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Cardiovascular and metabolic risk
The association of comorbid diabetes mellitus and symptoms of depression with all-cause mortality and cardiac rehospitalization in patients with heart failure
  1. Geri C Reeves1,
  2. Abdullah S Alhurani2,3,
  3. Susan K Frazier2,
  4. John F Watkins2,
  5. Terry A Lennie2,
  6. Debra K Moser2,4
  1. 1Vanderbilt University, Tennessee, USA
  2. 2University of Kentucky, Lexington, USA
  3. 3The University of Jordan, Amman, Jordan
  4. 4The University of Ulster, Newtownabbey, UK
  1. Correspondence to Dr Abdullah S Alhurani; asal223{at}uky.edu

Abstract

Background More than 22% of individuals with diabetes mellitus have concomitant heart failure (HF), and the prevalence of diabetes in those with HF is nearly triple that of individuals without HF. Comorbid depressive symptoms are common in diabetes and HF. Depressive symptoms are an independent predictor of mortality in individuals with diabetes alone, as well as those with HF alone and are a predictor of rehospitalization in those with HF. However, the association of comorbid HF, diabetes and depressive symptoms with all-cause mortality and rehospitalization for cardiac causes has not been determined.

Objective The purpose of this study was to evaluate the association of comorbid HF, diabetes and depression with all-cause mortality and rehospitalization for cardiac cause.

Method Patients provided data at baseline about demographic and clinical variables and depressive symptoms; patients were followed for at least 2 years. Participants were divided into four groups based on the presence and absence of diabetes and depressive symptoms. Cox regression analysis was used to determine whether comorbid diabetes and depressive symptoms independently predicted all-cause mortality and cardiac rehospitalization in these patients with HF.

Results Patients (n=663) were primarily male (69%), white (76%), and aged 61±13 years. All-cause mortality was independently predicted by the presence of concomitant diabetes and depressive symptoms (HR 3.71; 95% CI 1.49 to 9.25; p=0.005), and depressive symptoms alone (HR 2.29; 95% CI 0.94 to 5.40; p=0.05). The presence of comorbid diabetes and depressive symptoms was also an independent predictor of cardiac rehospitalization (HR 2.36; 95% CI 1.27 to 4.39; p=0.007).

Conclusions Comorbid diabetes and depressive symptoms are associated with poorer survival and rehospitalization in patients with HF; effective strategies to regularly evaluate and effectively manage these comorbid conditions are necessary to improve survival and reduce rehospitalization rates.

  • Heart Failure
  • Mortality
  • Type 1
  • Type 2 Diabetes

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

https://doi.org/10.1136/bmjdrc-2014-000077

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    Key messages

    • The co-occurrence of diabetes mellitus, heart failure and depressive symptoms is high in community dwelling patients.

    • Co-morbid diabetes mellitus and depressive symptoms among patients with heart failure is associated with higher risk of death or rehospitalization.

    Introduction

    Nearly 30 million adult Americans, or approximately 12% of the adult population of the USA, has diabetes;1 the cost of care for these individuals totaled $245 billion in 2012.1 ,2 Cardiovascular disease is the primary cause of death for individuals with diabetes,1 and diabetes significantly increases the risk for development of hypertension and dyslipidaemia, two major risk factors for cardiovascular disease. The prevalence of diabetes in individuals with heart failure (HF) ranges from 24% (in those with chronic HF) to 40% (in hospitalized patients with worsening HF).3 In those with diabetes, the risk for acute coronary syndrome is increased by 80%, risk for stroke by 50%, and risk for cardiac death by 70%.2 Thus, comorbid diabetes and HF confer a significant risk of cardiovascular morbidity and mortality.

    The presence of depressive symptoms and major depression are also associated with greater risk of morbidity and mortality in individuals with HF. Suzuki et al4 found that depressive symptoms in individuals with HF more than doubled the likelihood of mortality (OR 2.24, CI 1.17 to 4.28, p=0.01), while Fan et al5 reported that depression nearly doubled the risk for mortality (HR 1.98, CI 1.23 to 3.19). Individuals with diabetes are also at increased risk for depression. Roy et al6 reported that depression prevalence ranged from 15% to 66% in individuals with diabetes. Depression and comorbid diabetes were associated with a nearly 50% increase in mortality.7 Depression has also been associated with worse self-care, poorer quality of life, higher healthcare costs and greater mortality in those with HF and diabetes.7–9

    Although there have been prior studies of these associations in individuals with diabetes alone and HF alone, the association of comorbid HF, diabetes and depressive symptoms in individuals with all-cause mortality and rehospitalization for cardiac cause has not been systematically investigated. Thus, the purpose of this study was to examine whether comorbid depressive symptoms and diabetes were associated with all-cause mortality or rehospitalization for cardiac causes in patients with HF.

