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European Journal of Heart Failure 2002 4(4):541-551; doi:10.1016/S1388-9842(02)00101-0
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© 2002 European Society of Cardiology

Clinical depression is common and significantly associated with reduced survival in patients with non-ischaemic heart failure

R. Farisa,*, H. Purcella, M.Y. Heneina and A.J.S. Coatsa,b

a Department of Clinical Cardiology, Royal Brompton Hospital London, UK
b Department of Cardiac Medicine, The National Heart & Lung Institute, Imperial College School of Science, Technology, and Medicine, The Royal Brompton Hospital Dovehouse Street, London, SW3 6LY, UK

* Corresponding author. Fax: +44-20-7376-3442 E-mail address: rajaa_faris18{at}hotmail.com E-mail address: r.al-faris{at}ic.ac.uk


   Abstract
Top
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Limitations
 6. Conclusion and future...
 References
 
Several studies have shown that depression is an important predictor of morbidity and mortality in patients with ischaemic heart failure. We have investigated whether clinically recognised depression is linked to mortality in patients with non-ischaemic heart failure due to dilated cardiomyopathy (DCM) in the Royal Brompton Hospital (RBH), a tertiary cardiac centre located in London, UK. We retrospectively examined a cohort of 396 consecutive adult patients with DCM who satisfied our inclusion and exclusion criteria identified from an echocardiographic database and the hospital medical records. Mean age was 53±15 years. In all, 83 patients (21%) were clinically depressed, the majority of which (60%) were taking antidepressant therapy. After a follow-up period of 48 months, 83 (21%) patients died, 15 (4%) underwent cardiac transplantation and 130 (33%) were readmitted; 29 (35%) of the deaths and 40 (31%) of the readmissions were among clinically depressed patients. After 5 years, clinically depressed patients had significantly higher mortality and readmission rates than non-depressed; 36 vs. 16% (hazards ratio for death, 3.0; 95% CI, 1.4–6.4; P=0.004), and 87 vs. 74% (hazards ratio for readmission, 0.25; 95% CI, 0.07–0.90; P=0.03), respectively. The risk of depression was greatly increased in the presence of other recognised adverse clinical variables at baseline. Depression increases the risk of death and readmission in patients with heart failure secondary to non-ischaemic DCM. The risk associated with depression appears to be greatest among patients with milder disease, those with a shorter duration of symptoms and those demonstrating a lower systolic or diastolic blood pressure, renal impairment, or a restrictive left ventricular physiology on echocardiography. Interventions targeted at reducing depression warrant further study as a possible way to improve quality of life and/or outcome in patients with heart failure.

Key Words: Clinical depression • Survival • Non-ischaemic heart failure

Received May 18, 2001; Revised October 9, 2001; Accepted December 14, 2001


   1. Introduction
Top
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 5. Limitations
 6. Conclusion and future...
 References
 
Heart failure is a clinical syndrome that is increasing in incidence world-wide and carries a very high morbidity and mortality. Depression is relatively common in this population, with a reported prevalence between 24 and >40% in patients with stable heart failure [1,2]. Considerable attention has been directed towards the identification of risk factors for mortality in patients with ischaemic heart failure in order to assess prognosis and design appropriate interventions. Several studies have shown that depression is an important predictor of morbidity and mortality in these patients [3,4], but none of these studies has clarified the relationship between depression and markers of disease severity, such as the New York Heart Association (NYHA) classification in predicting prognosis. One hospital-based study and one community-based survey have reported the effect of depression on morbidity and mortality in patients with chronic heart failure [5,6]. Neither of these studies, however, evaluated the effect of depression on morbidity and mortality specifically in patients with heart failure secondary to non-ischaemic dilated cardiomyopathy. The effects on patients with or without atherosclerotic disease may well be different. In addition, these earlier studies focused on elderly patients and excluded younger age groups. The psychological effects of ischaemic heart disease might differ from other non-ischaemic causes of chronic heart failure and may depend on age. Our objective was, therefore, to determine whether depression is linked to mortality in a non-selected population of patients suffering from chronic heart failure due to non-ischaemic DCM.


