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Karl-Heinz Ladwig, Thomas C Baghai, Frank Doyle, Mark Hamer, Christoph Herrmann-Lingen, Evelyn Kunschitz, Cédric Lemogne, Margarita Beresnevaite, Angelo Compare, Roland von Känel, Hendrik B Sager, Willem Johan Kop, Mental health-related risk factors and interventions in patients with heart failure: a position paper endorsed by the European Association of Preventive Cardiology (EAPC), European Journal of Preventive Cardiology, Volume 29, Issue 7, May 2022, Pages 1124–1141, https://doi.org/10.1093/eurjpc/zwac006
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Abstract
The prevalence and public health burden of chronic heart failure (CHF) in Europe is steadily increasing mainly caused by the ageing population and prolonged survival of patients with CHF. Frequent hospitalizations, high morbidity and mortality rates, and enormous healthcare costs contribute to the health-related burden. However, multidisciplinary frameworks that emphasize effective long-term management and the psychological needs of the patients are sparse. The present position paper endorsed by the European Association of Preventive Cardiology (EAPC) provides a comprehensive overview on the scientific evidence of psychosocial aspects of heart failure (HF). In order to synthesize newly available information and reinforce best medical practice, information was gathered via literature reviews and consultations of experts. It covers the evidence for aetiological and prospective psychosocial risk factors and major underlying psycho-biological mechanisms. The paper elucidates the need to include psychosocial aspects in self-care concepts and critically reviews the current shortcomings of psychotherapeutic and psycho-pharmacological interventions. It also highlights the need for involvement of psychological support in device therapy for patients with HF and finally calls for better palliative care in the final stage of HF progression.
Introduction
Heart failure (HF) is a major public health challenge worldwide. The European Society of Cardiology defines HF as a clinical syndrome characterized by symptoms (e.g. breathlessness, ankle swelling, tiredness, and fatigue) and/or signs (e.g. elevated jugular venous pressure, hepatojugular reflux, and a third heart sound) caused by a structural and/or functional cardiac pathology, leading to reduced cardiac output.1 The diverse clinical presentations of HF can be described in terms of three broad dimensions: the role of left ventricular function, the timing of HF symptoms, and functional limitations related to HF. The main terminology used to describe HF subtypes is related to the measurement of left ventricular ejection fraction (LVEF). Patients with signs and/or symptoms of HF are grouped into those with (i) HF with preserved LVEF (≥50%, HFpEF), (ii) HF with mid-range reduced LVEF (40–49%, HFmrEF), and HF with reduced LVEF (<40%, HFrEF).1 Another frequently used terminology related to HF refers to the time course of HF. Patients who suffer from HF for already longer periods are often classified to have ‘chronic HF (CHF)’. Chronic stable HF may worsen/decompensate acutely resulting in aggravation of symptoms/signs, often leading to hospital admission. De novo HF may also present acutely (e.g. in the setting of acute myocardial infarction) or in an incremental fashion (e.g. patients with dilated cardiomyopathy).1 A third broadly implemented terminology relates to the severity of symptoms and functional limitations usually described by the New York Heart Association (NYHA) functional classification.2 It is important to emphasize that these three dimensions of CHF do not necessarily overlap (e.g. left ventricular function measures in HF correlate poorly with symptom severity).1 These differences in the dimensions of HF are attributable to compensation mechanisms in cardiac structure and function and patients also adjust their daily behaviours to manage their symptoms or under-report the severity of their symptoms, resulting in poor correspondence between HF-related measures such as measures of left ventricular function, chronicity of HF, and functional limitations.
Heart failure is caused by various aetiologies which can be grouped into underlying pathologies that lead to: (i) diseased myocardium causing systolic and/or diastolic ventricular dysfunction (e.g. ischaemic heart disease), (ii) abnormal loading conditions (e.g. hypertensive cardiomyopathy, abnormalities of the valves, pericardium, and endocardium), and (iii) arrhythmias (e.g. atrial tachyarrhythmias).1
The prevalence and public health burden of chronic HF in Europe is steadily increasing. A recent analysis of health records of 4 million individuals from the UK Clinical Practice Research Datalink evidenced an increase in the absolute number of prevalent HF cases of 23% from 2002 to 2014 mainly caused by the ageing population and prolonged survival of patients with HF, despite a decrease of HF incidence by 7%.3 Socioeconomically deprived individuals were more likely to develop HF and did so earlier in life.3 The high individual and societal burden of HF are associated with frequent hospitalizations, high morbidity and mortality rates, and enormous healthcare costs.4 However, many patients with CHF are not receiving optimal care with a multidisciplinary approach that emphasizes effective long-term management and the psychological needs.5–7
Although substantial progress has been made in recent years particularly within cardiac rehabilitation,7 psychosocial risk factors, and mental health-related issues in HF remain often under-diagnosed and hence undertreated.1 To address this issue, the European Association of Preventive Cardiology (EAPC) convened a task force with the remit to comprehensively review the published evidence on the role of psychosocial and psychobiological risk factors for incident HF and HF progression, and identify areas in which these factors could be used to optimize treatment in patients with chronic HF. This paper provides expert recommendation resulting from the EAPC Task Force discussion on how to improve self-care and other health behaviours and outline interventions that target the psychosocial correlates of chronic HF, including the importance of palliative care and advanced care planning.
Psychosocial risk factors for incident chronic heart failure and clinical outcomes in patients with chronic heart failure
Psychosocial risk factors for incident chronic heart failure
Large-scale epidemiological studies on the association of psychosocial factors with incident HF have primarily focused on depression, anxiety, anger/hostility, and social isolation/loneliness. As displayed in Table 1, evidence is strongest for the predictive value of major depression. Inconsistencies in the literature probably reflect the multifactorial aetiology and the long-time intervals between the psychological assessment and incident CHF. However, findings are strong enough to encourage clinicians to assess depressed mood, and possibly also anger proneness and social isolation in patients at high risk of CHF during clinical evaluation.
Psychosocial factors and incident HF: findings from observational prospective population based studies
Authors (year) . | Study type (acronym) . | Psychosocial factors . | Sample size total, N . | Risk of incident HR (95%CI)a . | Comments . |
---|---|---|---|---|---|
Cené et al. (2012)11 | Prospective cohort study (ARIC) | Social isolation | 12 976 | 1.18 (1.06–1.32) | Adjusted for age, sex, race/study community, and education |
Effect-mediation by (vital) exhaustion | |||||
Gustad et al. (2014)12 | Prospective population-based study (HUNT) | Depression | 62 567 | 1.41 (1.07–1.87) | Risk for severe and moderate depressive symptoms |
1.07 (0.87–1.30) | |||||
Garfield et al. (2014)13 | Retrospective cohort study baseline age 50–80 yrs (VA-Database) | Anxiety | 1.00 (0.70–1.43) | ||
Depression | 236 079 | 1.56 (1.45–1.67) | Major depressive disorder (comorbid anxiety excluded) | ||
Anxiety | 1.46 (1.35–1.58) | For high levels of anxiety [composite of GAD, PTSD, and Anxiety Disorder Un-specified (comorbid depression excluded)] | |||
Depression + | 1.74 (1.61–1.88) | Comorbid depression and anxiety | |||
Ogilvie et al. (2016)14 | Prospective cohort study (MESA) | Depression | 6782 | 1.06 (0.91–1.22) | Comparison per interquartile. Comparisons of highest vs. lowest quartile also presented. |
Anxiety | 0.91 (0.74–1.13) | Overall effects stronger for individuals with poor physical health | |||
Anger | 1.00 (0.83–1.20) | ||||
Hostility | 1.16 (0.96–1.40) | ||||
Chronic stress | 1.25 (1.00–1.57) | ||||
Kucharska-Newton et al. (2014)15 | Prospective cohort study mean age 56.9 yrs (ARIC) | Anger (trait) | 13 171 | 1.44 (1.23–1.69) | Age-adjusted (Model 2). Effects stronger for men association was attenuated when adjusting for vital exhaustion |
Authors (year) . | Study type (acronym) . | Psychosocial factors . | Sample size total, N . | Risk of incident HR (95%CI)a . | Comments . |
---|---|---|---|---|---|
Cené et al. (2012)11 | Prospective cohort study (ARIC) | Social isolation | 12 976 | 1.18 (1.06–1.32) | Adjusted for age, sex, race/study community, and education |
Effect-mediation by (vital) exhaustion | |||||
Gustad et al. (2014)12 | Prospective population-based study (HUNT) | Depression | 62 567 | 1.41 (1.07–1.87) | Risk for severe and moderate depressive symptoms |
1.07 (0.87–1.30) | |||||
Garfield et al. (2014)13 | Retrospective cohort study baseline age 50–80 yrs (VA-Database) | Anxiety | 1.00 (0.70–1.43) | ||
Depression | 236 079 | 1.56 (1.45–1.67) | Major depressive disorder (comorbid anxiety excluded) | ||
Anxiety | 1.46 (1.35–1.58) | For high levels of anxiety [composite of GAD, PTSD, and Anxiety Disorder Un-specified (comorbid depression excluded)] | |||
Depression + | 1.74 (1.61–1.88) | Comorbid depression and anxiety | |||
Ogilvie et al. (2016)14 | Prospective cohort study (MESA) | Depression | 6782 | 1.06 (0.91–1.22) | Comparison per interquartile. Comparisons of highest vs. lowest quartile also presented. |
Anxiety | 0.91 (0.74–1.13) | Overall effects stronger for individuals with poor physical health | |||
Anger | 1.00 (0.83–1.20) | ||||
Hostility | 1.16 (0.96–1.40) | ||||
Chronic stress | 1.25 (1.00–1.57) | ||||
Kucharska-Newton et al. (2014)15 | Prospective cohort study mean age 56.9 yrs (ARIC) | Anger (trait) | 13 171 | 1.44 (1.23–1.69) | Age-adjusted (Model 2). Effects stronger for men association was attenuated when adjusting for vital exhaustion |
CI, confidence interval; HF, heart failure; yrs, years.