    Methods

    Design, sample, and setting

    We performed a secondary analysis of data from the HF Health-Related Quality of Life Collaborative Registry,10 housed at the University of Kentucky College of Nursing. The database was accessed through the Research and Interventions for Cardiovascular Health (RICH) program at the University of Kentucky. This is a longitudinal database that included data from patients with HF across the USA (n=4076). We selected cases (n=663) with complete data for the variables of interest that were a representative sample of those with and without diabetes, and with and without depressive symptoms from the database. We compared demographic (ie, age, gender and ethnicity) and clinical variables (New York Heart Association (NYHA) functional class, body mass index (BMI), smoking history, coronary artery disease (CAD) history, hypertension (HTN) history, left ventricle ejection fraction (LVEF) and use of antidepressant medication) of those selected with the remainder of the data set; there were no significant differences between these groups. Thus, this was a representative sample from the data set.

    The inclusion criteria for the database included: (1) a confirmed diagnosis of HF with impaired or preserved left ventricular systolic function confirmed by a cardiologist; (2) absence of cognitive dysfunction that precluded giving informed consent; (3) no acute myocardial infarction or stroke within the previous 6 months; (4) prescribed stable doses of HF medications; (5) not on the cardiac transplantation waiting list; and (6) absence of life-threatening comorbidities like active cancer, and end-stage renal or liver failure. Data about mortality and rehospitalization were collected for at least 2 years using a standardized protocol that used regular phone contact with the participant and family, medical record review and death record review as appropriate.11 ,12

    Measures

    Demographical and clinical variables

    To characterize the study participants and evaluate potential confounding variables, data that included age, gender, ethnicity, NYHA functional class, smoking history, comorbidity burden (diabetes, CAD history, HTN history), BMI, LVEF and antidepressant use were obtained by patient questionnaire, a brief interview and a thorough medical record review. NYHA functional class was determined by careful patient interview by trained research associates. On the basis of patient report of their ability to perform their usual activities, they were assigned a NYHA classification of: I—ordinary physical activity causes no symptoms of fatigue, dyspnea, angina or palpitations; II—symptoms with ordinary physical activity that slightly limit physical activity; III—symptoms occur with less than ordinary physical activity and markedly limit activity; or IV—symptoms occur at rest.

    Depressive symptoms

    The Patient Health Questionnaire (PHQ-9)13 was used to measure depressive symptoms. It is a 9-item, self-reported measure of depression that reflects the severity of depressive symptoms over the past 2 weeks.14 Patients respond to each item by using a Likert-type scale, in which responses range from 0 (not at all) to 3 (nearly every day). Scores for each item are summed to provide a total score. The total summary score can range from 0 to 27; a higher score reflects more severe depressive symptoms. Good internal consistency, stability, as well as construct and concurrent validity of the PHQ-9 have been supported.12 ,14 The standard cut point of 10 was used to categorize participants who were and were not depressed.12 This cut point had an 88% sensitivity and 88% specificity for the diagnosis of major depression.14

    All-cause mortality

    All-cause mortality was determined by a combination of medical record review, discussion with patient healthcare providers and family, automated hospital records and review of county death records to obtain date and cause of death. At enrollment, patients were asked for contact information for a close friend or next of kin if the patient was unable to be contacted. For patients who were unable to be reached by telephone, automated hospital records were first evaluated to see if the patient had died. If such evidence was found, the friend or next of kin was contacted. If neither the patient nor these contacts were able to be located or if additional information was needed, the county death records were searched.

    Cardiac rehospitalization

    Cardiac rehospitalization was determined by a combination of medical record review, hospital administrative records review, and an interview with the patient and family members. Dates and reasons for all hospitalizations were recorded. When patient recall varied from hospital records, we were able to validate the admission using hospital records. For hospital admissions outside the system, discharge reports released to the patient were reviewed.

    Procedure

    Permission for the conduct of this study was obtained from the University of Kentucky Institutional Review Board. For the original study, eligible patients were approached by a research assistant during a clinic visit. The protocol was explained and informed consent obtained. At that time, an appointment was made for baseline data collection. Demographic and clinical characteristics were collected by patient interview and by review of the medical record. Data were collected at the General Clinical Research Center in a private room. All participating patients completed questionnaires, and were asked to record their future hospitalization history in a log book. We followed up with monthly phone calls to collect hospitalization reports. Finally, we confirmed all dates and causes of hospitalization by review of medical records. For this secondary analysis, we selected a representative sample of cases, compared those selected with those not, examined data distributions and evaluated data for outliers in preparation for analysis.

