Prediction of outcomes in patients with heart failure

The main aim of this thesis is to explore risk factors associated to an increased risk of adverse outcomes for heart failure (HF) patients and improve the early re-admission or mortality prediction in HF. Data from two studies (OPERA-HF study in the UK and SAPHIRE study in US) has been used to explore a wide range of variables as potential risk factors. We found that depression is a significant and independent predictor of all-cause mortality among HF patients. Depression was also significantly associated with recurrent events: unplanned readmission or mortality. Other psychosocial or non-clinical variables independently associated with increasing risk of recurrent events in the year following discharge after a HF hospital admission were: presence of frailty, moderate-to-severe anxiety, living alone and the presence of cognitive impairment. We then used data from the OPERA-HF study to develop a 30-day composite outcome model and to explore the added predictive value of non-clinical predictors to early outcomes: 30-day unplanned readmission or mortality. The performance of the model improved by including physical frailty and social support next to clinical variables. The transportability of the model to a different geography was proved in the external validation of the model on the SAPHIRE study data. LUMC / Geneeskunde Repositoriu

Added value of frailty and social support in predicting risk of 30-day unplanned re-admission or death for patients with heart failure: an analysis from OPERA-HF

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

What does it take to make integrated care work? A ‘cookbook’ for large-scale deployment of coordinated care and telehealth

The Advancing Care Coordination & Telehealth Deployment (ACT) Programme is the first to explore the organisational and structural processes needed to successfully implement care coordination and telehealth (CC&TH) services on a large scale. A number of insights and conclusions were identified by the ACT programme. These will prove useful and valuable in supporting the large-scale deployment of CC&TH. Targeted at populations of chronic patients and elderly people, these insights and conclusions are a useful benchmark for implementing and exchanging best practices across the EU. Examples are: Perceptions between managers, frontline staff and patients do not always match; Organisational structure does influence the views and experiences of patients: a dedicated contact person is considered both important and helpful; Successful patient adherence happens when staff are engaged; There is a willingness by patients to participate in healthcare programmes; Patients overestimate their level of knowledge and adherence behaviour; The responsibility for adherence must be shared between patients and health care providers; Awareness of the adherence concept is an important factor for adherence promotion; The ability to track the use of resources is a useful feature of a stratification strategy, however, current regional case finding tools are difficult to benchmark and evaluate; Data availability and homogeneity are the biggest challenges when evaluating the performance of the programmes

The association of depression and all-cause and cause-specific mortality: an umbrella review of systematic reviews and meta-analyses

Background: Depression is a prevalent and disabling mental disorder that frequently co-occurs with a wide range of chronic conditions. Evidence has suggested that depression could be associated with excess all-cause mortality across different settings and populations, although the causality of these associations remains unclear. Methods: We conducted an umbrella review of systematic reviews and meta-analyses of observational studies. PubMed, PsycINFO, and Embase electronic databases were searched through January 20, 2018. Systematic reviews and meta-analyses that investigated associations of depression and all-cause and cause-specific mortality were selected for the review. The evidence was graded as convincing, highly suggestive, suggestive, or weak based on quantitative criteria that included an assessment of heterogeneity, 95% prediction intervals, small-study effects, and excess significance bias. Results: A total of 26 references providing 2 systematic reviews and data for 17 meta-analytic estimates met inclusion criteria (19 of them on all-cause mortality); data from 246 unique studies (N = 3,825,380) were synthesized. All 17 associations had P < 0.05 per random effects summary effects, but none of them met criteria for convincing evidence. Associations of depression and all-cause mortality in patients after acute myocardial infarction, in individuals with heart failure, in cancer patients as well as in samples from mixed settings met criteria for highly suggestive evidence. However, none of the associations remained supported by highly suggestive evidence in sensitivity analyses that considered studies employing structured diagnostic interviews. In addition, associations of depression and all-cause mortality in cancer and post-acute myocardial infarction samples were supported only by suggestive evidence when studies that tried to adjust for potential confounders were considered. Conclusions: Even though associations between depression and mortality have nominally significant results in all assessed settings and populations, the evidence becomes weaker when focusing on studies that used structured interviews and those that tried to adjust for potential confounders. A causal effect of depression on all-cause and cause-specific mortality remains unproven, and thus interventions targeting depression are not expected to result in lower mortality rates at least based on current evidence from observational studies