Hazard rates (HRs) >1.0 indicate significantly increased risks with regard to the special endpoint under consideration.
Psychosocial factors and incident HF: findings from observational prospective population based studies
Authors (year) . | Study type (acronym) . | Psychosocial factors . | Sample size total, N . | Risk of incident HR (95%CI)a . | Comments . |
---|---|---|---|---|---|
Cené et al. (2012)11 | Prospective cohort study (ARIC) | Social isolation | 12 976 | 1.18 (1.06–1.32) | Adjusted for age, sex, race/study community, and education |
Effect-mediation by (vital) exhaustion | |||||
Gustad et al. (2014)12 | Prospective population-based study (HUNT) | Depression | 62 567 | 1.41 (1.07–1.87) | Risk for severe and moderate depressive symptoms |
1.07 (0.87–1.30) | |||||
Garfield et al. (2014)13 | Retrospective cohort study baseline age 50–80 yrs (VA-Database) | Anxiety | 1.00 (0.70–1.43) | ||
Depression | 236 079 | 1.56 (1.45–1.67) | Major depressive disorder (comorbid anxiety excluded) | ||
Anxiety | 1.46 (1.35–1.58) | For high levels of anxiety [composite of GAD, PTSD, and Anxiety Disorder Un-specified (comorbid depression excluded)] | |||
Depression + | 1.74 (1.61–1.88) | Comorbid depression and anxiety | |||
Ogilvie et al. (2016)14 | Prospective cohort study (MESA) | Depression | 6782 | 1.06 (0.91–1.22) | Comparison per interquartile. Comparisons of highest vs. lowest quartile also presented. |
Anxiety | 0.91 (0.74–1.13) | Overall effects stronger for individuals with poor physical health | |||
Anger | 1.00 (0.83–1.20) | ||||
Hostility | 1.16 (0.96–1.40) | ||||
Chronic stress | 1.25 (1.00–1.57) | ||||
Kucharska-Newton et al. (2014)15 | Prospective cohort study mean age 56.9 yrs (ARIC) | Anger (trait) | 13 171 | 1.44 (1.23–1.69) | Age-adjusted (Model 2). Effects stronger for men association was attenuated when adjusting for vital exhaustion |
Authors (year) . | Study type (acronym) . | Psychosocial factors . | Sample size total, N . | Risk of incident HR (95%CI)a . | Comments . |
---|---|---|---|---|---|
Cené et al. (2012)11 | Prospective cohort study (ARIC) | Social isolation | 12 976 | 1.18 (1.06–1.32) | Adjusted for age, sex, race/study community, and education |
Effect-mediation by (vital) exhaustion | |||||
Gustad et al. (2014)12 | Prospective population-based study (HUNT) | Depression | 62 567 | 1.41 (1.07–1.87) | Risk for severe and moderate depressive symptoms |
1.07 (0.87–1.30) | |||||
Garfield et al. (2014)13 | Retrospective cohort study baseline age 50–80 yrs (VA-Database) | Anxiety | 1.00 (0.70–1.43) | ||
Depression | 236 079 | 1.56 (1.45–1.67) | Major depressive disorder (comorbid anxiety excluded) | ||
Anxiety | 1.46 (1.35–1.58) | For high levels of anxiety [composite of GAD, PTSD, and Anxiety Disorder Un-specified (comorbid depression excluded)] | |||
Depression + | 1.74 (1.61–1.88) | Comorbid depression and anxiety | |||
Ogilvie et al. (2016)14 | Prospective cohort study (MESA) | Depression | 6782 | 1.06 (0.91–1.22) | Comparison per interquartile. Comparisons of highest vs. lowest quartile also presented. |
Anxiety | 0.91 (0.74–1.13) | Overall effects stronger for individuals with poor physical health | |||
Anger | 1.00 (0.83–1.20) | ||||
Hostility | 1.16 (0.96–1.40) | ||||
Chronic stress | 1.25 (1.00–1.57) | ||||
Kucharska-Newton et al. (2014)15 | Prospective cohort study mean age 56.9 yrs (ARIC) | Anger (trait) | 13 171 | 1.44 (1.23–1.69) | Age-adjusted (Model 2). Effects stronger for men association was attenuated when adjusting for vital exhaustion |
CI, confidence interval; HF, heart failure; yrs, years.
Hazard rates (HRs) >1.0 indicate significantly increased risks with regard to the special endpoint under consideration.
Association of psychosocial risk factors for clinical outcomes and mortality in patients with chronic heart failure
Extensive research has addressed the predictive value of psychosocial factors on the clinical prognosis in patients with established CHF. Table 2 summarizes the most recent meta-analyses suggesting that depression and social isolation/loneliness are independent contributors to an adverse long-term course of patients with CHF (hospitalization, mortality), thus emphasizing the urgent need to consider these conditions in treating patients with CHF in everyday life. Patients with CHF may be more susceptible to social isolation as they tend to be older and may suffer from CHF-induced physical and mobility limitations8 but also from disrupted social relationships due to life course factors (e.g. being widowed). The role of anxiety and anger/hostility has less been investigated.
Association of psychosocial risk factors with clinical outcomes and mortality in patients with chronic heart failure
Study . | Study type . | Psychosocial risk factors . | Number of follow-up studies (for meta-analyses) and sample size . | Follow-up duration . | HR (95% CI) . | Outcome and comments . |
---|---|---|---|---|---|---|
Meta-analyses | ||||||
Rutledge et al. (2006)16 | Prospective cohort studies | Depression | 8 (1862) | 6 months to >4 yrs | 2.1 (1.7–2.6) | Mortality and major clinical events |
Fan et al. (2014)17 | Prospective cohort studies | Depression | 9 (4012) |
| 1.98 (1.23–3.29)
| Mortality (all-cause) |
Sokoreli et al. (2016)18 | Prospective cohort studies | Depression | 26 (80 627) |
| 1.40 (1.22–1.60)
| Mortality (all-cause) |
Anxiety | 6 (17 214) | >6 months | 1.02 (1.00–1.04) |
| ||
Gathright et al. (2017)19 | Prospective cohort studies | Depression | 18 (5629) | 756 days to 12 yrs | 1.20 (1.10–1.31) unadjusted HR = 1.75, 95% CI = 1.33–2.30 | Mortality (all-cause) |
Effects stronger for patients ≥65 years | ||||||
Machado et al. (2018)20 | Review of systematic reviews and meta-analyses | Depression | 22 | >5 yrs | 1.46 (1.30–1.65) | Mortality (all-cause) |
| ||||||
Kewcharoen et al. (2020)21 | Prospective cohort studies | Depression | 10 (53 165) | >1 week | 1.54 (1.22–1.94) |
|
Heidari Gorji et al. (2019)22 | Prospective cohort Studies | Social isolation | 13 (6468) | >1 week | 1.55 (1.39–1.73) | Rehospitalization |
Odds ratios are reported | ||||||
Individual studies published after the meta-analysis | ||||||
Adelborg et al. (2016)23 | Registry-based study | Depression History of depression, not post HF depression | 204 523 | >1 year | 1.03 (1.01–1.06) | Mortality (all-cause) |
Freedland et al. (2016)24 | Prospective cohort study | Depression | 662 | 20 yrs | 1.64 (1.27–2.11) | Mortality (all-cause) |
Saito et al. (2019)8 | Prospective cohort study | Social isolation | 148 | 90 days |
| Rehospitalization |
Sokoreli et al. (2016)25 | Prospective cohort study (OPERA-HF) | Depression | 242 | 360 days | 3.0 (1.3–7.0) |
|
Sokoreli et al. (2018)26 | Prospective cohort study (OPERA-HF) | Depression | 779 | >discharge | 1.74 (1.24–2.44) | Psychosocial assessments |
>1 year: N = 641 | (HADS and other) complete for >4 in 54% of pts 41 death and N = 518 had readmission | |||||
Anxiety | 1.67 (1.21–2.30) | |||||
Cognitive | 1.43 (0.90–2.28) | |||||
Dysfunction | HRs for first event | |||||
Living alone | 1.04 (0.85–1.27) adjusted for covariates | |||||
Christensen et al. (2020)27 | Registry-based cohort study | Loneliness | 987 |
| 2.92 (1.55–5.49) | Mortality (all-cause) |
Social isolation | 2.14 (1.43–3.22) | |||||
Individual studies not included into the meta-analyses being cited | ||||||
Endrighi et al. (2016)28 | Prospective cohort study | Perceived stress | 144 | 9 months | 1.10 (1.04–1.17) | Mortality and rehospitalization |
Odds ratios reported | ||||||
Rafanelli et al. (2016)29 | Prospective cohort study | Hostility | 60 | 4 yrs | 2.38 (1.04–5.45) |
|
Keith et al. (2017)30 | Prospective cohort study | Anger/hostility | 146 | 3 yrs | No risk ratios reported |
|
Study . | Study type . | Psychosocial risk factors . | Number of follow-up studies (for meta-analyses) and sample size . | Follow-up duration . | HR (95% CI) . | Outcome and comments . |
---|---|---|---|---|---|---|
Meta-analyses | ||||||
Rutledge et al. (2006)16 | Prospective cohort studies | Depression | 8 (1862) | 6 months to >4 yrs | 2.1 (1.7–2.6) | Mortality and major clinical events |
Fan et al. (2014)17 | Prospective cohort studies | Depression | 9 (4012) |
| 1.98 (1.23–3.29)
| Mortality (all-cause) |
Sokoreli et al. (2016)18 | Prospective cohort studies | Depression | 26 (80 627) |
| 1.40 (1.22–1.60)
| Mortality (all-cause) |
Anxiety | 6 (17 214) | >6 months | 1.02 (1.00–1.04) |
| ||
Gathright et al. (2017)19 | Prospective cohort studies | Depression | 18 (5629) | 756 days to 12 yrs | 1.20 (1.10–1.31) unadjusted HR = 1.75, 95% CI = 1.33–2.30 | Mortality (all-cause) |
Effects stronger for patients ≥65 years | ||||||
Machado et al. (2018)20 | Review of systematic reviews and meta-analyses | Depression | 22 | >5 yrs | 1.46 (1.30–1.65) | Mortality (all-cause) |