    Statistical analysis

    Descriptive statistics were used to characterize the participants. Patients were categorized as those with and without depressive symptoms using the standard cut point of 10 for the PHQ-9.12 Patients were divided into four groups: (1) those without either diabetes or depressive symptoms; (2) those without diabetes, but with depressive symptoms; (3) those with diabetes, but without depressive symptoms; and (4) those with both diabetes and depressive symptoms. Sample demographic and clinical characteristics (ie, age, gender, ethnicity, NYHA class, smoking history, CAD history, HTN history, BMI, LVEF and antidepressant use) were compared between these four groups using χ2 analyses or ANOVA based on the level of measurement. Post hoc examination of standardized residuals for χ2 analyses and of Bonferroni comparisons for ANOVA was used to determine location of significant differences. Unadjusted and adjusted hierarchical Cox regression analyses were used to determine whether comorbid diabetes and depressive symptoms predicted mortality or cardiac rehospitalization in these patients with HF. Data were entered into the regression in three blocks to provide more information about the contribution of each variable to the final prediction model. The following covariates were included in the regression analyses, age, gender, ethnicity, NYHA class, smoking history, CAD history, HTN history, BMI, LVEF and antidepressant use. Data were analyzed using SPSS software, V.20.0 (SPSS Inc, Chicago, Illinois, USA). A p value of<0.05 determined statistical significance.

    Results

    Characteristics of the participants

    Participants (n=663) were primarily white (76%), males (69%), and aged 61±13 years (table 1). A majority of participants were in NYHA functional classes III and IV (58%) with an LVEF of 30±14%. The mean PHQ-9 score for all participants was 7.51±6; one-third of participants (33%) were classified as having depressive symptoms based on the cut point. However, more than half of the participants were prescribed antidepressant medication (56%). Forty per cent were diagnosed with diabetes, and nearly three-fourths of these participants reported being a current smoker (70%). Half of the participants had a history of CAD; a majority had a history of HTN (68%).

    View this table:
    Table 1

    Characteristics of participants (n=663)

    When categorized based on the cut point for the depressive symptoms measure and the presence or absence of diabetes, the largest proportion of participants had neither (40%). Twenty per cent of participants reported depressive symptoms, but were without a diabetes diagnosis. Twenty-seven per cent were with diabetes, but did not have depressive symptoms. Fourteen per cent of participants had both diabetes and depressive symptoms. We compared demographical and clinical variables for these four groups (table 2). Although the overall p value for age was significant (p=0.03), post hoc testing with a Bonferroni comparison revealed no significant differences among the groups. BMI in those with both diabetes and depressive symptoms, and those with diabetes only, was significantly higher than in those in the group with neither diabetes nor depressive symptoms (p<0.001); BMI in those who had diabetes only was also significantly higher than in those who had depressive symptoms only (p≤0.001). LVEF in those participants who had diabetes only was significantly greater than in those with only depressive symptoms (p=0.005). There were fewer women than expected in the group with diabetes only, and more women than expected in the group with both diabetes and depressive symptoms (p=0.006). The group without diabetes or depression had a greater proportion of patients classified as NYHA class I/II than predicted, while those in the diabetes alone group and the group with both diabetes and depressive symptoms had fewer participants than expected in NYHA class I/II.

    View this table:
    Table 2

    Demographic and clinical variable comparisons among four groups categorized by diabetes and depressive symptoms (n=663)

