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. 2023 Mar 7;25(4):542–549. doi: 10.1177/10998004231163186

Depression Predicts Cardiac Cachexia in Heart Failure Patients

Samira M Moughrabi 1,✉, Samer I Habib 2, Lorraine Evangelista 3
PMCID: PMC12372416  NIHMSID: NIHMS2104698  PMID: 36880715

Abstract

Background

Cardiac cachexia (CC) is associated with increased morbidity and mortality in persons with heart failure (HF). Compared to the biological underpinning of CC, little is known about the psychological factors. Thus, the overarching objective of this study was to determine whether depression predicts the onset of cachexia at 6 months in patients with chronic HF.

Methods

114 participants with a mean age of 56.7 ± 13.0 years, LVEF of 33.13 ± 12.30% and NYHA class III (48.0%) were assessed for depression using the PHQ-9. Body weight was measured at baseline and at 6 months. Patients who had ≥6% non-edematous unintentional weight loss were classified as cachectic. Univariate and logistic multivariate regression were used to examine the relationship between CC and depression, controlling for clinical and demographic variables.

Results

Cachectic patients (11.4%) had significantly higher baseline BMI levels (31.35 ± 5.70 vs. 28.31 ± 4.73; p = .038), lower LVEF (mean = 24.50 ± 9.48 vs. 34.22 ± 12.18, p = .009), and depression scores (mean = 7.17 ± 6.44 vs. 4.27 ± 3.98, p = .049) when compared to their non-cachectic counterparts. In multivariate regression analysis, depression scores (β = 1.193, p = .035) and LVEF (β = .835, p = .031) predicted cachexia after controlling for age, gender, body mass index, VO2 max, and New York Heart Association class and accounted for 49% of the variance in Cardiac cachexia. When depression was dichotomized, depression and LVEF predicted 52.6% of the variance in CC.

Conclusion

Depression predicts CC in patients with HF. Additional studies are needed to expand the knowledge of the role of the psychological determinants of this devastating syndrome.

Keywords: heart failure, wasting, depression, cardiac cachexia

Introduction

Cardiac cachexia (CC) is a devastating yet underrecognized complication of heart failure (HF; Anker et al., 1999; 2003; Valentova et al., 2020). The syndrome affects 10–39% of HF patients increasing their 1-year mortality rate by 50% (Anker, Ponikowski, et al., 1997; Valentova et al., 2020). Progressive weight loss and tissue wasting, particularly the muscles are distinct features of CC. Non-edematous, unintentional weight loss of more than 6% of the previous weight within 6 months in the absence of other severe diseases has been the most commonly used definition of CC (Lena et al., 2019; Valentova et al., 2020). Muscle abnormality’s distinct features manifest in advanced myocardial and physical dysfunction, severe exercise intolerance, marked fatigue and dyspnea at low exercise levels, and symptom severity. Cachexia in HF correlates with hemodynamic deterioration and independently predicts poor prognosis, increased admission rates and length of stay (LOS), and survival (Anker et al., 2003; Anker, Ponikowski, et al., 1997; Anker, Swan, et al., 1997; Cicoira et al., 2001; Lena et al., 2019; Valentova et al., 2020).

Depression is a common comorbidity that often goes unnoticed because of the overlapping signs and symptoms with HF (Liguori et al., 2018). Compared to the general population, depression is more prevalent and predicts poorer health, worse disease, physical symptoms, poorer functional status, and decreased quality of life in HF patients (Carels, 2004; Rumsfeld et al., 2003; Vaccarino et al., 2001). Depression increases the risk for new HF, repeated hospitalization and short- and long-term mortality independent of HF severity, cardiovascular risk factors, and myocardial events (Abramson et al., 2001; Bobo et al., 2020; Rumsfeld et al., 2005; Vaccarino et al., 2001).

Significant strides have been made in understanding the biological underpinning of depression and CC. Pathophysiological pathways that involve the HPA axis and immune system leading to the overproduction of inflammatory cytokines and stress neurohormonal proteins are currently established as predictors of poor outcomes in CC and in depressed patients with cardiovascular disease (Lena et al., 2019; Stapel et al., 2022). Compared to our understanding of their biological underpinning, the relationship between CC and depression remains less understood. Thus, the overarching objective of this study was to determine whether depression predicts the onset of cachexia in patients with chronic HF. The authors hypothesized that depression increases the risk and is predictive of CC onset at 6 months.