| ||||||
Kewcharoen et al. (2020)21 | Prospective cohort studies | Depression | 10 (53 165) | >1 week | 1.54 (1.22–1.94) |
|
Heidari Gorji et al. (2019)22 | Prospective cohort Studies | Social isolation | 13 (6468) | >1 week | 1.55 (1.39–1.73) | Rehospitalization |
Odds ratios are reported | ||||||
Individual studies published after the meta-analysis | ||||||
Adelborg et al. (2016)23 | Registry-based study | Depression History of depression, not post HF depression | 204 523 | >1 year | 1.03 (1.01–1.06) | Mortality (all-cause) |
Freedland et al. (2016)24 | Prospective cohort study | Depression | 662 | 20 yrs | 1.64 (1.27–2.11) | Mortality (all-cause) |
Saito et al. (2019)8 | Prospective cohort study | Social isolation | 148 | 90 days |
| Rehospitalization |
Sokoreli et al. (2016)25 | Prospective cohort study (OPERA-HF) | Depression | 242 | 360 days | 3.0 (1.3–7.0) |
|
Sokoreli et al. (2018)26 | Prospective cohort study (OPERA-HF) | Depression | 779 | >discharge | 1.74 (1.24–2.44) | Psychosocial assessments |
>1 year: N = 641 | (HADS and other) complete for >4 in 54% of pts 41 death and N = 518 had readmission | |||||
Anxiety | 1.67 (1.21–2.30) | |||||
Cognitive | 1.43 (0.90–2.28) | |||||
Dysfunction | HRs for first event | |||||
Living alone | 1.04 (0.85–1.27) adjusted for covariates | |||||
Christensen et al. (2020)27 | Registry-based cohort study | Loneliness | 987 |
| 2.92 (1.55–5.49) | Mortality (all-cause) |
Social isolation | 2.14 (1.43–3.22) | |||||
Individual studies not included into the meta-analyses being cited | ||||||
Endrighi et al. (2016)28 | Prospective cohort study | Perceived stress | 144 | 9 months | 1.10 (1.04–1.17) | Mortality and rehospitalization |
Odds ratios reported | ||||||
Rafanelli et al. (2016)29 | Prospective cohort study | Hostility | 60 | 4 yrs | 2.38 (1.04–5.45) |
|
Keith et al. (2017)30 | Prospective cohort study | Anger/hostility | 146 | 3 yrs | No risk ratios reported |
|
Data are presented for meta-analyses, individual studies that were published after the meta-analyses, and individual studies on psychosocial factors that have not yet been reviewed in meta-analyses.
CI, confidence interval; ES, effect size; HF, heart failure; HR, hazard ratio; MDD, major depressive disorder; NS, not significant in multivariable analyses; OR, odds ratio; pts, patients; yrs, years.
Association of psychosocial risk factors with clinical outcomes and mortality in patients with chronic heart failure
Study . | Study type . | Psychosocial risk factors . | Number of follow-up studies (for meta-analyses) and sample size . | Follow-up duration . | HR (95% CI) . | Outcome and comments . |
---|---|---|---|---|---|---|
Meta-analyses | ||||||
Rutledge et al. (2006)16 | Prospective cohort studies | Depression | 8 (1862) | 6 months to >4 yrs | 2.1 (1.7–2.6) | Mortality and major clinical events |
Fan et al. (2014)17 | Prospective cohort studies | Depression | 9 (4012) |
| 1.98 (1.23–3.29)
| Mortality (all-cause) |
Sokoreli et al. (2016)18 | Prospective cohort studies | Depression | 26 (80 627) |
| 1.40 (1.22–1.60)
| Mortality (all-cause) |
Anxiety | 6 (17 214) | >6 months | 1.02 (1.00–1.04) |
| ||
Gathright et al. (2017)19 | Prospective cohort studies | Depression | 18 (5629) | 756 days to 12 yrs | 1.20 (1.10–1.31) unadjusted HR = 1.75, 95% CI = 1.33–2.30 | Mortality (all-cause) |
Effects stronger for patients ≥65 years | ||||||
Machado et al. (2018)20 | Review of systematic reviews and meta-analyses | Depression | 22 | >5 yrs | 1.46 (1.30–1.65) | Mortality (all-cause) |
| ||||||
Kewcharoen et al. (2020)21 | Prospective cohort studies | Depression | 10 (53 165) | >1 week | 1.54 (1.22–1.94) |
|
Heidari Gorji et al. (2019)22 | Prospective cohort Studies | Social isolation | 13 (6468) | >1 week | 1.55 (1.39–1.73) | Rehospitalization |
Odds ratios are reported | ||||||
Individual studies published after the meta-analysis | ||||||
Adelborg et al. (2016)23 | Registry-based study | Depression History of depression, not post HF depression | 204 523 | >1 year | 1.03 (1.01–1.06) | Mortality (all-cause) |
Freedland et al. (2016)24 | Prospective cohort study | Depression | 662 | 20 yrs | 1.64 (1.27–2.11) | Mortality (all-cause) |
Saito et al. (2019)8 | Prospective cohort study | Social isolation | 148 | 90 days |
| Rehospitalization |
Sokoreli et al. (2016)25 | Prospective cohort study (OPERA-HF) | Depression | 242 | 360 days | 3.0 (1.3–7.0) |
|
Sokoreli et al. (2018)26 | Prospective cohort study (OPERA-HF) | Depression | 779 | >discharge | 1.74 (1.24–2.44) | Psychosocial assessments |
>1 year: N = 641 | (HADS and other) complete for >4 in 54% of pts 41 death and N = 518 had readmission | |||||
Anxiety | 1.67 (1.21–2.30) | |||||
Cognitive | 1.43 (0.90–2.28) | |||||
Dysfunction | HRs for first event | |||||
Living alone | 1.04 (0.85–1.27) adjusted for covariates | |||||
Christensen et al. (2020)27 | Registry-based cohort study | Loneliness | 987 |
| 2.92 (1.55–5.49) | Mortality (all-cause) |
Social isolation | 2.14 (1.43–3.22) | |||||
Individual studies not included into the meta-analyses being cited | ||||||
Endrighi et al. (2016)28 | Prospective cohort study | Perceived stress | 144 | 9 months | 1.10 (1.04–1.17) | Mortality and rehospitalization |
Odds ratios reported | ||||||
Rafanelli et al. (2016)29 | Prospective cohort study | Hostility | 60 | 4 yrs | 2.38 (1.04–5.45) |
|
Keith et al. (2017)30 | Prospective cohort study | Anger/hostility | 146 | 3 yrs | No risk ratios reported |
|
Study . | Study type . | Psychosocial risk factors . | Number of follow-up studies (for meta-analyses) and sample size . | Follow-up duration . | HR (95% CI) . | Outcome and comments . |
---|---|---|---|---|---|---|
Meta-analyses | ||||||
Rutledge et al. (2006)16 | Prospective cohort studies | Depression | 8 (1862) | 6 months to >4 yrs | 2.1 (1.7–2.6) | Mortality and major clinical events |
Fan et al. (2014)17 | Prospective cohort studies | Depression | 9 (4012) |
| 1.98 (1.23–3.29)
| Mortality (all-cause) |
Sokoreli et al. (2016)18 | Prospective cohort studies | Depression | 26 (80 627) |
| 1.40 (1.22–1.60)
| Mortality (all-cause) |
Anxiety | 6 (17 214) | >6 months | 1.02 (1.00–1.04) |
| ||
Gathright et al. (2017)19 | Prospective cohort studies | Depression | 18 (5629) | 756 days to 12 yrs | 1.20 (1.10–1.31) unadjusted HR = 1.75, 95% CI = 1.33–2.30 | Mortality (all-cause) |
Effects stronger for patients ≥65 years | ||||||
Machado et al. (2018)20 | Review of systematic reviews and meta-analyses | Depression | 22 | >5 yrs | 1.46 (1.30–1.65) | Mortality (all-cause) |
| ||||||
Kewcharoen et al. (2020)21 | Prospective cohort studies | Depression | 10 (53 165) | >1 week | 1.54 (1.22–1.94) |
|
Heidari Gorji et al. (2019)22 | Prospective cohort Studies | Social isolation | 13 (6468) | >1 week | 1.55 (1.39–1.73) | Rehospitalization |
Odds ratios are reported | ||||||
Individual studies published after the meta-analysis | ||||||
Adelborg et al. (2016)23 | Registry-based study | Depression History of depression, not post HF depression | 204 523 | >1 year | 1.03 (1.01–1.06) | Mortality (all-cause) |
Freedland et al. (2016)24 | Prospective cohort study | Depression | 662 | 20 yrs | 1.64 (1.27–2.11) | Mortality (all-cause) |
Saito et al. (2019)8 | Prospective cohort study | Social isolation | 148 | 90 days |
| Rehospitalization |
Sokoreli et al. (2016)25 | Prospective cohort study (OPERA-HF) | Depression | 242 | 360 days | 3.0 (1.3–7.0) |
|
Sokoreli et al. (2018)26 | Prospective cohort study (OPERA-HF) | Depression | 779 | >discharge | 1.74 (1.24–2.44) | Psychosocial assessments |
>1 year: N = 641 | (HADS and other) complete for >4 in 54% of pts 41 death and N = 518 had readmission | |||||
Anxiety | 1.67 (1.21–2.30) | |||||
Cognitive | 1.43 (0.90–2.28) | |||||
Dysfunction | HRs for first event | |||||
Living alone | 1.04 (0.85–1.27) adjusted for covariates | |||||
Christensen et al. (2020)27 | Registry-based cohort study | Loneliness | 987 |
| 2.92 (1.55–5.49) | Mortality (all-cause) |
Social isolation | 2.14 (1.43–3.22) | |||||
Individual studies not included into the meta-analyses being cited | ||||||
Endrighi et al. (2016)28 | Prospective cohort study | Perceived stress | 144 | 9 months | 1.10 (1.04–1.17) | Mortality and rehospitalization |
Odds ratios reported | ||||||
Rafanelli et al. (2016)29 | Prospective cohort study | Hostility | 60 | 4 yrs | 2.38 (1.04–5.45) |
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Keith et al. (2017)30 | Prospective cohort study | Anger/hostility | 146 | 3 yrs | No risk ratios reported |
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Data are presented for meta-analyses, individual studies that were published after the meta-analyses, and individual studies on psychosocial factors that have not yet been reviewed in meta-analyses.