   2. Methods
Top
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 5. Limitations
 6. Conclusion and future...
 References
 
2.1. Study population
Using hospital medical records and an echocardiographic database, we retrospectively identified 396 consecutive adult patients with a principal discharge diagnosis of heart failure due to non-ischaemic DCM (ICD-10 CM codes 142.0, 142.6, 142.8 and 142.9) [7]. All had attended the Royal Brompton Hospital between 1994 and 1998.

Exclusion criteria included: previously documented myocardial infarction; a history of angina or symptoms suggestive of myocardial ischemia; the demonstration of coronary arterial narrowing on coronary arteriography; or perfusion defects on thallium scanning. In addition, patients with aetiologically important valvular heart disease or documented hypertension were also excluded.

2.2. Clinical and follow-up data
Patients were followed for an average of 48±35 months (the maximum follow-up period was 84 months), starting from the first visit to the RBH clinic and ending with a cardiac event, heart transplant, or on the most recent date of follow-up in survivors. Demographic data and symptomatic status at study entry were assessed by careful review of the medical records. Heart rate and blood pressure were obtained as closely as possible temporally to the index echocardiogram and were used for data analysis. The interval from the onset of symptoms to first subsequent hospital admission was also analysed. Survival and symptomatic status at follow-up were determined from review of medical records, and by telephone contact with the patients’ usual physicians.

The following details were recorded from the patients records: (1) date of onset of symptoms; (2) duration of heart failure; (3) outcome (survival, hospital admissions); (4) NYHA functional class at baseline and at follow-up; (5) history of arrhythmia; (6) presence of other diseases at baseline that could have influenced survival (e.g. cancer, renal impairment or failure, COPD); (7) history of smoking or alcohol intake; (8) use of medications including ACE inhibitors, diuretics, amiodarone and antidepressants; (9) family history of DCM; and (10) subsequent number of hospitalisations (only those for worsening HF or pulmonary oedema were recorded).

At first assessment, all patients had a physical examination, including vital status. Of 396 patients, 383 (97%) had resting ECG, 363 (92%) had chest X-ray and CTR measurement, and 178 (45%) had 24-h ambulatory monitoring, All records were analysed by one observer.

2.3. Diagnosis of depression
Clinical depression was defined as the diagnosis of depression being listed in patients’ medical records as an active problem (ICD-10 code F32) [7], or being clinically diagnosed after a routine systematic psychological assessment in those patients being assessed for cardiac transplantation. The validity of a diagnosis of depression was carefully reviewed in those patients taking antidepressant medications to ascertain whether there was a history of receiving psychiatric care or treatment-seeking behaviour. Self-reported depression was not considered confirmed if the symptoms resolved in 2 weeks or less, or if the symptoms were exclusively related to reactive grief consequent upon specific incident(s). In this study, we chose a definition of clinical depression, and not a measure of depression symptoms based on a questionnaire or familiar tests or instruments. As a result, the term ‘major depression’ is not used. Our definition has underestimated the true prevalence of depressive symptoms in this population.

2.4. Echocardiographic data
All echocardiographic recordings (2-D, M-mode and Doppler) were performed in the echocardiography laboratory by an experienced operator. Echo-derived data were calculated by one analyser from a mean of three beats in patients with regular rhythm, and from six beats in patients with irregular rhythms. From the left ventricular minor-axis trace, we measured end-diastolic (EDD) and end-systolic (ESD) dimensions as defined by the American Society of Echocardiography using leading edge methodology [8]. Fractional shortening (FS %) was calculated using the standard formula [FS %=(EDD–ESD)/EDD]. Isovolumic relaxation time (IVRT) was taken as the time interval between the aortic component of the second heart sound (A2) of the phonocardiogram to the onset of mitral cusp separation from the mitral echocardiogram. From the transmitral pulsed Doppler trace, we measured peak early ‘E’ velocity with its deceleration time (DT), as well as late ‘A’ velocity, and hence the ‘E’/‘A’ ratio was calculated. Restrictive LV filling pattern was defined by a dominant ‘E’ velocity, a shortened deceleration time (<140 ms), and/or a shortened IVRT [9]. From each long-axis M-mode trace, the amplitude of long-axis shortening beyond A2 was taken as a sign of incoordination. From colour-flow and continuous-wave Doppler echocardiography, mitral regurgitation (MR) and/or tricuspid regurgitation (TR) were semiquantitatively graded from 1 to 3+ according to the American Society of Echocardiography [10]. A volume of regurgitation graded >1+ was considered significant.