Methods

Study design and patient population

This study employed a longitudinal correlational design utilizing a convenience sample of 114 patients being followed in a tertiary, university-affiliated HF clinic. Patients were invited to participate in the study by their cardiologist or nurse practitioner. Inclusion criteria for participation included: diagnosis of HF over 6 months with an LVEF ≤40% documented by an echocardiogram or radionuclide ventriculography within the previous 6 months, age 18 years or older, ability to read, write, and speak English, and absence of a decompensated state, or any other primary cachectic state (e.g., end-stage liver, pulmonary, or renal disease, malignancy, acquired immunodeficiency syndrome). Approval from the corresponding Institutional Review Board was obtained, and all patients signed informed consents.

Procedures

At the initiation of the study, the baseline body weight and height of participants were measured during the patients’ routine cardiology follow-up visit. The weight scale and stadiometer were calibrated before each use, following the calibration guidelines provided by the manufacturers. After 6 months and again during the patients’ routine clinic follow-up visits, body weight measurements were repeated to determine the onset of CC. Patients who lost at least 6% of their baseline weight at 6 months were classified as cachectic. The patient’s BMI, height-adjusted weight, and index of total body obesity was calculated as the weight in kilogram divided by height in square meters at baseline and 6 months.

Depression was assessed using the Patient Health Questionnaire-9 (PHQ-9) at baseline during their cardiology visit. The PHQ-9 is the depression scale of the self-reported PHQ that is used to diagnose depressive disorders and assess depressive symptoms and severity in different medical settings (Kroenke et al., 2001; Martin et al., 2006). This questionnaire consists of nine questions asking participants how frequently they have been bothered by certain problems (i.e., little interest or pleasure in doing things, feeling depressed, trouble falling/staying asleep or sleeping too much, etc.) over the past 2 weeks. Questions are answered using a Likert scale from 0 (not at all) to 3 (nearly every day) with a cumulative overall score ranging from 0 to 27. Criterion and construct validity were established against independent structured mental health professional interviews, the 20-item Short-Form General Health survey, and sick days and clinic visits. PHQ-9 scores ≥10 have a sensitivity of 88% and a specificity of 88% for major depression, whereas scores of 5, 10, 15, and 20 correspond to mild, moderate, moderately severe, and severe depression, respectively. The reliability and validity of the PHQ-9 as a diagnostic tool in assessing depression severity have been well documented (Kroenke et al., 2001; Martin et al., 2006). The Cronbach’s alpha for PHQ-9 for the current study was 0.77.

Demographic information was collected through a self-administered questionnaire. Participants were asked about their age, sex. race, marital status, education, current employment status and annual income. Information on medical history (e.g., etiology of HF, presence of comorbidities, medications, smoking, and alcohol use) was obtained through self-report and verified by chart reviews. Results of diagnostic tests (e.g., echocardiogram, cardiopulmonary exercise test) and information related to the patient’s current clinical status (e.g., New York Heart Association [NYHA] class, LVEF, peak oxygen consumption (VO2 max.) at baseline was obtained through medical records review.

Data Analysis

Data were analyzed using SPSS for Windows (version 27.0, SPSS, Inc, Chicago, Ill). Descriptive statistics were used to describe study variables, including means, standard deviations, and percentages. Continuous variables were checked for normal distribution using the Kolmogorov-Smirnov test. Normality and equal variances were not satisfied for depression scores, thus natural log transformation was applied. Student’s t-test and Mann-Whitney U were used to comparing cachectic and non-cachectic groups on parametric and non-parametric variables, respectively. The Bonferroni correction was applied to correct for multiple univariate comparisons. Univariate analyses using Pearson product moment or Spearman Rho correlation were conducted as appropriate to examine the unadjusted relationship between CC and sociodemographic, clinical, and medical characteristics. Variables that achieved univariate significance of <0.10 and variables that were considered theoretically important in the literature were included in multivariate regression analyses. A hierarchical multivariate logistic regression using forced variable entry was conducted to examine the relationship between CC and depression. Variables were entered in blocks as covariates with demographic characteristics (age, sex) entered first, followed by clinical variables (baseline weight, VO2 max, NYHA class, LVEF), and finally, depression scores were entered last. The same regression model was repeated with depression as a categorical predictor of CC. Criteria for entry and removal of variables were determined by the likelihood ratio test with enter and remove values set at p ≤ 0.05 and p ≥ 0.100, respectively.