CI, confidence interval; ES, effect size; HF, heart failure; HR, hazard ratio; MDD, major depressive disorder; NS, not significant in multivariable analyses; OR, odds ratio; pts, patients; yrs, years.
Although poor left ventricular function does not play a primary causal role for depression in CHF,9 functional limitations, biological correlates,10 and psychological reactions to having a life-threatening disease are primary factors driving depression in patients with CHF. As illustrated in Figure 1, disease progression is likely to facilitate restrictions in daily activities and increased awareness of limited life expectancy, resulting in transient episodes of despair and hopelessness, which may induce reduced adherence with effective treatment ending up in refractory depression.

Bi-directionality between depression and the clinical sequelae of chronic heart failure.
1. State-of-the-science:
Evidence from population-based studies indicates that depression and social isolation/loneliness are associated with increased risk for incident (new-onset) HF. For other psychosocial risk factors (e.g. anxiety, anger/hostility), current evidence is insufficient.
For patients with CHF, there is strong evidence that depression is associated with increased risk of HF progression and mortality; the predictive value of other psychosocial factors requires further research.
2. Knowledge gaps:
Further research is needed to determine high-risk subgroups based on psychological and social factors, in combination with biological processes and health behaviours relevant to HF progression.
Research on the bi-directional relationship between depression and the clinical sequelae of CHF (e.g. symptoms and functional limitations) is still in its infancy. More research is needed on whether interventions targeting one ‘pathway’ of these bi-directional processes will also positively influence the related pathways relevant to HF progression.
The contributions of contextual socio-economic variables require critical consideration (e.g. loss of work or social engagement).
Knowledge gaps exist for the importance of follow-up periods and age-, sex-, and ethnicity-related issues in comorbid mental health disparities.
Autonomic nervous system dysregulation, neuro-humoral processes, and inflammation as mediators
A compensatory neuro-hormonal overdrive, as a consequence of an increasing decline of the contraction and relaxation capacity of the heart, is one major pathway to decompensated HF. In early stages of the disease process, the activation of the sympathetic branch of the autonomic nervous system and the endocrine renin–angiotensin–aldosterone system (RAAS) contribute to the maintenance of an adequate intravascular volume.31 Sustained neuro-hormonal activation, however, drives systemic vascular resistance and increased left ventricular afterload which in turn increases myocardial demand and left ventricular end-diastolic pressure and promotes inflammatory pathways32 (usually framed as ‘inflammatory reflex’).
Severe sustained psychological distress results in autonomic, neuroendocrine, and inflammatory responses in order to support the organism to cope with high-demand conditions.10 They substantially overlap with the compensatory neuro-hormonal overdrive associated with CHF and therefore likely result in a synergism between the neurobiological correlates of CHF and psychosocial distress—further reinforcing their deleterious effects on the progression of CHF (Figure 2) best framed within the allostatic load model according to which an initially adaptive compensatory mechanism can develop into maladaptive processes. Although the concept is intriguing, the empirical evidence is still in its infancy.

Flow-chart demonstrating the impact of (psychosocial) stress-induced autonomic, endocrine, and inflammatory pathways on compensatory neuro-humoral processes aggravating the progression to end-stage heart failure.
Autonomic nervous system dysregulation
Sympathetic overdrive and parasympathetic withdrawal are clinically common features of sustained adverse psychosocial conditions which can be indexed with heart rate variability (HRV) measures and impedance cardiogram analysis.33 However, to date, no studies have investigated an additive impact of psychosocial distress and autonomic dysregulation on CHF progression. Clinical studies that have addressed HRV response patterns in patients with CHF revealed rather blunted than exaggerated reactions.34 A prospective follow-up study of patients with systolic CHF demonstrated an excess mortality risk among those who exhibited lowest cardiovascular reactivity to mental stress most likely reflecting a suboptimal pressure responses as a prognostic relevant factor in CHF progression.35
Neuroendocrine processes
Impairments of the hypothalamic–pituitary–adrenal axis as reflected by increased serum cortisol levels were found in patients with CHF36 and, more importantly, contribute substantially to disease progression.37,38 Thus, sustained stress-induced hypercortisolaemic states further amplify the critical neuroendocrine activation in patients with CHF. In contrast to these findings, a recent investigation revealed heightened evening salivary cortisol levels39 as an independent predictor of decompensated chronic CHF which points to a disturbed or even blunted circadian rhythm of cortisol secretion. Of note, a synergistic evaluation of cortisol levels in CHF patients with and without comorbid mental health disparities has not been undertaken to date. Cortisol may also activate mineralocorticoid receptors in CHF. The mineralocorticoid aldosterone has gained limited attention as stress hormone in human stress biology so far. Yet, findings from a large population-based study showing that the combined presence of depression and social isolation was associated with a substantial increase in aldosterone levels, particularly in men, point to considerable psychosocial involvement in the activation of the RAAS.40
Inflammation
Evidence of the role of inflammation in the association between depression and CHF progression is based on several cross-sectional and prospective clinical investigations involving sTNFR1,41 interleukin 6 and C-reactive protein,42,43 and more extended patterns of inflammation markers.44 All but one study45 confirmed a positive relationship between increased sustained inflammation and depression—a combination which may contribute to an excess mortality risk in patients with CHF and depression.46
1. State-of-the-science:
Sustained stress-induced activation of the autonomic, neuroendocrine, and inflammatory pathways—superimposed on well-established compensatory neuro-hormonal overdrive in CHF progression—increase the risk of fatal disease outcomes.
In advanced stages of CHF, blunted rather than exaggerated response patterns may be observed.
In addition to the potential synergy between biological correlates of psychosocial stress and CHF, there is a bidirectional association between functional limitations associated with CHF (e.g. reduced physical activity and CHF-related physical challenges) and psychosocial factors such as depression.
2. Knowledge gaps:
Larger, statistically well-powered epidemiological and clinical intervention studies are needed to determine the (difference in) effect sizes of biological processes that mediate the association between psychosocial factors and CHF progression.
Novel data-analytic models are needed to clarify the synergistic roles of psychosocial factors, biological processes, and CHF-related features.
Association of psychological factors with poor self-care and other health behaviours
Self-care involves practices that patients engage in maintaining their own health.47 Key elements of CHF-related self-care refer to adherence to medication, detecting, monitoring, and managing signs and symptoms of disease progression and reducing water and sodium intake. Less specific CHF features include favourable health behaviours with increasing physical activity, quitting smoking and reducing alcohol consumption. Insufficient self-care affect more than half of the patients with CHF and are leading causes for poor outcomes including increased CHF exacerbations, higher risk for hospital admission and death.47 A systematic review on the efficacy of adherence-promoting interventions,48 including 24 trials with 15 016 patients with CHF, found only modest improvements (Table 3).
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Interventions to improve CHF-related self-care should be components of structured cardiac rehabilitation.49 Specific eHealth interventions to enhance disease management of patients with CHF are an attractive option for the future. A Cochrane Review50 indicates that structured telephone support and non-invasive home tele-monitoring for patients with CHF reduced the risk of all-cause mortality, HF-related hospitalization and quality of life (QoL) by improvements in HF knowledge and self-care behaviours. Psychological interventions tend to improve self-care in patients with CHF without clinical depression and cognitive impairments.51 Yet, improvements disappeared as the length of time from the intervention increased. There were no statistically significant intervention effects on anxiety.
