Background: The prevalence of heart failure (HF) is expected to rise due to increased survivorship and life expectancy of patients with acute heart conditions. Patients with HF and other multiple comorbid conditions are likely to have poor health outcomes. This study aimed to assimilate the current body of knowledge and to provide the pooled effect of HF patients’ comorbid conditions on health outcomes. Methods: A systematic search was performed using MEDLINE, EMBASE and CINAHL databases. Observational studies evaluating the relationship between comorbid conditions and the health outcomes of HF were included. The pooled effect sizes of comorbidity on the identified health outcomes were calculated using a random effects model, and heterogeneity was evaluated using I2 statistics. Results: A total of 42 studies were included in this review, and a meta-analysis was performed using the results of 39 studies. In the pooled analysis, the presence of a comorbid condition showed significant pooled effect size in relation to the prognostic health outcomes: all-cause mortality (HR 1.31; 95% CI 1.18, 1.45), all-cause readmission (HR 1.16; 95% CI 1.09, 1.23), HF-related readmission (HR 1.13; 95% CI 1.05, 1.23), and non-HF-related readmission (HR 1.17; 95% CI 1.07, 1.27). Also, comorbidity was significantly associated with self-care confidence. Furthermore, we identified 10 individual comorbid conditions that have negative effects on overall prognostic outcomes: DM (HR 1.16, 95% CI 1.11, 1.22, p< 0.001), COPD (HR 1.31, 95% CI 1.23, 1.39, p< 0.001), CKD (HR 1.18, 95% CI 1.14, 1.23, p< 0.001, stroke (HR 1.25, 95% CI 1.17, 1.33, p< 0.001), IHD (HR 1.17, 95% CI 1.11, 1.23, p< 0.001), anemia (HR 1.42, 95% CI 1.14, 1.78, p< 0.01), cancer (HR 1.17, 95% CI 1.04, 1.32, p= 0.01), atrial fibrillation (HR 1.25, 95% CI 1.01, 1.54, p= 0.04), dementia (HR 1.19, 95% CI 1.03, 1.36, p= 0.02) and depression (HR 1.17, 95% CI 1.04, 1.31, p= 0.07). Conclusions: Comorbid conditions have significantly negative pooled effects on HF patient health outcomes, especially in regard to the prognostic health outcomes. Clinicians should carefully identify and manage these conditions when implementing HF interventions to improve prognostic outcomes.

Funding Acknowledgements Type of funding sources: None. Background Although medication adherence is an important self-care activity for hypertensive patients, their medication adherence is not often optimal. When patients with hypertension have comorbidities, they are asked to adhere to medications prescribed for all of their conditions, resulting in a greater burden. Some may decide to take medications for conditions they prioritize, while others may take all medications as prescribed. It is possible that the number of comorbidity affect the pattern of the patients’ medication adherence. Purpose To examine if the number of comorbidity is associated with the medication adherence pattern in patients with hypertension and at least one of the following comorbidity related to poor outcomes in hypertensive patients: diabetes, hyperlipidemia, ischemic heart disease and stroke. Methods A secondary data analysis was conducted using the 2018 Korea Health Panel Survey, including 2218 hypertensive patients with at least one of the following comorbidity: diabetes, hyperlipidemia, ischemic heart disease and stroke. Two types of medication adherence was assessed: primary (i.e., filling prescriptions of medications prescribed by clinicians) and secondary medication adherence (i.e., taking medications as directed). Patients were divided into three groups based on the patterns of primary and secondary medication adherence in each comorbidity (Figure 1). Multinomial logistic regression was used to determine whether the number of comorbidity was associated with the medication adherence pattern after controlling for relevant covariates (i.e. age, gender, marital status, income level, education level, unmet medical needs and presence of primary care providers). Results A total of 2218 patients (mean age 70.1, female 58.7%) had an average of 1.5 comorbidities (SD: 0.7); 10% had three or more comorbidities. About four-fifths of the patients (84.9%) were adherent to medications for all their chronic conditions (i.e., adherent group), 11% partially adhered to their medications (i.e., suboptimal group) and 4.1% did not adhere to any medications (i.e., non-adherent group). Compared with the adherent group, the suboptimal group were more likely to have a greater number of comorbidities after adjusting for covariates (adjusted odds ratio [aOR]=1.46). On the other hand, compared with the adherent group, the non-adherent group were more likely to have a smaller number of comorbidities (aOR=0.54). Conclusion Our study showed that an increased number of comorbidity is a risk factor for inconsistent medication adherence. However, since we also found that patients with a smaller number of chronic conditions were likely to be non-adherent to all medications, hypothesizing that increased number of comorbidity is associated with medication non-adherence may have been simplistic regarding these patients. The unexpected findings of non-adherent group needs to be further explored.

Aims It is recommended that patients and clinicians discuss end-of-life deactivation of their implantable cardioverter defibrillator (ICD) prior to device implantation and throughout the illness trajectory to facilitate shared decision-making. However, such discussions rarely occur, and little is known about patients’ openness to this discussion. The purpose of this study was to explore factors associated with patients’ openness to discussing end-of-life ICD deactivation with clinicians. Methods and results This cross-sectional study recruited 293 patients with an ICD from outpatient clinics in the USA, Australia, and South Korea. Patients were classified into an open or resistant group based on their desire to discuss device deactivation at end of life with clinicians. Multivariable logistic regression was used to explore factors related to patients’ openness to this discussion. About half of the participants (57.7%) were open to discussing such issues with their clinicians. Factors related to patients’ openness to discussing device deactivation at end of life were living with someone, not having severe comorbid conditions (cancer and/or chronic kidney disease), greater ICD knowledge, and more experience discussing end-of-life issues with clinicians (odds ratio: 0.479, 0.382, 1.172, 1.332, respectively). Conclusion Approximately half of the ICD recipients were reluctant to discuss device deactivation at end of life with clinicians. Unmodifiable factors were their living arrangement and severe comorbidity. ICD knowledge and prior experience discussing end-of-life issues were potentially modifiable factors in the future. These factors should be addressed when assessing patients’ readiness for a shared discussion about device deactivation at end of life.

Background Comorbidities are risk factors for poor clinical outcomes in patients with heart failure. However, no consensus has been reached on how to assess comorbidities related to clinical outcomes in patients with heart failure. Objective The aims of this study were to review (1) how comorbidities have been assessed, (2) what chronic conditions have been identified as comorbidities and (3) the rationale for choosing the comorbidity instruments and/or specific comorbidities when exploring clinical outcomes in patients with heart failure. Methods The clinical outcomes of interest were mortality, hospitalization, quality of life, and self-care. Three electronic databases and reference list searches were used in the search. Results In this review, we included 39 articles using 3 different ways to assess comorbidities in the relationship with clinical outcomes: using an instrument (ie, Charlson Comorbidity Index), disease count, and including individual comorbidities. A total of 90 comorbidities were investigated in the 39 articles; however, definitions and labels for the diseases were inconsistent across the studies. More than half of the studies (n = 22) did not provide a rationale for selecting the comorbidity instruments and/or all of the specific comorbidities. Some of the rationale for choosing the instruments and/or specific comorbidities was inappropriate. Conclusions We found several issues related to measuring comorbidities when examining clinical outcomes in patients with heart failure. Researchers need to consider these methodological issues when measuring comorbidities in patients with heart failure. Further efforts are needed to develop guidelines on how to choose proper measures for comorbidities.