Results

The mean age of the 114 participants was 56.70 ± 13.00 years. The sample primarily consisted of Caucasians (68%), males (68.5%), and 75% were unemployed. Most participants had NYHA II (31.0%) to III (48.5%) with a mean LVEF of 33.13 ± 12.30% and were diagnosed with dilated and ischemic cardiomyopathy (56.8% and 32.4%, respectively). Overweight and obesity were common in this sample with 77.0% had BMI levels >25. At 6 months, 13 (11.4%) participants lost at least 6% of their baseline weight and were classified as cachectic with an average weight loss of 9.9%. The mean depression score of the sample was 4.58 ± 4.37, and 10% were found to have PHQ-9 scores of ≥10.

Both cachectic and non-cachectic patients were comparable in their sociodemographic and most of their clinical characteristics (Table 1). Patients who developed CC had significantly higher BMI at baseline (31.35 ± 5.70 vs. 28.31 ± 4.73; p = .038) than those who remained non-cachectic. Cachectic patients also had lower LVEF (24.50 ± 9.48 vs. 34.22 ± 12.18; p = .009) and higher baseline depression scores (7.17 ± 6.44 vs. 4.27 ± 3.98, p = .049) than their counterparts. No significant difference in NYHA and VO2 max was found between both groups. The unadjusted univariate analyses (Table 2) showed that baseline LVEF (r = −.276, p = .004) and depression scores (r = .208, p = .045) were significantly associated with CC. In the multivariate regression model (Table 3) that included age, gender, NYHA class, VO2 max, baseline BMI, and depression scores as the independent variables, both depression scores and LVEF predicted cachexia and accounted for 49% of the variance in CC. Participants with higher depression scores (β = 1.193, p = .035) and lower LVEF (β = .835, p = .031) were more likely to become cachectic at 6 months Patients with lower LVEF were also at increased risk to develop cachexia after 6 months. These relationships remained significant when depression was dichotomized with depression and LVEF predicting 52.6% of the variance in CC (Table 4).

Table 1.

Differences in Patient Characteristics Between Cachectic and Non-Cachectic Groups (N = 114).

Cachectic N = 13 Non-cachectic N = 101 p-value
Age, (mean ± SD) 57.70 ± 15.01 56.04 ± 12.83 .688
Sex, % .243
Male 83.3 66.7
Female 16.7 33.3
Race, % .792
Caucasian 77.8 67.0
Hispanic 11.1 11.4
Other races 11.1 21.6
Education (mean ± SD) 14.90 ± 12.03 14.10 ± 3.21 .518
Non-smokers % 100 89.6 .248
Medications %
 ACE inhibitors 66.7 72.5 .676
 Beta blockers 91.7 93.9 .768
 Diuretics 83.3 78.6 .703
 Digoxin 33.4 46 .410
 Statins 83.4 73.5 .461
 Heart failure etiology % .478
 Non-ischemic 58.4 68.7
 Ischemic 41.7 30.7
 Employment % .132
 Employed 16.7 34.0
 Unemployed 83.3 66.0
 Atrial fibrillation 36.4 36.9 .969
 Hypertension 36.4 45.2 .580
 Diabetes 33.3 24.7 .522
 PHQ-9 (mean ± SD) 7.17 ± 6.44 4.27 ± 3.98 .049*
 BMI (baseline), (mean ± SD) 31.35 ± 5.70 28.31 ± 4.73 .038*
 BMI (6 months), (mean ± SD) 28.15 ± 5.22 28.94 ± 4.65 .575
 VO2 max 11.92 ± 4.57 10.16 ± 3.94 .216
 LVEF (mean ± SD) 24.5 ± 9.48 34.22 ± 12.18 .009*
 NYHA class 2.80 ± 0.79 2.59 ± 0.80 .442
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Note. *p < 0.05.