Among psychological techniques promoting self-care, motivational interviewing (MI) is receiving increasing attention. A Cochrane review52 based on 8 studies (with 758 patients, age range 58–79 years) reported a positive impact of MI over advice-giving, implicating that MI improves the long-term CHF outcomes through better general self-care behaviours, especially when delivered over a longer duration. The quantitative pooling of effect sizes of MI on enhancing self-care behaviours among patients with CHF in a meta-analysis of nine randomized controlled trials (RCTs)53 yielded moderate effects on enhancing self-care confidence and self-care management and large effects on improving self-care maintenance (i.e. adherence to treatment and symptom monitoring) (Hedge’s g = 0.873; 95% confidence interval = 0.430–1.317; P < 0.001). Of note, no effects were found for directly assessed physical functioning using the 6-min walking test.
Factors known to compromise readiness and maintenance of CHF self-care include depression,54 but also factors like illness perception, physical functioning, social support, and more general health-related attitudes such as self-efficacy.47 Anxiety has no particular detrimental impact on CHF self-care.55 Surprisingly, the level of evidence linking social support with better adherence to medical recommendations is modest.56 Reasons for why depressed patients with CHF often are non-adherent to their treatment regime are related to the specific phenotype of depression (e.g. reduced energy to carry out activities)57 but also interfere with reductions in cognitive functioning that may affect memory.58 Both depressed mood and impaired cognitive functioning probably affect self-care behaviours indirectly: a study of 628 Italian patients with CHF showed that self-efficacy (or task-specific confidence) mediated the relationship between cognitive functioning and poor CHF self-care.59
1. State-of-the-science:
Chronic heart failure self-care interventions are recommended for detecting CHF exacerbations, improving symptom management and preventing hospitalizations.
Insufficient CHF self-care conditions (e.g. lack of adherence to medication) affect more than half of the patients with CHF and is one of the leading causes of poor outcomes.
The efficacy of CHF self-care interventions usually applied in clinical practice is modest, most likely because the majority of concepts do not consider the impact of impaired cognition, depressed mood, and other psychological barriers.
Efforts aimed at promoting self-care are the cornerstone of CHF disease management and should be components of structured cardiac rehabilitation.
2. Knowledge gaps:
Medical and health psychology research on how to motivate patients in an early stage of CHF to engage in exercise training on a regular basis is missing.
Among brief psychological techniques promoting self-care, MI is receiving increasing attention. Given the many opportunities of nursing staff to interact with patients, it is recommended that specialized nurses should be trained to incorporate this psychological technique to maximize intervention effectiveness.
eHealth interventions specific to CHF (telephone support and home tele-monitoring) to enhance disease management programs are a clear option for the future. More knowledge is needed to optimally tailor these interventions to individual patient and provider needs and to incorporate mental health outcomes.
Psychotherapy, psycho-pharmacotherapy, and other health psychological interventions
Psychotherapy in chronic heart failure
Psychotherapy involves psychological and behavioural methods grounded in a defined psychological theory and based on interactions with a formally trained mental health professional to help a person change cognitions, attitudes, and behaviour, so as to overcome emotional and other psychological problems.
Cognitive behavioural therapy
A few mainly small psychotherapy studies have used cognitive behavioural therapy (CBT) to treat depressive symptoms in patients with CHF (e.g.60 summarized by two meta-analyses61,62) The first meta-analysis included five RCTs and one observational study (total n = 320) and found that CBT for depression had small but significant positive effects on depressive symptoms and QoL.51 A more recent meta-analysis (k = 8; N = 480) patients confirmed the beneficial effect on depressive symptoms (standardized mean difference: SMD = −0.27) but found only a marginal effect on QoL (SMD = 0.21) and no effect on self-care or physical functioning (6-min walk test).60,61,63 Insufficient evidence that treatment for depression improves physical capacity is not limited to CBT.63 However, the benefits of CBT can possibly be enhanced by complementing CBT with structured exercise programmes.64,65 The effectiveness of psychological interventions such as psycho-dynamically oriented interventions have not been systematically investigated in a large enough number of patients with CHF.
Other psychotherapeutic interventions
At advanced stages of CHF, issues related to end-of-life questions, fear of dying, and existential topics require different approaches than CBT.66,67 (see also Section ‘Palliative care in end-stage chronic heart failure’ addressing palliative care). Here, alternative psychotherapeutic approaches (e.g. family dynamics) may be better suited to meet the needs of patients with CHF.68
(Blended) collaborative care and disease management
Several RCTs have used supervised nurses to continuously support CHF patients in disease coping and health behaviours. While a German RCT found beneficial effects on all-cause mortality and physical but not mental QoL,69 two American trials70,71 found no intervention effects on overall QoL but a beneficial effect on depressive symptoms, especially in the depressed subgroup. No RCT has so far published results on blended collaborative care specifically targeting mental comorbidity in CHF.72 However, simultaneous integrated care for CHF health behaviour and mental distress72 may be most appropriate for improving not only mental well-being and QoL but also prognosis, although this still needs to be demonstrated.63
Psycho-pharmacological interventions in patients with chronic heart failure
Adequate treatment of depressive disorders typically includes pharmacological treatment, especially for moderate and severe depression. As a consequence of interactions with somatic CHF symptoms and concomitant cardiac medications, more adverse reactions may occur in response to pharmacological therapy in patients wih CHF. Several large scale health registries73,74 have examined the frequency and adverse effects of antidepressants in the general population and evidenced a significant increase in prescriptions of antidepressants over the long-term clinical course and an increased all-cause and cardiovascular mortality risk (even independent from depression). An overflowing use of antidepressants in patients with CHF was recently confirmed in an US data set.75
A systematic review revealed that specifically for patients with CHF and depression, the use of selective serotonin reuptake inhibitors (SSRIs), serotonin and norepinephrine reuptake inhibitors (SNRIs), and tricyclic antidepressants (TCAs) are significantly associated with increased all-cause mortality (SSRIs RR = 1.26; SNRIs RR = 1.17; TCAs RR = 1.30), although not cardiovascular disease-related mortality.76 It is therefore important to weigh the improvements in QoL against a potentially increased mortality risk associated with depression and antidepressant medications. This risk estimation should include the cardiac risk of untreated depression in comparison to the risk due to adverse cardiac events of the psychopharmacological treatment. Therefore, individualized medication treatment plans are needed to optimally treat these patients with a focus on tolerability and effectiveness. Of note, a recent systematic review concluded that more RCTs are needed to obtain valid information on whether antidepressants are safe and effective.77
Currently, two large scale RCTs of antidepressants for patients with CHF are available: the MOOD-CHF RCT, which failed to show reduced mortality or even antidepressant efficacy78 and the prior SAD HEART-HF study,79 which demonstrated no significant effects for sertraline on depression or cardiovascular outcomes. In consequence, recommendations to prescribe SSRIs in these patients were withdrawn.80 Nevertheless, secondary analyses indicate that remission from depression may improve cardiovascular outcome of patients with CHF81 mainly due to a mean reduction in heart rate.82 Among SSRI treated patients, heart disease-related risks seem to be the highest with (es)citalopram,83 medium with sertraline and fluoxetine in patients with specific risk factors,84 and low in patients treated with paroxetine83 although paroxetine has been linked to the induction of orthostatic hypotension due to its anticholinergic properties.85
SNRI (selective serotonin and noradrenaline reuptake inhibitors)
Given the spectrum of potential adverse side effects of SNRIs likely to provoke worsening and exacerbation of CHF,86 SNRIs should be avoided or at least cautiously used with regular monitoring.86 The same holds true for TCA, their use has been associated with an increased risk of myocardial infarction,87 orthostatic hypotension, conduction delays, and increased heart rates, all increasing the risk of cardiac morbidity and mortality.88 Therefore, TCAs should be avoided in patients with CHF.89
Newer generation antidepressant drugs
The newer generation antidepressants such as the NARI (selective noradrenaline/norepinephrine reuptake inhibitor) reboxetine,90 the DNRI (selective dopamine and norepinephrine reuptake inhibitor) bupropion,91 the NaSSA (specific noradrenergic and specific serotonergic antidepressant) α2-blocker mirtazapine,91 and also the melatonin MT1/MT2 agonist and 5HT2c antagonist agomelatine may all exert (with the exception of agomelatine) negative cardiac effects due to their noradrenergic properties and the potential to prolong the QTc interval (with the lowest risk for bupropion)92 and their negative influence on HRV (e.g. mirtazapine).93 Close monitoring (particularly electrocardiogram monitoring during initiation of treatment) for these drugs is mandatory94 (Table 4).