    Predictors of all-cause mortality

    During the study follow-up period, 47 (7%) participants died. Diabetes and depression were treated as categorical variables, and the four categories previously defined were entered in a hierarchical Cox regression model to predict all-cause mortality (table 3). Variables were entered into the regression in three blocks to determine predictors of mortality during the follow-up period. In the first block, demographic variables (age, gender, and ethnicity) were entered. In the second block, NYHA functional class, smoking status, CAD and HTN diagnosis, BMI, LVEF and antidepressant prescription were entered. In the final block, the categories (no diabetes or depressive symptoms, depressive symptoms alone, diabetes alone, both diabetes and depressive symptoms) were entered. The final regression model was significant (χ2=82.10, p<0.001). Independent predictors of increased mortality included the presence of both diabetes and depression (p=0.005), the presence of depression alone (p=0.05), white ethnicity (p=0.02), NYHA functional class (p=0.01) and prescription of antidepressant medication (p<0.001). Patients with HF with both diabetes and depression were 3.7 times more likely to die compared to those participants without either condition; patients with HF with depression alone were 2.3 times more likely to die compared to those with neither diabetes nor depression (figure 1). Those with white ethnicity were six times more likely to die compared to African-Americans. Those participants in NYHA functional classes III and IV were 2.7 times more likely to die compared to those in functional classes I and II; those prescribed antidepressant medication had a 7.8 times greater likelihood of mortality compared to those not prescribed these medications. Predictors of reduced mortality in the model included absence of a CAD diagnosis (p=0.001), increased BMI (p=0.02) and greater LVEF (p=0.002). Those participants without a CAD diagnosis were 70% less likely to die during the follow-up period. A 1 unit increase in BMI was associated with a 6% reduction in likelihood of mortality; a 1% increase in LVEF was associated with a 4% reduction in likelihood of mortality.

    View this table:
    Table 3

    Predictors of all-cause mortality (n=663)

    In a sensitivity analysis of these data to confirm these findings, the prior four groups were removed from the analysis and depression was entered as a continuous variable using the total score of PHQ-9; diabetes was entered as a categorical variable. All other variables were entered unchanged. These results demonstrated that diabetes (HR 0.93; 95% CI 0.54 to 1.75; p=0.929) was not a significant predictor of mortality. However, depressive symptoms (HR 1.12; 95% CI 1.06 to 1.18; p<0.001) were a significant predictor of mortality; for every 1 unit increase in the PHQ-9 score, the likelihood of mortality increased by 12%. In further analyses, we entered β-blocker use, ACE blocker use, diuretic use and other comorbidities. These analyses did not alter the results.

    Predictors of cardiac rehospitalization

    During the follow-up period, there were 115 (17%) hospitalizations for cardiac reasons. Diabetes and depression were again treated as categorical variables, and the four categories previously defined were entered in a hierarchical Cox regression in three blocks to determine predictors of cardiac rehospitalization (table 4). In the first block, demographic variables (age, gender and ethnicity) were entered. In the second block, NYHA smoking history, CAD history, HTN history, BMI, LVEF and antidepressant use were entered. The final block contained the four categories of patients (neither diabetes nor depressive symptoms, diabetes only, depressive symptoms only, both diabetes and depressive symptoms). The final regression model was significant (χ2=42.23, p<0.001). Independent predictors of increased risk for cardiac rehospitalization were the presence of both diabetes and depressive symptoms, and prescription of antidepressant medication. Those participants with both diabetes and depressive symptoms were 2.4 times more likely to be rehospitalized compared to those without either diabetes or depression (⇓figure 2). Patients who were prescribed antidepressant medications were 1.7 times more likely to be rehospitalized compared to those without a prescription. Again, sensitivity analysis was carried out with removal of the four categories of patients and depressive symptoms entered as a continuous variable and diabetes as a categorical variable. Diabetes (HR 1.28; 95% CI 0.89 to 1.86; p=0.189) was not a significant predictor of rehospitalization in these patients. However, depressive symptoms (HR 1.06; 95% CI 1.03 to 1.10; p<0.001) were a significant predictor of rehospitalization; for each 1 unit increase in the PHQ-9 score, the likelihood of cardiac rehospitalization increased by 6%. In further analyses, we entered β-blocker use, ACE blocker use, diuretic use and other comorbidities. These analyses did not alter the results.

    View this table:
    Table 4

    Predictors of rehospitalization (n=663)

    Figure 1
    Figure 1

    All-cause mortality according to comorbid symptoms of diabetes and depression.

    Figure 2
    Figure 2

    Cardiac re-hospitalization according to comorbid symptoms of diabetes and depression.

    Discussion

    We found that the combination of comorbid HF, diabetes and depressive symptoms was associated with shorter survival and an increased likelihood of cardiac rehospitalization. A diabetes diagnosis alone did not predict either mortality or cardiac rehospitalization. However, depressive symptoms were independently associated with both mortality and cardiac rehospitalization when the PHQ-9 score was used as a continuous variable. The depressive symptoms alone group was also significantly associated with mortality. The likelihood of mortality and rehospitalization increased by 12% and 6%, respectively, with analysis of depressive symptoms as a continuous variable; the presence of depressive symptoms alone increase the likelihood of mortality by 2.3 times compared to those without depressive symptoms. However, the combination of comorbid diabetes and depressive symptoms was associated with a 3.7 times and 2.4 times greater likelihood of mortality and cardiac rehospitalization, respectively. Thus, the presence of diabetes, HF and depressive symptoms demonstrated an apparent cumulative effect on mortality and cardiac rehospitalization.

