Several studies suggest that psychological factors are associated with negative outcomes and in particular higher mortality rates among heart failure (HF) patients. We aimed to evaluate the effect sizes of depression and anxiety on all-cause mortality in HF patients. We conducted a systematic review according to the PRISMA methodology. We searched for studies on depression or anxiety effects on all-cause mortality among HF patients published up to June 2015. A number of 26 and 6 articles met inclusion criteria for depression (total 80,627 patients) and anxiety (total 17,214 patients), respectively. The effect estimates were pooled using random-effect meta-analysis. Depression has significant and moderately heterogeneous effect on all-cause mortality (HR = 1.57; 95%CI 1.30-1.89, p < 0.001); adjustment for confounders led to a similar effect estimate (HR = 1.40; 95%CI 1.22-1.60; p < 0.001). Larger studies and higher study prevalence of depression were associated with smaller effect size. The effect of anxiety on mortality outcome was small and not conclusive given the low number of studies (n = 6) (HR = 1.02; 95% CI 1.00-1.04, p < 0.05). This systematic review and meta-analysis suggests that depression is an important and independent predictor of all-cause mortality among HF patients, while anxiety does not appear to have a strong effect. Further research is recommended toward the detection and treatment of depression.

Psychosocial factors are strongly associated with unplanned recurrent readmissions or mortality following an admission to hospital for HF. Further research is needed to show whether recognition of these factors and support tailored to individual patients' needs will improve outcomes.

Background: Models for predicting the outcome of patients hospitalized for heart failure (HF) rarely take a holistic view. We assessed the ability of measures of frailty and social support in addition to demographic, clinical, imaging and laboratory variables to predict short-term outcome for patients discharged after a hospitalization for HF. Methods: OPERA-HF is a prospective observational cohort, enrolling patients hospitalized for HF in a single center in Hull, UK. Variables were combined in a logistic regression model after multiple imputation of missing data to predict the composite outcome of death or readmission at 30 days. Comparisons were made to a model using clinical variables alone. The discriminative performance of each model was internally validated with bootstrap re-sampling. Results: 1094 patients were included (mean age 77 [interquartile range 68-83] years; 40% women; 56% with moderate to severe left ventricular systolic dysfunction) of whom 213 (19%) had an unplanned re-admission and 60 (5%) died within 30 days. For the composite outcome, a model containing clinical variables alone had an area under the receiver-operating characteristic curve (AUC) of 0.68 [95% CI 0.64-0.72]. Adding marital status, support from family and measures of physical frailty increased the AUC (p<0.05) to 0.70 [95% CI 0.66-0.74]. Conclusions: Measures of physical frailty and social support improve prediction of 30-day outcome after an admission for HF but predicting near-term events remains imperfect. Further external validation and improvement of the model is required.