The role of selected psycho-pharmacological treatment options and their potential risks in CHF-patients with depression
Class and indication . | Generic name . | Pharmaco-dynamic effects . | Typical cardiac side effects . | Cardiovascular risk estimationb . |
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Antidepressants | Agomelatine | MT1/2 agonist | HRV ↓ | o |
Sertraline | SSRI | ++ | ||
Fluoxetine | SSRI | ++ | ||
(Es)citalopram | SSRI | QTc ↑ | ++ | |
Vortioxetinea | SSRI | + | ||
Paroxetine | SSRI | BP ↓ | o | |
Duloxetine | SNRI | HR ↑ | +++ | |
Venlafaxine | SNRI | HRV ↓ | +++ | |
Milnacipran | SNRI | BP ↑ | +++ | |
Mirtazapine | NaSSA | HRV ↓ | + | |
Reboxetine | NARI | BP ↑, QTc ↑ | + | |
Bupropion | DNRI | BP ↑ | + | |
Amitriptyline | TCA | BP ↓, MI ↑ | ++++ | |
Doxepine | TCA | BP ↓, MI ↑ | ++++ | |
Tranylcypromine | MAOI | BP ↓, BP ↑ | ++ | |
Augmentation strategies and concomitant treatment | ||||
Mood stabilizer | Lithium | QTc ↑ | ++++ | |
Atypical antipsychotics | Aripiprazole | D2-, 5HT1-partial agonist | QTc ↑, HR ↑ | ++ |
Quetiapine | D2-, 5HT2-antagonist | QTc ↑, BP ↓ | +++ | |
Clozapine | D2-, 5HT2-antagonist | QTc ↑, HRV ↓, HR ↑, BP ↓ | ++++ | |
Response accelerator | (Es)ketamine | NMDA-antagonist | BP ↑, HR ↑ | +o |
Hypnotics | Lorazepam | GABA-modulator | Evidence weak | |
Zopiclone | GABA-agonist | Evidence weak |
Class and indication . | Generic name . | Pharmaco-dynamic effects . | Typical cardiac side effects . | Cardiovascular risk estimationb . |
---|---|---|---|---|
Antidepressants | Agomelatine | MT1/2 agonist | HRV ↓ | o |
Sertraline | SSRI | ++ | ||
Fluoxetine | SSRI | ++ | ||
(Es)citalopram | SSRI | QTc ↑ | ++ | |
Vortioxetinea | SSRI | + | ||
Paroxetine | SSRI | BP ↓ | o | |
Duloxetine | SNRI | HR ↑ | +++ | |
Venlafaxine | SNRI | HRV ↓ | +++ | |
Milnacipran | SNRI | BP ↑ | +++ | |
Mirtazapine | NaSSA | HRV ↓ | + | |
Reboxetine | NARI | BP ↑, QTc ↑ | + | |
Bupropion | DNRI | BP ↑ | + | |
Amitriptyline | TCA | BP ↓, MI ↑ | ++++ | |
Doxepine | TCA | BP ↓, MI ↑ | ++++ | |
Tranylcypromine | MAOI | BP ↓, BP ↑ | ++ | |
Augmentation strategies and concomitant treatment | ||||
Mood stabilizer | Lithium | QTc ↑ | ++++ | |
Atypical antipsychotics | Aripiprazole | D2-, 5HT1-partial agonist | QTc ↑, HR ↑ | ++ |
Quetiapine | D2-, 5HT2-antagonist | QTc ↑, BP ↓ | +++ | |
Clozapine | D2-, 5HT2-antagonist | QTc ↑, HRV ↓, HR ↑, BP ↓ | ++++ | |
Response accelerator | (Es)ketamine | NMDA-antagonist | BP ↑, HR ↑ | +o |
Hypnotics | Lorazepam | GABA-modulator | Evidence weak | |
Zopiclone | GABA-agonist | Evidence weak |
Vortioxetine is approved by the European Medicines Agency but not marketed in Germany.
0 ‘Very low', + ‘Low', ++ ‘Medium', +++ ‘High', ++++ ‘Highest (contra-indicated).
The role of selected psycho-pharmacological treatment options and their potential risks in CHF-patients with depression
Class and indication . | Generic name . | Pharmaco-dynamic effects . | Typical cardiac side effects . | Cardiovascular risk estimationb . |
---|---|---|---|---|
Antidepressants | Agomelatine | MT1/2 agonist | HRV ↓ | o |
Sertraline | SSRI | ++ | ||
Fluoxetine | SSRI | ++ | ||
(Es)citalopram | SSRI | QTc ↑ | ++ | |
Vortioxetinea | SSRI | + | ||
Paroxetine | SSRI | BP ↓ | o | |
Duloxetine | SNRI | HR ↑ | +++ | |
Venlafaxine | SNRI | HRV ↓ | +++ | |
Milnacipran | SNRI | BP ↑ | +++ | |
Mirtazapine | NaSSA | HRV ↓ | + | |
Reboxetine | NARI | BP ↑, QTc ↑ | + | |
Bupropion | DNRI | BP ↑ | + | |
Amitriptyline | TCA | BP ↓, MI ↑ | ++++ | |
Doxepine | TCA | BP ↓, MI ↑ | ++++ | |
Tranylcypromine | MAOI | BP ↓, BP ↑ | ++ | |
Augmentation strategies and concomitant treatment | ||||
Mood stabilizer | Lithium | QTc ↑ | ++++ | |
Atypical antipsychotics | Aripiprazole | D2-, 5HT1-partial agonist | QTc ↑, HR ↑ | ++ |
Quetiapine | D2-, 5HT2-antagonist | QTc ↑, BP ↓ | +++ | |
Clozapine | D2-, 5HT2-antagonist | QTc ↑, HRV ↓, HR ↑, BP ↓ | ++++ | |
Response accelerator | (Es)ketamine | NMDA-antagonist | BP ↑, HR ↑ | +o |
Hypnotics | Lorazepam | GABA-modulator | Evidence weak | |
Zopiclone | GABA-agonist | Evidence weak |
Class and indication . | Generic name . | Pharmaco-dynamic effects . | Typical cardiac side effects . | Cardiovascular risk estimationb . |
---|---|---|---|---|
Antidepressants | Agomelatine | MT1/2 agonist | HRV ↓ | o |
Sertraline | SSRI | ++ | ||
Fluoxetine | SSRI | ++ | ||
(Es)citalopram | SSRI | QTc ↑ | ++ | |
Vortioxetinea | SSRI | + | ||
Paroxetine | SSRI | BP ↓ | o | |
Duloxetine | SNRI | HR ↑ | +++ | |
Venlafaxine | SNRI | HRV ↓ | +++ | |
Milnacipran | SNRI | BP ↑ | +++ | |
Mirtazapine | NaSSA | HRV ↓ | + | |
Reboxetine | NARI | BP ↑, QTc ↑ | + | |
Bupropion | DNRI | BP ↑ | + | |
Amitriptyline | TCA | BP ↓, MI ↑ | ++++ | |
Doxepine | TCA | BP ↓, MI ↑ | ++++ | |
Tranylcypromine | MAOI | BP ↓, BP ↑ | ++ | |
Augmentation strategies and concomitant treatment | ||||
Mood stabilizer | Lithium | QTc ↑ | ++++ | |
Atypical antipsychotics | Aripiprazole | D2-, 5HT1-partial agonist | QTc ↑, HR ↑ | ++ |
Quetiapine | D2-, 5HT2-antagonist | QTc ↑, BP ↓ | +++ | |
Clozapine | D2-, 5HT2-antagonist | QTc ↑, HRV ↓, HR ↑, BP ↓ | ++++ | |
Response accelerator | (Es)ketamine | NMDA-antagonist | BP ↑, HR ↑ | +o |
Hypnotics | Lorazepam | GABA-modulator | Evidence weak | |
Zopiclone | GABA-agonist | Evidence weak |
Vortioxetine is approved by the European Medicines Agency but not marketed in Germany.
0 ‘Very low', + ‘Low', ++ ‘Medium', +++ ‘High', ++++ ‘Highest (contra-indicated).
Cardiovaskular risk estimation:
o . | + . | ++ . | +++ . | ++++ . |
---|---|---|---|---|
Very low | Low | Medium | High | Highest (contra-indication) |
o . | + . | ++ . | +++ . | ++++ . |
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Very low | Low | Medium | High | Highest (contra-indication) |
BP, blood pressure; HR, heart rate; HRV, heart rate variability; MI, risk for myocardial infarction.
Cardiovaskular risk estimation:
o . | + . | ++ . | +++ . | ++++ . |
---|---|---|---|---|
Very low | Low | Medium | High | Highest (contra-indication) |
o . | + . | ++ . | +++ . | ++++ . |
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Very low | Low | Medium | High | Highest (contra-indication) |
BP, blood pressure; HR, heart rate; HRV, heart rate variability; MI, risk for myocardial infarction.
Treatment-resistant depression
A substantial proportion of CHF patients with comorbid depression suffers from a protracted, often treatment-resistant clinical course forcing cardiologists to achieve a competence in delegation by rapidly involving psychiatric specialists for further anti-depressive treatment. Here, psychiatrists have several third line treatment options at hand, among them the irreversible monoamine oxidase inhibitor tranylcypromine for which a protective effect in CHF is currently discussed.95 Caution is warranted for lithium96 and also for atypical newer generation antipsychotics which may cause serious cardiovascular side-effects including QT interval prolongation.97 Electrocardiogram monitoring98 and detailed individual risk estimation when using these medications is mandatory. The cardiac safety profile of intranasal administration of esketamine (an NMDA receptor antagonist) seems to be acceptable.99
Benzodiazepines and non-benzodiazepine hypnotics (Z-substances)
Benzodiazepine derivatives are frequently used in case of acute suicidality, agitation, and anxiety and considered as relatively safe medications with low risk of cardiac safety-related problems apart from increases in nocturnal blood pressure in the elderly.100 For non-benzodiazepine hypnotics (e.g. zolpidem), no specific cardiac risks have been published101 but the body of evidence is relatively weak.