    Our findings support prior research evidence15–21 that established the negative impact of comorbid diabetes and depressive symptoms in patients with HF. We extended the understanding of the association between these comorbid conditions and mortality and rehospitalization with identification of a cumulative effect on outcomes when these three conditions are present. Thus, the triad of HF, diabetes and depressive symptoms should be considered prognostic for poorer outcomes.

    Such consideration demands assessment of depression by cardiologists, endocrinologists and other providers who care for patients with HF and diabetes. Such assessments are not common, yet are recommended and can be performed easily in the context of busy clinical practices.22 There are well-defined recommendations for assessing and treating depression in patients with cardiac disease to guide providers.22–25 Some providers, believing that depression is natural in the context of chronic illnesses, do not assess or treat depression.22 ,26 This belief discounts the danger of depression and subjects patients to unnecessary risk.

    As would be expected, in our sample, patients with diabetes had more severe HF, as reflected by NYHA functional class criteria, than those without diabetes. This is similar to previous studies evaluating HF patients with diabetes.21 ,27 Despite this association, the co-occurrence of diabetes and depression remained independently predictive of both cardiac rehospitalization and all-cause mortality. Thus, HF severity alone does not explain the observed associations.

    Comorbid depression and diabetes might be associated with worse outcomes in patients with HF due to shared behavioral pathways. Behaviorally, depressive symptoms likely contribute to poor outcomes by decreasing patient adherence to medical regimens and increasing uptake of risky behaviors.28 Among diabetics, adherence to recommended therapy is poor.29 ,30 Thus, in patients with concomitant diabetes and depression, adherence could be expected to be even worse than in those with each condition alone.31 ,32

    Physiological mechanisms linking depressive symptoms and diabetes with adverse outcomes in HF are likely related to shared pathophysiology among the three conditions. Neurohormonal activation, rhythm disturbances, inflammation and hypercoagulability have all been implicated in the development, progression and outcomes of HF.33 Similarly, each of these pathological states is also seen in depressed patients.33–36 In patients with diabetes, hyperglycemia has been shown to activate the same intracellular signaling pathways as a mechanical stretch or increased ventricular wall stress (seen in HF), which alters protein kinase C and mitogen-activated proteinkinase.37 ,38 Impaired myocardial performance eventually requires activation of the neurohormonal compensatory systems, including the renin–angiotensin system and the sympathetic nervous system, to avoid systemic hypoperfusion. This compensatory response increases oxidative stress, and upregulates the activity of ACE and other components of the renin-aldosterone system, which contributes to the development of cardiomyopathy.39 ,40 Other pathophysiological links between HF, diabetes and depressive symptoms may include increased levels of circulating cytokines such as tumor necrosis factor, impaired baroreflex sensitivity and decreased heart rate variability.37 ,39

    Limitations: The primary limitation of our study was the use of an existing data set; secondary analyses can only include the existing data previously collected. Other variables cannot be evaluated for their importance. For example, we did not include potential physiological mechanisms in the regression analyses. Another potential limitation of our study was the use of self-report measures of symptoms of depression, rather than diagnostic interviews. However, self-report instruments completed by patients with HF have been shown to be reliable and valid measures. A final limitation of this study is our inability to distinguish patients with type I versus type II diabetes.

    Conclusions

    We found that the combination of diabetes and depressive symptoms in patients with HF was associated with a greater likelihood of mortality and cardiac rehospitalization. Diabetes alone was not a predictor of either mortality or cardiac rehospitalization. When analyzed as a continuous variable, depressive symptoms score alone predicted both mortality and rehospitalization. The mechanisms for these associations require further systematic investigation, so that effective interventions can be developed and tested to improve outcomes.

