various settings and populations are crucial to verify the usefulness of the researchers' operational approach to physical frailty as well as depressive symptoms in older adults with HF. In addition, health care providers should consider assessments of depressive symptoms and physical frailty while estimating risk and making therapeutic decisions for HF management and quality of care.
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Depression and Physical Frailty Status by Patients' Characteristics (N = 190)
|Characteristic||n (%)||p Value||n (%)||p Value|
|Not Depressed (n = 133)||Depressed (n = 57)||Not Frail (n = 73)||Frail (n = 117)|
|Age (years) (mean [SD])||69.9 (7.6)||71.2 (8.0)||0.290||67.7 (6.7)||71.9 (7.8)||<0.001|
| Male||102 (76.7)||37 (64.9)||62 (84.9)||77 (65.8)|
| Female||31 (23.3)||20 (35.1)||11 (15.1)||40 (34.2)|
| Illiterate||21 (15.8)||11 (19.3)||9 (12.3)||23 (19.7)|
| Elementary school||36 (27.1)||21 (36.8)||13 (17.8)||44 (37.6)|
| Above middle school||76 (57.1)||25 (43.9)||51 (69.9)||50 (42.7)|
|Married||105 (78.9)||42 (73.7)||0.427||64 (87.7)||83 (70.9)||0.007|
|Employed||38 (28.6)||14 (24.6)||0.570||30 (41.1)||22 (18.8)||0.001|
|Body mass index (kg/m2) (mean [SD])||24.3 (2.9)||23.5 (3.4)||0.080||24.4 (3.2)||23.8 (3.0)||0.263|
|Duration of HF diagnosis (years) (mean [SD])||5.4 (4.9)||4.3 (3.8)||0.143||6.0 (3.8)||4.5 (5.0)||0.034|
| Class I||48 (36.1)||12 (21.1)||30 (41.1)||30 (25.6)|
| Class II||76 (57.1)||35 (61.4)||40 (54.8)||71 (60.7)|
| Class III||9 (6.8)||10 (17.5)||3 (4.1)||16 (13.7)|
|LVEF ≤40||86 (64.7)||40 (70.2)||0.461||48 (65.8)||78 (66.7)||0.897|
|Hypertension||59 (44.4)||35 (61.4)||0.031||36 (49.3)||58 (49.6)||0.972|
|Diabetes||33 (24.8)||25 (43.9)||0.009||19 (26.0)||39 (33.3)||0.287|
|CAD||98 (73.7)||41 (71.9)||0.803||56 (76.7)||83 (70.9)||0.382|
|Atrial fibrillation||8 (6.0)||0 (0)||0.108||2 (2.7)||6 (5.1)||0.713|
|ACEI/ARB||44 (33.1)||23 (40.4)||0.337||28 (38.4)||39 (33.3)||0.481|
|CCB||76 (57.1)||33 (57.9)||0.923||46 (63.0)||63 (53.8)||0.214|
|Beta-blocker||88 (66.2)||32 (56.1)||0.189||50 (68.5)||70 (59.8)||0.228|
|Diuretics||48 (36.1)||19 (33.3)||0.716||19 (26.0)||48 (41.0)||0.035|
Comparison of Physical Frailty Between Groups With and Without Depressive Symptoms (N = 190)
|Frailty Items (p Value)||n (%)|
|Not Depressed (n = 133)||Depressed (n = 57)|
|Fatigue—feeling tired during the past 4 weeks (<0.001)|
| No||85 (63.9)||12 (21.1)|
| Yes||48 (36.1)||45 (78.9)|
|Resistance—difficulty walking up 10 steps without aids (0.005)|
| No||116 (87.2)||40 (70.2)|
| Yes||17 (12.8)||17 (29.8)|
|Ambulation—difficulty walking several hundred yards (<0.001)|
| No||116 (87.2)||36 (63.2)|
| Yes||17 (12.8)||21 (36.8)|
|Loss of weight during 1 year (0.001)|
| No (<5%)||122 (84.2)||42 (73.7)|
| Yes (≥5%)||11 (15.8)||15 (26.3)|
|Illness—number of comorbidities (0.162)|
| No (<5)||132 (99.2)||55 (96.5)|
| Yes (≥5)||1 (0.8)||2 (3.5)|
|Risk of physical frailty total score (<0.001)|
| Not frail (0)||64 (48.1)||9 (15.8)|
| Frail (≥1)||69 (51.9)||48 (84.2)|
Predictors of Physical Frailty in Older Adults With Heart Failure (N = 190)
|OR||[95% CI]||p Value||OR||[95% CI]||p Value|
|Age (year)||1.082||[1.037, 1.130]||<0.001||1.049||[0.985, 1.118]||0.139|
|Gender (reference = men)||2.928||[1.388, 6.176]||0.005||1.460||[0.582, 3.660]||0.420|
|Education (reference = illiterate)|
| Elementary school||1.324||[0.493, 3.558]||0.577||1.796||[0.587, 5.490]||0.304|
| Above middle school||0.384||[0.162, 0.910]||0.030||1.029||[0.336, 3.149]||0.960|
|Spouse (reference = yes)||2.913||[1.304, 6.508]||0.009||1.454||[0.537, 3.936]||0.461|
|Job (reference = yes)||3.013||[1.561, 5.815]||0.001||1.618||[0.654, 4.005]||0.298|
|Duration of HF diagnosis (year)||0.932||[0.872, 0.997]||0.041||0.964||[0.893, 1.041]||0.348|
|NYHA class (reference = Class I)|
| Class II||1.775||[0.938, 3.357]||0.078||1.187||[0.552, 2.551]||0.661|
| Class III||5.333||[1.406, 20.225]||0.014||1.789||[0.379, 8.453]||0.463|
|Hypertension (reference = yes)||1.010||[0.563, 1.813]||0.972||1.751||[0.868, 3.532]||0.118|
|Diabetes (reference = yes)||1.421||[0.743, 2.719]||0.289||0.613||[0.276, 1.358]||0.228|
|Diuretics (reference = yes)||1.977||[1.043, 3.748]||0.037||0.627||[0.296, 1.332]||0.225|
|Depressed (reference = PHQ-9 <5)||4.947||[2.247, 10.889]||<0.001||4.789||[1.996, 11.491]||<0.001|