Other intervention options to improve psychosocial risk factors in patients with chronic heart failure
Herbal antidepressants
The herbal antidepressant hyperforin, a major constituent of St. John’s Wort preparations (Hypericum perforatum) represents a treatment alternative for patients with CHF. It seems to have anti-inflammatory properties.102 Safety and tolerability are better than that of SSRIs.103 Nevertheless, the risk of a substantial interaction potential with concomitant cardiac medications has to be taken into consideration.
Polyunsaturated omega-3 fatty acids
Advantages of polyunsaturated omega-3 fatty acids (n-3 PUFA) in CHF are supported by intervention studies104 beneficial effects for CHF are suggested predominantly by preclinical studies, but also by an epidemiologic study.105 Several reviews and meta-analyses confirmed the efficacy of n-3 PUFA in the treatment of depression.106 Many depressed patients have a deficiency of these nutritional factors107 and n-3 PUFA prescription may therefore be beneficial for both, the treatment and for the secondary prophylaxis of cardiac disorders.108 Sufficient dosage is needed to induce a satisfactory reduction in depressive symptoms.108
Exercise-based interventions
Exercise training programmes are a crucial part of CHF rehabilitation and have benefits for physical and mental health (including QoL) even in CHF patients with severely reduced systolic left ventricular function.49 Nevertheless, they still are poorly implemented in European countries, mainly because of the lack of resources or national guidelines.109 Research on the effects of exercise training on depression in CHF is summarized in a meta-analysis (k = 16, N = 3226) evidencing a reduction in depressive symptoms (SMD = −0.38),109 particularly in patients >65 years and in those with poor systolic function. Centre-based interventions (vs. home setting) have stronger effects on depression.110 Another meta-analysis of RCTs (k = 12 studies, 516 patients) indicates that combined aerobic and resistance training improves exercise capacity, muscle strength, and 6-min walk distance as well as QoL in patients with CHF. Here, no effects were found for depression and sleep.111 However, a meta-analysis of 21 studies (k = 21; total N = 4563) comparing different treatment approaches on reducing depression in CHF patients, evidenced the strongest improvements in depression following physical exercise training (effect size SMD) = −0.38 (SMD −0.16).65 Individually adapted supervised exercise training—although not always associated with improved clinical prognosis in terms of mortality—goes along not only with an increased exercise capacity but also with enhanced QoL. Against this background, an important recommendation is to establish ambulatory ‘heart failure groups’ not only providing a ‘CHF-specialized’ supervised exercise training but also contributing to the improvement of QoL by maintaining the individual exercise capacity and by supporting continuous social contacts of these patients. Adverse events are rare if the programme is gradually incremental in volume/intensity. Key point here is that patients need interventions to be weaned off supervised sessions and encouraged how to integrate physical activity into their daily lives. Complementing structured exercise programs with CBT possibly further enhances their favourable effects.65,66 In the future, digital health technologies may also help to promote sustained physical activity behaviour changes.112
1. State-of-the-science:
Multiple (psycho) therapeutic options are available for treating CHF patients with mental impairments. However, currently, no single approach is completely convincing.
Complementing exercise programmes can possibly enhance the benefits of psychological interventions.
Cognitive behavioural therapy seems to be moderately effective in improving depressive symptoms and possibly other mental comorbidities in CHF resulting in small improvements in QoL but without clear benefit in terms of somatic disease outcomes.
Multiple psychopharmacological interventions are available for patients with CHF but may all increase all-cause mortality risk. Caution is warranted.
Monitoring the continuous disease progression with increasing suffering from disabling symptoms during psychotherapy and psychopharmacological interventions is mandatory.
Treatment possibilities for mental health conditions (including the use of psychotherapy) should be discussed openly with all potential (dis)advantages in patients with CHF, applying a shared decision-making process.
Initiating ambulatory ‘heart failure groups’ which provide a ‘CHF-specialized’ supervised exercise training may contribute to the improvement of QoL by maintaining the individual exercise capacity and by supporting continuous social contacts of these patients.
2. Knowledge gaps:
More research is needed to support conclusive evidence for other forms of psychotherapy than CBT in CHF and which patients will benefit most.
Because of the scarcity of clinical trials, there is still little evidence that antidepressants are effective for depression in patients with CHF.
The complex crosstalk of psychopharmacology on decompensated heart muscle cells (among others by influencing norepinephrine-related pathways) is only poorly understood, so careful monitoring for negative cardiovascular side effects of antidepressants is required.
Health psychology research on how to motivate patients in the early stages of HF to engage in regular exercise training is lacking.
Devices in patients with chronic heart failure: implantable defibrillators and left ventricular assist devices
Implantable cardioverter-defibrillators
Implantable cardioverter-defibrillators (ICDs) continuously monitor cardiac rhythm and provide overdrive pacing in case of ventricular tachycardia and an electric shock in case of a life-threatening arrhythmia such as ventricular fibrillation. Specific device settings are tailored to the patient’s clinical characteristics. Having an ICD may be associated with substantially elevated psychological burden and often results in anxiety related to experiencing an (appropriate or inappropriate) ICD discharge which can be very painful. The current state of knowledge on the prevalence of depression and anxiety in patients with an ICD is not convincing: a meta-analyses covering over 5000 patients with an ICD from 45 studies disclosed a wide range of 11–28% of patients suffering from depression and 11–26% who had an anxiety disorder.113
Phobic anxiety may be up to be 10-fold higher in patients with an ICD compared to the general population and data from a prospective 7-years of follow-up clinical study indicated a progressive increase in phobia incidence (31% vs. 24%, P = 0.048).112 Depression is an independent risk factor for experiencing adequate ICD discharges114 and is also associated with (total) mortality.115 Among ICD patients, posttraumatic stress disorder should also be taken into consideration as it may impact survival independent of depression and major concurrent somatic risk factors.116
Surprisingly, studies do not find substantially different levels of QoL in patients with an ICD compared to non-ICD controls but shocks appear to adversely affect QoL.117 Few studies have been conducted on psychological interventions in patients with ICD, with some meta-analytic evidence supporting the effectiveness of CBT for depression and anxiety118 and that individual tailoring of interventions will be essential.119 Because most patients with ICDs have relatively minor CHF symptoms (NYHA class I/II), psychological problems in ICD patients are in most cases related to experiencing shocks from the device.
Left ventricular assist devices
Mechanical circulatory support systems [left ventricular assist devices (LVADs)] were originally conceived as temporary treatment for heart transplant candidates (‘Bridge-To-Transplant’ BTT) as strategy to rescue patients with end-stage HF.120 However, given the growing prevalence of end-stage CHF and the limited availability of organs for transplantation, utilizing LVAD solely as BTT is subject to the current debate and is increasingly in use as a permanent therapy (‘Destination Therapy’ DT)121 further stimulated by the advent of smaller continuous flow (CF) pumps. Conservative estimates count a total of 500 000 eligible patients with CHF in the EU and an annual implantation rate of >2000 LVADs.122
Accompanying measures how to cope psychologically with an LVAD are urgently needed.123 Living with an LVAD is very challenging for both the patients and their caregivers. During the pre-implantation phase, patients with advanced CHF experience severe and frightening symptoms. They face an excess risk of dying (>90%) within 1 year. Comorbid depression and anxiety (including fear of death) in this stage is omnipresent. Patients often employ denial to cope with such an almost unbearable situation. In one study, physicians regarded 69% of CHF patients to be at high risk for transplant, LVAD, or death, whereas only 14% patients felt they were at high risk.124
Patients undergoing LVAD implantation must strictly adhere to medical therapies. Substance abuse contraindicates LVAD placement.122 Implantation of an LVAD requires open-heart surgery often accompanied by cognitive decline and delirium in the immediate aftermath and the risk of serious adjustment disorders.125 Nevertheless, in the post-acute implantation phase, most CHF patients with DT experience a relief reaction with the strongest improvements in patients’ QoL in the first month after LVAD placement.126 Data from RCTs consistently demonstrate that ≈80% of patients achieve an NYHA functional class I/II symptom level at 24 months post-implantation contributing to an immediate improvement in QoL127 (whereas it tends to decrease while patients wait for a transplant).128
Nonetheless, major restriction in daily life caused by technical features of the extracorporeal support system (e.g. a percutaneous driveline connected to an external controller and energy source requiring replacement every 4–12 h) often compromise the patient’s relief reaction. The CF pumps inhibits the perception of heart beats/peripheral pulses thus further contributing to a continuous adverse awareness of being dependent on the functioning of a technical device. Notably, patients experience high rates of LVAD-related adverse events (e.g. 65–80% 1-year rehospitalization rates).129 Gradually, levels of psychological distress, depression, and poor QoL130 may increase again. Of note, depression in this stage is associated with increased risk of readmission.131
Remarkably, despite all these obstacles, the majority of patients achieve a satisfactory mental health status quo. Social network and marital status are important factors for good outcomes with LVAD therapy.132 Left ventricular assist device patients who are ambulatory stable may even safely return to driving without an increased risk of motor vehicle accidents.133 Caregiver engagement plays an important role in the care of patients with an LVAD. Pursuing an LVAD is a major ‘preference-sensitive decision’134 that requires high-level caregiver engagement and specific knowledge. Currently, feasible strategies on how to involve caregivers or how to apply shared decision are lacking.134 Most caregiver distress occurs prior to LVAD placement and in the first month after LVAD placement.126 A better understanding of the role of patients’ caregivers when considering LVAD placement and during post-LVAD follow-up is needed.