    References

    1. ↵
      National Diabetes Statistics Report. 2014. http://www.cdc.gov/diabetes/pubs/estimates14.htm (accessed 25 Sep 2014).
    2. ↵
      Statistics About Diabetes. 2014. http://www.diabetes.org/diabetes-basics/statistics/ (accessed 25 Sep 2014).
    3. ↵
      1. Dei Cas A,
      2. Khan SS,
      3. Butler J, et al
      . Impact of diabetes on epidemiology, treatment, and outcomes of patients with heart failure. JACC Heart Fail 2015;3:136–45. doi:10.1016/j.jchf.2014.08.004
      OpenUrlCrossRefPubMed
    4. ↵
      1. Suzuki T,
      2. Shiga T,
      3. Kuwahara K, et al
      . Impact of clustered depression and anxiety on mortality and rehospitalization in patients with heart failure. J Cardiol 2014;64:456–62. doi:10.1016/j.jjcc.2014.02.031
      OpenUrlCrossRefPubMed
    5. ↵
      1. Fan H,
      2. Yu W,
      3. Zhang Q, et al
      . Depression after heart failure and risk of cardiovascular and all-cause mortality: a meta-analysis. Prev Med 2014;63:36–42. doi:10.1016/j.ypmed.2014.03.007
      OpenUrlCrossRefPubMed
    6. ↵
      1. Roy T,
      2. Lloyd CE
      . Epidemiology of depression and diabetes: a systematic review. J Affect Disord 2012;142(Suppl):S8–21. doi:10.1016/S0165-0327(12)70004-6
      OpenUrlCrossRefPubMed
    7. ↵
      1. Kessing D,
      2. Pelle AJ,
      3. Kupper N, et al
      . Positive affect, anhedonia, and compliance with self-care in patients with chronic heart failure. J Psychosom Res 2014;77:296–301. doi:10.1016/j.jpsychores.2014.08.007
      OpenUrlCrossRefPubMed
    8. ↵
      1. Heo S,
      2. Lennie TA,
      3. Moser DK, et al
      . Types of social support and their relationships to physical and depressive symptoms and health-related quality of life in patients with heart failure. Heart Lung 2014;43:299–305. doi:10.1016/j.hrtlng.2014.04.015
      OpenUrlCrossRefPubMed
    9. ↵
      1. Smith DH,
      2. Johnson ES,
      3. Blough DK, et al
      . Predicting costs of care in heart failure patients. BMC Health Serv Res 2012;12:434. doi:10.1186/1472-6963-12-434
      OpenUrlCrossRefPubMed
    10. ↵
      1. Moser DK,
      2. Heo S,
      3. Lee KS, et al
      . ‘It could be worse…lot's worse!’ Why health-related quality of life is better in older compared with younger individuals with heart failure. Age Ageing 2013;42:626–32. doi:10.1093/ageing/aft078
      OpenUrlAbstract/FREE Full Text
    11. ↵
      1. Lee CS,
      2. Riegel B,
      3. Driscoll A, et al
      . Gender differences in heart failure self-care: a multinational cross-sectional study. Int J Nurs Stud 2009;46:1485–95. doi:10.1016/j.ijnurstu.2009.04.004
      OpenUrlCrossRefPubMed
    12. ↵
      1. Wu JR,
      2. Moser DK,
      3. Chung ML, et al
      . Objectively measured, but not self-reported, medication adherence independently predicts event-free survival in patients with heart failure. J Card Fail 2008;14:203–10. doi:10.1016/j.cardfail.2007.11.005
      OpenUrlCrossRefPubMedWeb of Science
    13. ↵
      1. Spitzer RL,
      2. Kroenke K,
      3. Williams JB
      . Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. JAMA 1999;282:1737–44. doi:10.1001/jama.282.18.1737
      OpenUrlCrossRefPubMedWeb of Science
    14. ↵
      1. Dekker RL,
      2. Lennie TA,
      3. Albert NM, et al
      . Depressive symptom trajectory predicts 1-year health-related quality of life in patients with heart failure. J Card Fail 2011;17:755–63. doi:10.1016/j.cardfail.2011.04.016
      OpenUrlCrossRefPubMed
    15. ↵
      1. Faris R,
      2. Purcell H,
      3. Henein MY, et al
      . Clinical depression is common and significantly assoicated with reduced survival in patients with non-ischeamic heart failure. Eur J Heart Fail 2002;4:541–51. doi:10.1016/S1388-9842(02)00101-0
      OpenUrlCrossRefPubMedWeb of Science
    16. ↵
      1. Jiang W,
      2. Alexander J,
      3. Christopher E, et al
      . Relationship of depression to increased risk of mortality and rehospitalization in patients with Congestive heart failure. Arch Intern Med 2001;161:1849–56. doi:10.1001/archinte.161.15.1849