Table 2.

Univariate Correlation Matrix for Sociodemographic, Clinical, and Depression with Cardiac Cachexia.

Weight Loss >6% LVEF BMI (Baseline) BMI (6 months) Gender Age NYHA Class VO2 max
LVEF −.276
.004**
BMI (baseline) .184 .057
.067 .583
BMI (6 months) −.073 .090 .908
.471 .389 .000**
Gender −.111 .214 −.141 −.144
.244 .027* .170 .161
Age .068 .158 .050 −.005 −.144
.482 .105 .631 .961 .135
NYHA class .062 −.163 .127 .108 .019 .219
.558 .127 .242 .323 .857 .038*
VO2 max .118 .046 −.062 −.178 −.054 .017 −.243
.280 .676 .573 .103 .623 .879 .027*
PHQ-9 score .208 .062 .093 .035 −.147 .033 .217 −.139
.045* .564 .411 .758 .160 .756 .056 .241
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Note. **p < 0.01; *p < 0.05 level; top row of each variable shows the correlation, bottom row shows the p value.

Table 3.

Full Multiple Regression Model of Cardiac Cachexia with Depression as a Continuous Predictor.

Beta p value
Sex 1.675 .715
Age 1.057 .170
BMI 1.185 .195
VO2 max 1.240 .129
LVEF .835 .031*
NYHA .499 .153
PHQ-9 score 1.193 .035*
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Note. R2 = .490, p = .007; *p < 0.05.

Table 4.

Full Multiple Regression Model of Cardiac Cachexia with Depression as a Categorical Predictor.

Beta p-value
Sex 1.888 .614
Age 1.0622 .147
BMI 1.218 .136
VO2 max 1.293 .078
LVEF .832 .024*
NYHA .462 .140
Depression symptoms 22.095 .014*
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Note. R2 = .526, p = .004; *p < 0.05.

Discussion

The current literature describes CC as multifactorial syndrome, involving malabsorption, insufficient dietary intake, metabolic dysfunction, physical inactivity and deconditioning, impaired skeletal muscle perfusion, and heightened inflammation (Anker, Clark, et al., 1997a; Anker et al., 1999; Hweidi et al., 2021; Lena et al., 2019; Selthofer-Relatić et al., 2019; Valentova et al., 2020). To the best of our knowledge, this study is the first to explore the psychological determinants of cachexia in HF patients. The novel results that a relationship exists between cachexia and depression, suggest the importance of mental health as a risk to CC in HF. Together, depression and LVEF synergically interact to predict cachexia onset after 6 months, independent of age, gender, NYHA class, VO2 max, and baseline BMI. These observations are consistent with previous findings showing that depression increases the risk of poor outcomes when added to LVEF and VO2 max (Jünger et al., 2005). In other studies, depression alone was even a stronger predictor of mortality, hospitalization, worsening of HF symptoms, physical and social function, and quality of life (Carels, 2004; Rumsfeld et al., 2003; 2005; Sullivan et al., 2004a; Vaccarino et al., 2001). In congruence with these observations, the results of this study suggest that depression may present HF patients with additional clinical (deterioration in LVEF, NYHA, symptoms, physical functioning) and behavioral (treatment non-adherence, physical inactivity) risks leading to immune-inflammatory activation that in turn, predispose them to CC (Carels, 2004; Qiu et al., 2021; Rumsfeld et al., 2003; Sullivan et al., 2004a; Vaccarino et al., 2001). Disruption of anti-/pro-inflammatory cytokine production is a key player in HF that results in new HF onset, reduced LVEF, poor functional status, progressive deterioration of heart function and other organs and tissues, and cachexia (Anker, Clark, et al., 1997; Anker et al., 1999; Cesari et al., 2003; Deswal et al., 2001; Suleiman et al., 2006). In cancer patients, a complex relationship involving the immune system has been hypnotized to relate depression with cachexia (Illman et al., 2005; Menzies et al., 2005), but this relationship remains meagerly unfolded in patients with HF.