Cardiopulmonary exercise testing with measurement of maximal oxygen consumption (MVO2max) was performed in 137 (35%) patients, determined by the request of the sponsoring cardiologist.

2.5. Outcome variables
The outcome variables of this study were (1) mortality, defined as a confirmed death or cardiac transplantation, and (2) hospital readmission for worsening heart failure. Information about death and heart transplant were determined from review of hospital records when available, or by telephone contact with the patient's referring physician.

2.6. Statistical analysis
Descriptive statistics were used to display the baseline characteristics and clinical outcomes of the study population: quantitative data are expressed as mean±standard deviation (S.D.) and qualitative data as percentages. Initially, comparisons between clinically depressed and non-depressed patients were made using the Student's unpaired t-test for continuous variables and the Chi square ({chi}2) test for nominal variables.

The association between baseline parameters and outcomes were evaluated with bivariate analysis and multivariate stepwise regression analysis (Cox proportional hazard model) [11]. Patients who died or were readmitted during the follow-up period were compared with patients who neither died nor were readmitted. To rule out the possibility that depressed patients were at greater risk because of more severe cardiac disease, we examined for possible differences in baseline characteristics between the two groups. Baseline variables that were significantly (P<0.05) related to outcomes in bivariate analysis were entered into a multivariate stepwise regression analysis to predict outcomes. A forward stepwise model with a P value ≤0.5 for entry was used. The results of the multivariate analysis were reported as hazards ratios with 95% confidence interval (CI). Survival was estimated by the Kaplan–Meier method, with the follow-up period starting at the index echocardiogram, and outcomes curves were compared using the log rank test to examine the differences between the groups. All tests were two-tailed. Statistical analyses were carried out on a personal computer using the STATVIEW 4.5 software package (Abacus Space Concepts, California).


   3. Results
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 5. Limitations
 6. Conclusion and future...
 References
 
3.1. Baseline characteristics of the study population
The cohort was composed of 396 consecutive patients, mean age 53±15 years (range 15–86). The majority (74%) were men, married (65%) and white (83%). The mean duration of heart failure symptoms was 65±60 months. Only 10% of the patients were in NYHA symptom class IV, 33%, 37% and 20% were in classes I, II and III, respectively. A total of 83 patients (21%) satisfied our criteria for being defined as clinically depressed. The mean fractional shortening on the echocardiogram was measured at 17±8%. Medical treatments included digoxin in 182 patients (46%), diuretics in 314 (81%), ACE inhibitors in 317 (80%), β-blockers in 35 (8%), and amiodarone and warfarin in 120 (46% each). Antidepressants were used in 63 (76%) of the depressed patients; the majority were taking tricyclics 38 (60%), with 25 (40%) taking selective serotonin reuptake inhibitors (SSRIs). None of the depressed patients had received electroconvulsive therapy (ECT) (Table 1).


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  		Table 1 Baseline characteristics of study population

 
3.2. Follow-up and clinical outcomes
The mean follow-up period was 48±35 months (range 3–84 months). During this period, 83 patients (21%) died and 15 (4%) required heart transplantation. The majority of deaths (86%) were due to progressive pump failure. There were 660 hospital readmissions during a total follow-up period of 396 patient-years, giving a readmission rate of 1.7 per patient-year. Tables 1 and 2, and Figs. 1–3 show comparisons of outcomes between depressed and non-depressed patients.


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  		Table 2 Comparison of study outcomes between clinically depressed and non-depressed patients

 


Figure 1
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  		Fig. 1 Cumulative Kaplan–Meier survival curve in the present series: P=0.004.

 


Figure 2
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  		Fig. 2 Cumulative Kaplan–Meier readmission curve in the present series: P=0.008.

 


Figure 3
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  		Fig. 3 Comparisons of admission rates between (a) clinically depressed patient and (b) non-depressed patients.