      OpenUrlCrossRefPubMedWeb of Science
    17. ↵
      1. Junger J,
      2. Schellberg D,
      3. Muller-Tasch T, et al
      . Depression increasingly predicts mortality in the course of heart failure. Eur J Heart Fail 2005;7:261–7. doi:10.1016/j.ejheart.2004.05.011
      OpenUrlCrossRefPubMedWeb of Science
    18. ↵
      1. Murberg TA,
      2. Furze G
      . Depressive symptoms and mortality in patients with congestive heart failure: a six-year follow-up. Med Sci Monitor 2004;10:CR643–648.
      OpenUrl
    19. ↵
      1. Sullivan MD,
      2. Levy WC,
      3. Crane BA, et al
      . Usefulness of depression to predict time to combined end point of transplant or death for outpatients with advanced heart failure. Am J Caardiol 2004;94:1577–80. doi:10.1016/j.amjcard.2004.08.046
      OpenUrlCrossRef
    20. ↵
      1. Vaccarino V,
      2. Kasl S,
      3. Abramson J, et al
      . Depressive symptoms and risk of functional decline and death in patients with heart failure. J Am Coll Cardiol 2001;38:199–205. doi:10.1016/S0735-1097(01)01334-1
      OpenUrlCrossRefPubMedWeb of Science
    21. ↵
      1. Dries DL,
      2. Sweitzer NK,
      3. Drazner MH, et al
      . Prognostic impact of diabetes mellitus in patients with heart failure according to the etiology of left ventricular systolic dysfunction. J Am Coll Cardiol 2001;38:421–8. doi:10.1016/S0735-1097(01)01408-5
      OpenUrlCrossRefPubMedWeb of Science
    22. ↵
      1. Lichtman JH,
      2. Bigger JT, Jr..,
      3. Blumenthal JA, et al
      . Depression and coronary heart disease: recommendations for screening, referral, and treatment: a science advisory from the American Heart Association Prevention Committee of the Council on Cardiovascular Nursing, Council on Clinical Cardiology, Council on Epidemiology and Prevention, and Interdisciplinary Council on Quality of Care and Outcomes Research: endorsed by the American Psychiatric Association. Circulation 2008;118:1768–75. doi:10.1161/CIRCULATIONAHA.108.190769
      OpenUrlAbstract/FREE Full Text
    23. ↵
      1. Gilbody S,
      2. Richards D,
      3. Brealey S, et al
      . Screening for depression in medical settings with the Patient Health Questionnaire (PHQ): a diagnostic meta-analysis. J Gen Intern Med 2007;22:1596–602. doi:10.1007/s11606-007-0333-y
      OpenUrlCrossRefPubMedWeb of Science
    24. ↵
      1. McManus D,
      2. Pipkin SS,
      3. Whooley MA
      . Screening for depression in patients with coronary heart disease (data from the Heart and Soul Study). Am J Cardiol 2005;96:1076–81. doi:10.1016/j.amjcard.2005.06.037
      OpenUrlCrossRefPubMedWeb of Science
    25. ↵
      1. Davidson KW,
      2. Kupfer DJ,
      3. Bigger JT, et al
      . Assessment and treatment of depression in patients with cardiovascular disease: National Heart, Lung, and Blood Institute working group report. Ann Behav Med 2006;32:121–6. doi:10.1207/s15324796abm3202_9
      OpenUrlCrossRefPubMedWeb of Science
    26. ↵
      1. Feinstein RE,
      2. Blumenfield M,
      3. Orlowski B, et al
      . A national survey of cardiovascular physicians’ beliefs and clinical care practices when diagnosing and treating depression in patients with cardiovascular disease. Cardiol Rev 2006;14:164–9. doi:10.1097/01.crd.0000200977.41695.43
      OpenUrlCrossRefPubMed
    27. ↵
      1. Domanski M,
      2. Krause-Steinrauf H,
      3. Deedwania P, et al
      . The effect of diabetes on outcomes of patients with advanced heart failure in the BEST Trial. J Am Coll Cardiol 2003;42:914–22. doi:10.1016/S0735-1097(03)00856-8
      OpenUrlCrossRefPubMedWeb of Science
    28. ↵
      1. Michalsen GK,
      2. Thimme W
      . Preventable causative factors leading to hospital admission with decompensated heart failure. Heart 1998;80:437–41. doi:10.1136/hrt.80.5.437
      OpenUrlAbstract/FREE Full Text
    29. ↵
      1. Tunceli K,
      2. Zhao C,
      3. Davies MJ, et al
      . Factors associated with adherence to oral antihyperglycemic monotherapy in patients with type 2 diabetes. Patient Prefer Adherence 2015;9:191–7.
      OpenUrlPubMed
    30. ↵
      1. Larkin AT,