Consistent with other studies, obesity was common in this sample, regardless of developing cachexia (Ely et al., 2020). Castillo-Martinez et al. (2005) prospectively found high overweight and obesity rates among their participants who developed CC at 6 months. The authors suggested that the lower physical activity levels reported by these cachectic patients could explain the high incidence of obesity. Although VO2 max did not predict CC and physical activity was not measured in this sample, the same postulation may explain the higher incidence of obesity among our cachectic patients who had lower baseline LVEF than the non-cachectic patients. Similar to depression (Carels, 2004; Qiu et al., 2021; Rumsfeld et al., 2003; Sullivan et al., 2004; Vaccarino et al., 2001), decreased LVEF is associated with lower functional capacity (Davos et al., 2003) and exercise levels due to dyspnea and marked fatiguability (Anker, Swan, et al., 1997) Thus, obesity in HF may not necessarily indicate the absence of cachexia and muscle wasting (Ge et al., 2022; Selthofer-Relatić et al., 2019) and might be explained by decreased physical activity due to the decreased LVEF and advanced HF.

Alternatively, the heightened inflammation state associated with obesity, and depression (Ambrósio et al., 2018), may explain the increased risk for cachexia among participants with higher BMI at baseline. Higher BMI levels were found in depressed patients, with inflammation partially accounting for the relationship between BMI and depression. It was also suggested that depression promotes obesity through adverse behavioral processes (e.g., physical activity), which stimulate an inflammatory cascade from the liver and fat tissues (Dragan & Akhtar-Danesh, 2007; Miller et al., 2002). Abnormally high levels inflammatory proteins were observed in depressed HF patients, with and without HF (Ferketich et al., 2005; Miller et al., 2002; Moughrabi et al., 2014; Suarez et al., 2003), with an increased depression risk by 5-fold risk that did not improve with adequate antidepressant treatment. These findings suggest that inflammation is a key player in the pathology of depression (Moorman et al., 2007). Further studies are needed to verify our findings and expand our understanding of psycho-behavioral and biological determinants of CC.

Limitations

The small sample number, especially in the cachectic group, could have reduced the statistical power; therefore, detection of significance in some relationships with cachexia may have been hindered. Because most of the study participants were men and Caucasians, our sample may not represent the general HF population and the results may be limited to HF populations with similar characteristics. Future studies should consider representation of more women and participants with diverse ethnic backgrounds. The use of self-reported expression tools at the initiation of the study may have resulted in underreporting of depressive symptoms at baseline and any change in these symptoms over time in this sample.

Conclusion

Important advances have been made to expand knowledge on CC, particularly regarding its biological underpinning. To the best of our knowledge, this study is the first to examine the psychological side of cachexia in the setting of HF. The results that depression combined with the severity of HF are predictors of CC may be explained by several shared pathways and symptomatologies that have been found to link depression to HF patients leading to poor outcomes. The shared inflammatory processes established as an important underpinning in depression and cardiac failure have gained increased attention. In addition to behavioral factors, inflammation may provide one conceivable explanation for the relationship between cachexia and depression in patients with HF. Nonetheless, this relationship is more complex, and much remains to be understood. Our findings lay the ground for larger prospective studies that would increase the understanding of this syndrome. Until these studies emerge, results from this study could provide an opportunity for early identification of depressed HF patients who might be at risk for cachexia.

Footnotes

Author Contributions: Moughrabi, S.M. contributed to conception and design, contributed to analysis, drafted manuscript, critically revised manuscript, gave final approval agrees to be accountable for all aspects of work ensuring integrity and accuracy. Habib, S. contributed to conception, contributed to interpretation, drafted manuscript, critically revised manuscript, gave final approval agrees to be accountable for all aspects of work ensuring integrity and accuracy. Evangelista, L. contributed to conception and design, contributed to interpretation, critically revised manuscript, gave final approval agrees to be accountable for all aspects of work ensuring integrity and accuracy.

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Samira M. Moughrabi https://orcid.org/0000-0002-0721-2917

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