1. State-of-the-science:
The number of patients with CHF who are eligible for treatment with an ICD or LVAD is increasing rapidly.
Assessments regarding the impact of technological device innovations on psychological conditions to minimize unnecessary interventions and to prevent psychological and ethical conflicts are sparse.
Adequate concepts of how to cope psychologically with living with these medical devices are missing.
2. Knowledge gaps:
Systematic psychological counselling of patients and their caregivers should be an integral part of the ICD and LVAD treatment management. Tools and concepts are missing.
Development of critical management tools is urgently required.
Palliative care in end-stage chronic heart failure
In their final few months, Patients wih CHF are often faced with burdensome and debilitating symptoms, with increasing cognitive impairments and loss of independence, often overshadowed by the increasing awareness of dying soon.135 Up to 40% of patients will die within 12 months of first CHF hospitalization,135 and many physical symptoms (e.g. pain and severe shortness of breath136) are often under-treated and emotional symptoms (e.g. depression) are under-recognized.137 Therefore, the need for palliative care in patients with CHF is increasingly acknowledged.138 In this paper, we maintain a neutral attitude towards assisted suicide or euthanasia, which has been recently legalized in some but not all European countries.
Palliative care focuses on maximizing QoL and reducing suffering for patients and families at the (anticipated) last stages in their life cycle, where the aims clearly differ from standard medical care. However, because of the unpredictable trajectory of CHF, palliative care should not be viewed as an intervention of last-resort.139 An interdisciplinary palliative care approach can improve QoL for patients and their families at various stages of the disease.140 Of note, the European Society of Cardiology (ESC) 2020 position paper138 emphasizes the need to steadily revisit earlier decisions on therapy, recalibrating goals of care because of the inexorable nature of end-stage CHF progression. Palliative care providers need to acknowledge that previously expected outcomes may have become unrealistic and may now represent false hopes.
Multidisciplinary palliative care approaches are highlighted in systematic reviews of RCTs141 evidencing that such approaches lead to decline in symptom burden and depression, to better QoL and functional status, patient and caregiver satisfaction. Basic levels of palliative care should therefore be provided by both primary care clinicians and cardiologists and should address the needs of patients with CHF and their families. In some European countries, community support care models but also practitioners who specialize in palliative care are now available. However, to date, only a minority of patients with end-stage CHF receive help in designated palliative care units in the EU.138 Systemic and organizational factors, insufficient staff training and attitudes, along with the unpredictability of the HF trajectory and missing agreement regarding referral criteria, contribute to this lack of care. Also, a multitude of ethical, legal, family, and psychosocial issues can act as barriers to palliative care provision.
1. State-of-the-science:
An interdisciplinary palliative care approach and advanced care planning appear to increase QoL in patients with CHF and their families.
Because of the unpredictable trajectory of CHF, palliative care should not be viewed as an intervention of last-resort. We support earlier integration of advanced care planning into CHF management.
2. Knowledge gaps:
Further research is required to enhance confidence in this evidence, to determine which individuals will benefit, and the optimal settings for such care. The psychological impact on care providers should also be investigated. Currently, such research and funding is insufficiently prioritized.
There is an urgent need to develop training curricula for all healthcare providers dealing with CHF patients to increase professional competence in order to assist patients and their family members in all issues surrounding the inexorable progressing terminal phase of life.
General conclusions
Recent years have witnessed an increasing interest of implementing psychosocial aspects into every day cardiology practice throughout Europe. In support of this paradigm shift, the present position paper argues for the inclusion of these issues in the diagnosis and treatment of patients with CHF by systematically outlining the scientific evidence relevant for this achievement and by providing practical recommendations.
Evidence from large-scale prospective population-based and long-term clinical studies confirm the effect size of psychosocial risk factors for incident CHF and as prognostic covariates in the long-term course of the disease where they are associated with poor QoL, an unfavourable prognosis and increased mortality rates. Particularly for depression and social isolation/loneliness, findings are strong enough to encourage clinicians to assess these conditions in patients at high risk of CHF and during clinical evaluation.
Disease progression is likely to facilitate increased awareness of limited life expectancy, resulting in transient episodes of despair and hopelessness, which may compromise effective treatment and end up in refractory depression.
Chronic heart failure progression associated with mental health impairments is mediated in part by biological processes (autonomic dysregulation, neuro-endocrine processes, and inflammation), all likely contributing to a dysregulated compensatory neuro-hormonal overdrive in CHF progression.
Physicians should be aware that mental health impairments often facilitate denial of illness reality and cause reduced adherence to effective therapeutic interventions and lifestyle changes. Moreover, they are often associated with self-damaging behaviour (such as medication non-adherence, physical inactivity, poor dietary control, insufficient self-care) which yield an independent impact on CHF disease progression.
Multiple treatment options exist for depression in CHF, with the strongest evidence for exercise and CBT. However, such interventions are likely to miss essential psychological processes that are important to patients with CHF, particularly those related to end-of-life issues, dealing with frightening physical symptoms and limitations.
This position paper provides an in-depth overview about anti-depressive medication strategies which are however of questionable use for alleviating depressive symptoms and improving QoL in patients with CHF. It clearly states antidepressants whose use may come at a price for increased mortality. For treatment-resistant depression, it argues for a competence in delegation and proposes to refer these patients to specialized psychiatrists.
Engagement of CHF patients with the goal to maintain their own health is of utmost importance. Among brief psychological techniques promoting self-care, MI is receiving increasing attention. Interventions to improve self-care should be components of structured cardiac rehabilitation.
It is expected that novel blended collaborative care and remote monitoring techniques will be useful in helping patients and the families deal with CHF because they enable easy access, reduce hospital-based assessments, and create flexibility in methods and patient-tailoring of interventions. In addition to family-related issues, ethnic and cultural factors are important factors to consider in integrative CHF care.
E-health strategies are likely to become a major treatment option in the future. However, these technical strategies should not replace direct personal support. A careful balance needs to be found between these e-health interventions and personal provider-patient interactions that facilitates in-depth discussions of personally relevant issues.
A substantial proportion of patients with CHF require device therapy (ICDs or LVADs) at some time of the disease progression. Resourcing of psychological counselling of these patients and their caregivers urgently needs to become an integrative part of device treatment.
The unpredictable clinical disease progression of CHF is a major challenge for patients and their families. We support earlier integration of palliative care and advanced care planning at an early stage of CHF into CHF management. When possible, caregivers should be involved in decision making with regard to complicated care and end-of-life decisions.
There is an urgent need to develop training curricula for all healthcare providers dealing with CHF patients to increase professional competence in order to assist patients and their family members in all issues surrounding the inexorable progressing terminal phase of life.
Heart failure is a multifactorial syndrome and, consequently, a multi-approach strategy is needed to reduce risk and cope with the disease. There is a substantial mismatch between ‘objective’ disease indicators such as LVEF and blood-based biomarkers associated with CHF, and patients’ symptoms and functional abilities. The evidence reviewed here indicates that psychosocial factors are strongly interrelated with biological and functional aspects of CHF by interfering the patients’ QoL and CHF-related healthcare decisions. The scientific evaluation of patient-centred approaches that address psychosocial and biomedical processes and related interventions require different methodologies than standard RCTs; there is a need for new research methodologies in this area. Future collaborations with other European clinical and research societies that focus on the management of heart failure are needed to optimally integrate the present suggestions with clinical practice.
Acknowledgements
All authors were equally involved in the preparation, drafting, and revision of the manuscript and approve this version of the document. We would like to thank Mrs Carla Figueroa MD and Elisabeth Olliges, PhD for their expert administrative assistance.
Conflict of interest: The authors do not declare financial or other conflicts of interest related to this paper. The disclosures below cover the three-years period and are all outside this work. KHL received lecture honoraria from Bayer Health Care, BKK, MediClinAlbert Schweitzer, Novartis and Weleda, research support from the German Ministry of Education and Research (BMBF), the German Research Foundation (DFG), and the German Heart Association. KHL is on the advisory board of Idorsa (Switzerland). TCB reports honoraria from Neuraxpharm, Janssen and Servier. TCB received research grants from the Ministry of Education and Research (BMBF) and the German Research Foundation (DFG). FD has received research support from the Irish Research Council, the Health Research Board and the European Commission. MH has no conflicts of interest to disclose. CHL is receiving royalties from Hogrefe Huber Publishers for the German version of the Hospital Anxiety and Depression Scale. CHL received lecture honoraria from Pfizer and Novartis and research support from the German Ministry of Education and Research (BMBF), the German Research Foundation (DFG), and the European Commission. EK reports honoraria from Astra-Zeneca. CL reports personal fees and nonfinancial support from Boehringer Ingelheim, Janssen-Cilag, Lundbeck, Otsuka Pharmaceutical. MB has no conflicts of interest to disclose. AC receives research support from the Italian Research Council (IRC), Regione Lombardia. RvK reports honoraria from MSD, Vifor, Schwabe and Heel. HBS has received funding from the European Research Council under the European Union’s Horizon 2020 Research and Innovation Programme (STRATO, grant agreement No. 759272), the “Else-Kröner-Fresenius-Stiftung” (2020_EKSE.07) and the German Research Foundation (DFG) (SA 1668/5-1). WJK receives research support from the Dutch Research Council (NWO) and the European Commission.
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