      2. Hoffman C,
      3. Stevens A, et al
      . Determinants of adherence to diabetes treatment. J Diabetes 2015. doi:10.1111/1753-0407.12264
    31. ↵
      1. Park H,
      2. Hong Y,
      3. Lee H, et al
      . Individuals with type 2 diabetes and depressive symptoms exhibited lower adherence with self-care. J Clin Epidemiol 2004;57:978–84. doi:10.1016/j.jclinepi.2004.01.015
      OpenUrlCrossRefPubMedWeb of Science
    32. ↵
      1. Ciechanowski PS,
      2. Katon WJ,
      3. Russo JE
      . Depression and diabetes: impact of depessive symptoms on adherence, function, and costs. Arch Intern Med 2000;160:3278–85. doi:10.1001/archinte.160.21.3278
      OpenUrlCrossRefPubMedWeb of Science
    33. ↵
      1. Joynt KE,
      2. Whellan DJ,
      3. O'Connor C
      . Why is depression bad for the failing heart. J Card Fail 2004;10:258–71. doi:10.1016/j.cardfail.2003.09.008
      OpenUrlCrossRefPubMedWeb of Science
    34. ↵
      1. Carney RM,
      2. Blumenthal JA,
      3. Stein PK, et al
      . Depression, heart rate variability, and acute myocardial infarction. Circulation 2001;104:2024–8. doi:10.1161/hc4201.097834
      OpenUrlAbstract/FREE Full Text
    35. ↵
      1. Stein PK,
      2. Carney RM,
      3. Freedland KE, et al
      . Severe depression is associated with markedly reduced heart rate variability in patients with stable coronary heart disease. J Psychosom Res 2000;48:493–500. doi:10.1016/S0022-3999(99)00085-9
      OpenUrlCrossRefPubMedWeb of Science
    36. ↵
      1. Musselman DL,
      2. Evan DL,
      3. Nemeroff CB
      . The relationship of depression to cardiovascular disease: epidemiology, biology, and treatment. Arch Gen Psychiatry 1998;55:580–92. doi:10.1001/archpsyc.55.7.580
      OpenUrlCrossRefPubMedWeb of Science
    37. ↵
      1. Bell D
      . The frequent, forgotten, and often fatal complication of diabetes. Diabetes Care 2003;26:2433–41. doi:10.2337/diacare.26.8.2433
      OpenUrlAbstract/FREE Full Text
    38. ↵
      1. Coutinho M,
      2. Gerstein HC,
      3. Wang Y, et al
      . The relationship between glucose and incident cardiovascular events. Diabetes Care 1999;22:233–40. doi:10.2337/diacare.22.2.233
      OpenUrlAbstract/FREE Full Text
    39. ↵
      1. Giles TD,
      2. Sander GE
      . Diabetes mellitus and heart failure: basic mechanisms, clinical features, and therapeutic considerations. Cardiol Clin 2004;22:553–68. doi:10.1016/j.ccl.2004.07.002
      OpenUrlCrossRefPubMedWeb of Science
    40. ↵
      1. Eichhorn EJ,
      2. Bristow MR
      . Medical therapy can improve the biological properties of the chronically failing heart: a new era in the treatment of heart failure. Circulation 1996;94:2285–96. doi:10.1161/01.CIR.94.9.2285
      OpenUrlAbstract/FREE Full Text
    View Abstract

    Footnotes

    • Contributors GR researched the data and wrote part of the manuscript. ASA researched and analyzed the data and wrote part of the manuscript. SKF, JFW and TAL reviewed/edited the manuscript and contributed to discussion. DKM reviewed/edited the manuscript, contributed to discussion and mentored the entire project.

    • Funding Funding Statement: This work was supported by the National Institutes of Health, National Institute of Nursing Research [NIH, NINR P20 Center funding 5P20NR010679; NIH, NINR 1 R01 NR009280 (Terry Lennie PI) and R01 NR008567 (Debra Moser, PI)]. Since this study was funded by the NIH/NINR, we also would like to inform the publishers of British Medical Journal about an NIH Public access policy as below. “Journal acknowledges that Author retains the right to provide a copy of the final manuscript to the NIH upon acceptance for Journal publication, for public archiving in PubMed Central as soon as possible but no later than 12 months after publication by Journal.”

    • Patient consent Obtained.

    • Ethics approval University of Kentucky IRB.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement Inquiries about use of unpublished data from this project are welcome; send query email to the senior author, Debra K. Moser, dmoser@uky.edu