 
Comparisons of baseline characteristics between clinically depressed and non-depressed patients are presented in Table 1. At baseline, clinically depressed patients were more symptomatic (P<0.0001), had a longer duration of symptoms (P=0.04), a lower blood pressure (P=0.005) and more hospitalisation episodes (P=0.001). They also had lower exercise capacity (P=0.02), poorer LV function (P=0.04), a shorter isovolumic relaxation time (IVRT) (P=0.04) and more restrictive LV filling (P=0.009) on echocardiography. Furthermore, they were more likely to have left bundle branch block (P=0.05) and renal impairment (P=0.008).

3.3. Effect of depression on mortality and readmission
Table 2 shows comparisons of mortality and readmission rates between clinically depressed and non-depressed patients. The unadjusted and age-adjusted mortality rates were more than doubled in clinically depressed patients (hazards ratio for death, 2.1; 95% confidence interval (CI), 1.4–3.2; P=0.004). In the final Cox model, after adjusting for baseline characteristics in addition to age and antidepressant treatments, the risk of death in clinically depressed patients tripled (hazards ratio, 3.0; 95% CI, 1.4–6.4; P=0.004). Depression was also associated with a higher rate of readmission (adjusted hazard ratio for readmission, 0.25; 95% CI, 0.07–0.90; P=0.03). Figs. 1 and 2 show the estimated cumulative survival and readmission rates for depressed and non-depressed patients. After 1, 3 and 5 years, the survival and readmission rates for non-depressed patients were significantly better than for those who were clinically depressed [97, 93 and 84% vs. 91, 81 (Fig. 1) and 66%, P=0.004; and 96, 90 and 74% vs. 100, 98 and 87% (Fig. 2), respectively]. The factors most strongly related to death and readmission are summarised in Tables 3 and 4. Depression was not significantly related to gender, family history of DCM, social status, smoking, prevalence of alcohol intake or exercise capacity (peak MVO2).


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  		Table 3 Correlates of mortality and hospital readmission in bivariate analysis

 


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  		Table 4 Correlates of mortality and hospital readmission in multivariate analysis

 
3.4. Effect of antidepressants on mortality
Tricyclic agents, which were the antidepressants most commonly used by the majority of clinically depressed patients, are known to have cardiotoxic effects, and the use of these agents may explain the apparent association between clinical depression and death. The risk of death for patients reporting treatment with antidepressants (hazards ratio for death, 0.52; 95% CI, 0.31–0.87; P=0.01) did not differ from that for those reporting no treatment (hazards ratio for death, 0.63; 95% CI, 0.33–1.20; P=0.16).

3.5. Correlates of death and readmission
In bivariate analysis, 17 variables predicted mortality, including age, NYHA functional class, diastolic BP, bundle-branch block and incoordinate ventricular wall-motion. A total of 17 parameters were associated with hospital readmission in bivariate analysis, including living alone, being unemployed, history of alcohol consumption, atrial fibrillation, QRS duration on ECG and peak oxygen consumption (Table 3).

In Cox stepwise regression analysis, to determine whether the association between clinical depression and the outcomes were independent of demographic factors, medical history, baseline functional status and clinical severity, we adjusted for these variables in a multivariate model. After adjusting for all these variables, depression remained as a significant independent predictor of prognosis. In addition, multivariate analysis identified the following six parameters that were also statistically significant and independent predictors of poor survival: age; duration of symptoms; NYHA class; resting diastolic blood pressure; renal impairment; and restrictive LV filling on Doppler echocardiography. Seven variables were significantly associated with a higher rate of hospital readmission: living alone; being unemployed; duration of symptoms; history of alcohol consumption; resting systolic BP; renal impairment; and QRS duration on ECG (Table 3). Two variables were positive independent predictors of mortality and hospital readmission in multivariate analysis: (1) short duration of symptoms; and (2) renal impairment. Figs. 4 and 5 show the influence of those variables on mortality and readmission.


Figure 4
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  		Fig. 4 (a) Correlates of death in clinically depressed patients vs. non-depressed in multivariate analysis. (b) Correlates of readmission in clinically depressed patients vs. non-depressed in multivariate analysis.

 


Figure 5
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  		Fig. 5 Correlates of death and readmission in clinically depressed patients vs. non-depressed in multivariate analysis.