Factors associated with acute depressive symptoms in patients with comorbid depression attending cardiac rehabilitation

Background: The literature suggests that comorbid depression, defined in this paper as a history of depression prior to a cardiovascular event, has an impact on later onset depression as well as constituting increased risk of mortality and adverse cardiac events. However, which factors are associated with depression, specifically in patients with comorbid depression, is unclear. Therefore, this paper investigates the factors associated with depression in patients with comorbid depression attending cardiac rehabilitation (CR). Methods: This observational study used routinely collected data from the British Heart Foundation National Audit of Cardiac Rehabilitation for the time period between April 2012 and March 2017. CR participants with comorbid depression were selected as the study population. An independent t-test and chi-square test were used to compare the association between acute depression symptoms and baseline characteristics in this population. Results: A total of 2715 CR patients with comorbid depression were analysed. Characteristics associated with acute depressive symptoms in patients with comorbid depression were found to be: young age (MD: 2.71, 95% CI 1.91, 3.50), increased number of comorbidities (MD: -0.50, 95% CI -0.66, -0.34), increased weight (MD: -1.94, 95% CI -3.35, -0.52), high BMI (MD: -1.94, 95% CI -3.35, -0.52), HADS anxiety (MD: -5.17, 95% CI -5.47, -4.87), comorbid anxiety (52.4%, p < 0.001), physical inactivity (150 minutes moderate physical activity a week and 75 minutes vigorous exercise a week; 27.5%, p < 0.001; 5.6%, p < 0.001 respectively), smoking (12.7%, p < 0.001), and being less likely to be partnered (63.6%, p < 0.001). Conclusion: The study demonstrated the association between a variety of clinical and socio-demographic factors and depression. The findings of the research indicated that, at CR baseline assessment, caution must be taken with patients with comorbid depression, specifically those with higher level depressive symptoms at the start of rehabilitation. Furthermore, their multi-comorbid condition must also be taken into account. Patients with higher depression symptoms and comorbid depression scored five points higher on the HADS anxiety scale in comparison to patients with lower level depression symptoms at the start of CR, which demonstrated that anxiety and depression are interrelated and present together

Prediction of outcomes in patients with heart failure

The main aim of this thesis is to explore risk factors associated to an increased risk of adverse outcomes for heart failure (HF) patients and improve the early re-admission or mortality prediction in HF. Data from two studies (OPERA-HF study in the UK and SAPHIRE study in US) has been used to explore a wide range of variables as potential risk factors. We found that depression is a significant and independent predictor of all-cause mortality among HF patients. Depression was also significantly associated with recurrent events: unplanned readmission or mortality. Other psychosocial or non-clinical variables independently associated with increasing risk of recurrent events in the year following discharge after a HF hospital admission were: presence of frailty, moderate-to-severe anxiety, living alone and the presence of cognitive impairment. We then used data from the OPERA-HF study to develop a 30-day composite outcome model and to explore the added predictive value of non-clinical predictors to early outcomes: 30-day unplanned readmission or mortality. The performance of the model improved by including physical frailty and social support next to clinical variables. The transportability of the model to a different geography was proved in the external validation of the model on the SAPHIRE study data. </p

Prediction of outcomes in patients with heart failure

The main aim of this thesis is to explore risk factors associated to an increased risk of adverse outcomes for heart failure (HF) patients and improve the early re-admission or mortality prediction in HF. Data from two studies (OPERA-HF study in the UK and SAPHIRE study in US) has been used to explore a wide range of variables as potential risk factors. We found that depression is a significant and independent predictor of all-cause mortality among HF patients. Depression was also significantly associated with recurrent events: unplanned readmission or mortality. Other psychosocial or non-clinical variables independently associated with increasing risk of recurrent events in the year following discharge after a HF hospital admission were: presence of frailty, moderate-to-severe anxiety, living alone and the presence of cognitive impairment. We then used data from the OPERA-HF study to develop a 30-day composite outcome model and to explore the added predictive value of non-clinical predictors to early outcomes: 30-day unplanned readmission or mortality. The performance of the model improved by including physical frailty and social support next to clinical variables. The transportability of the model to a different geography was proved in the external validation of the model on the SAPHIRE study data. </p