 

   4. Discussion
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
5. Limitations
 6. Conclusion and future...
 References
 
4.1. Effect of depression on mortality
It has been reported elsewhere that patients with chronic heart failure due to various causes suffer more frequently from moderate to severe depression than patients with other chronic diseases (e.g. cancer, lung diseases) [12–14]. The combination of depressive symptoms with another medical condition appears to result in additive effects, further worsening of physical functioning [13], affecting quality of life [12] and potentially decreasing survival [3]. It has also been shown that the effective management of depression can help patients cope better with other illnesses. The overall prevalence of depression across all age groups of the general population is approximately 5–6% [15]. The prevalence is 3–10-fold higher in patients with cardiac disease [22,23].

The overall prevalence of depression in chronically ill patients has been estimated to be approximately 20% [16,17], but in more severely ill hospitalised patients, the prevalence can be between 40 and 60% [18,19]. In ischaemic heart failure patients, the prevalence of depression has been estimated to be between 18 and 60% [18]. In this context, although at the lower end, the prevalence of depression (21%) among patients with dilated cardiomyopathy in our study is comparable with that found in other severely ill patients, including those with ischaemic heart failure [15]. Our study cohort was, however, younger and with more mildly diseased patients affecting our referral patterns.

Our study demonstrates that, among patients with heart failure due to non-ischaemic DCM, depression was associated with a significantly higher risk of death and hospital readmission. The association was strong, and was not explained by sociodemographic factors, baseline functional status, medical history or other baseline characteristics. Furthermore, the risk associated with depression was strongly increased by several background demographic and clinical characteristics. Interestingly, age was not significantly associated with readmission in our study, although age above 53 years increased the likelihood of death in clinically depressed patients. One study has not agreed with this finding [5]. However, this earlier study evaluated elderly (age 65 years and above) patients hospitalised with congestive heart failure.

In previous studies of patients with ischaemic heart failure [19–21], depression was not related to the severity of disease. In the current study, despite the greater prevalence of depression among patients with more severe heart failure (NYHA class>II), depression did not increase the risk of death in these patients, whereas it did in patients with milder disease (NYHA class ≤II). This finding indicates that, in the present study, clinically depressed patients may not be sicker than non-depressed patients, although they were more symptomatic. There are three possible explanations for this. First, the considerable overlap between symptoms of heart failure and those of depression (e.g. fatigue is common in both). Second, depression may have impaired the patient's ability to cope effectively with the disease, resulting in exaggerated behaviour in response to cardiac symptoms rather than being associated with disease severity. Third, depression and greater severity of the disease are competing rather than interacting risk factors for mortality, and therefore the presence of either indicates a poorer outlook.

We also found that restrictive left ventricular filling (RFP) on Doppler echocardiography was strongly related to the prevalence of depression, and it was also a powerful independent predictor of mortality in our study. This restrictive filling pattern has been found to be associated with severe impairment of haemodynamics, worse clinical functional class, severe reduction of exercise capacity [22–25] and poor outcome [25–27]. In our study, the prevalence of RFP was higher in clinically depressed patients who were more symptomatic with a poorer ventricular function and lower exercise capacity.

Exercise capacity (MVO2max) has been shown to provide long-term prognostic information in patients with heart failure [28,29], although not reaching significance in some other studies [30]. In the present study, however, MVO2max was not found to be a significant predictor of prognosis. This may be due to the fact that this parameter was available in only 37% of the study population and in the majority the exercise limitation was mild.

Several studies [5,31,32] have emphasised the value of social status and support (e.g. unmarried, living alone, unemployed) in predicting survival in patients with heart failure. This was not confirmed by our findings. One study, however, is in agreement with ours [33]. This may be due to the fact that the majority of our study cohort were married (65%), employed (51%) and living with a family or a partner (85%). Furthermore, the earlier studies focused on elderly hospitalised individuals who were clinically unstable [5,31], or institutionalised patients [32]. In our study, however, unemployment and living alone were associated with an increase in the risk of hospital readmission. This is in agreement with previous publications [5,34]. Although the exact mechanism of the association between these risk factors and readmission is not clear, there are three possible causes for this association. First, diminished access to skilful medical care in low-income patients due to unemployment appears to influence the risk of hospital admission among patients with heart failure [35]. Second, financial constraints and/or living alone could compromise compliance with treatment recommendations and lead to a higher rate of hospitalisation [34,36]. Third, related factors, such as alcohol abuse and cigarette smoking that are more common among unemployed patients and/or those without social ties, could also play an important role. Indeed, alcohol consumption was associated with an increased likelihood of rehospitalisation in our study.

In contrast with previous publications [37–39], we failed to find any relationship between depression and arrhythmias. However, one study [40] is in agreement with this finding.

Tricyclic antidepressants have been associated with an increased risk of mortality and/or sudden death in patients with cardiovascular diseases due to their cardiotoxic effects [41]. Since 1981, several investigators have warned about the use of tricyclic agents, particularly among those with cardiovascular disease [42]. Even though the majority of our depressed patients (60%) were taking tricyclic antidepressants, 26 (43%) of whom died during the follow-up period, the use of these agents was not related to prognosis in our study, either in bivariate or multivariate analysis. This finding is in disagreement with previous studies [40,42]. However, our finding is supported by that of Vieth et al. [43].

4.2. Mechanism of depression
Although the exact mechanism for the association between depression and mortality is unknown, a number of explanations are possible. First, this association may be mediated by other factors, such as smoking and alcohol consumption. In our data, however, depression was not associated with smoking or a history of alcohol abuse. Second, the association of depression with cardiovascular disease outcomes may also be related to reduced compliance with medication and exercise regimens, as has been observed in other depressed cardiac patients [44]. In our study, we did not have reliable information on adherence to medication during follow-up, and therefore we could not measure the role of this factor in our results. Third, depression may worsen prognosis of heart failure through direct physiological mechanisms. It has been speculated that depression may inhibit parasympathetic activity and/or stimulate sympathetic activity with subsequent changes in catecholamines and their associated effects on myocytes. Such effects could increase heart rate, decrease heart rate variability and contribute to cardiac arrhythmias and/or sudden cardiac death [44].


   5. Limitations
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Limitations
6. Conclusion and future...
 References
 
Our study has several limitations typical of this type of report. First, it was performed at a tertiary hospital, thus limiting its generalisability. Our patients were younger than typical heart failure patients in community studies. Second, the diagnosis of depression was obtained only at initial assessment and was based on a clinical diagnosis, and the duration of depression during follow-up was unknown. Third, we obtained most of the clinical information through review of patients’ medical records. Some data were therefore inevitably missing, and other variables, such as a family history of depression, may not have been consistently recorded by the physicians. This may make some of the variables included in our final analysis susceptible to bias. Furthermore, our study population mainly consisted of subjects with NYHA functional class ≤II (70%), and hence our findings may not be applicable to individuals with more severe heart failure.


   6. Conclusion and future directions
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Limitations
 6. Conclusion and future...
References
 
Despite the above limitations, this is one of the largest studies of prognosis in patients with heart failure due to non-ischaemic dilated cardiomyopathy (DCM) that has assessed clinical depression, rather than the level of depressive symptoms per se. The risk associated with depression is greatly increased by a number of factors, including age, NYHA class, duration of symptoms, heart rate, diastolic blood pressure, renal impairment and restrictive LV filling patterns on Doppler echocardiography.

Our findings emphasise the importance of depression, along with clinically relevant prognostic indicators of severity of myocardial disease and comorbidity, as risk factors for mortality and hospital readmission in patients with dilated cardiomyopathy. The findings also support published data showing that psychosocial intervention deserve consideration as a potentially important component of prevention programmes in addition to drug therapy and exercise regimens [35,45].

The principal unanswered questions remain primarily aetiologic and treatment-related. To address these questions, future prospective research should focus on: (1) identifying the mechanisms by which depression affects the cardiovascular system in patients with heart failure; and (2) identifying the biological markers associated with depression (e.g. markers related to the hypothalamic–pituitary–adrenocortical axis or sympatho-adrenal hyperactivity). Identification of the interrelations between the central nervous system and cardiovascular systems, particularly in depressed cardiac patients, might provide a target for the development of new treatment modalities, which could not only improve quality of life, but also potentially decrease morbidity. Other controlled prospective studies are required to address whether heart failure patients who are clinically depressed will benefit from psychosocial therapy, and whether this therapy will improve prognosis.


   References
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Limitations
 6. Conclusion and future...
 References
 

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