Literature DB >> 26056566

The association of comorbid diabetes mellitus and symptoms of depression with all-cause mortality and cardiac rehospitalization in patients with heart failure.

Geri C Reeves1, Abdullah S Alhurani2, Susan K Frazier3, John F Watkins3, Terry A Lennie3, Debra K Moser4.   

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.

Entities:  

Keywords:  Heart Failure; Mortality; Type 1; Type 2 Diabetes

Year:  2015        PMID: 26056566      PMCID: PMC4452727          DOI: 10.1136/bmjdrc-2014-000077

Source DB:  PubMed          Journal:  BMJ Open Diabetes Res Care        ISSN: 2052-4897


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%).
Table 1

Characteristics of participants (n=663)

VariableFrequency (%) or mean±SD
Age61±13 years
Gender
 Male454 (68)
Ethnicity
 White502 (76)
 African-American121 (18)
 Other40 (6)
Body mass index30.1±7.4 kg/m2
Left ventricular ejection fraction30±14
NYHA functional class
 I/II276 (42)
 III/IV387 (58)
Type 2 diabetes mellitus267 (40)
Depressive symptoms present221 (33)
Prescribed antidepressants370 (55.8)
Current smoker463 (70)
Coronary artery disease332 (50)
Hypertension451 (68)
PHQ-9 score7.51±6.04

NYHA, New York Heart Association; PHQ-9, Patient Health Questionnaire-9.

Characteristics of participants (n=663) NYHA, New York Heart Association; PHQ-9, Patient Health Questionnaire-9. 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.
Table 2

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

VariableNo diabetes, no depressive symptoms (n=265)Depressive symptoms only (n=131)Diabetes only (n=177)Both diabetes and depressive symptoms (n=90)p Value
Age in years62±1459±1363±1160±110.027
Male gender182 (69%)85 (65%)136 (77%)*51 (57%)*0.006
Ethnicity
 White51 (19%)24 (18%)25 (14%)21 (23%)0.194
 AA192 (73%)101 (77%)145 (82%)64 (71%)
 Other22 (8%)6 (5%)7 (4%)5 (6%)
LVEF30±15%27±14%33±14†29±140.008
BMI28.5±6.829±7.931.8±7‡32.7±7.7‡<0.001
NYHA class III/IV122 (46%)*92 (70%)93 (53%)*80 (89%)*<0.001
CAD107 (41%)60 (46%)107 (61%)55 (63%)<0.001
Hypertension150 (61%)85 (68%)121 (72%)72 (83%)0.001
Prescribed antidepressants129 (49%)103 (79%)70 (40%)68 (76%)<0.001
Current smoker179 (68%)93 (71%)124 (70%)67 (74%)0.647

*Significant difference from predicted proportion p<0.05.

†Significantly different from category diabetes only p<0.05.

‡Significantly different from category neither diabetes nor depressive symptoms p<0.05.

AA, African-American; BMI, body mass index; CAD, coronary artery disease; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association functional class.

Demographic and clinical variable comparisons among four groups categorized by diabetes and depressive symptoms (n=663) *Significant difference from predicted proportion p<0.05. †Significantly different from category diabetes only p<0.05. ‡Significantly different from category neither diabetes nor depressive symptoms p<0.05. AA, African-American; BMI, body mass index; CAD, coronary artery disease; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association functional class.

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.
Table 3

Predictors of all-cause mortality (n=663)

BExp. B95% CIp Value
Block 1. Demographic variables
 Age0.151.020.99 to 1.040.226
 Gender (male)0.701.070.60 to 2.030.830
 White ethnicity (AA)1.3653.920.92 to 16.660.065
 Other ethnicity (AA)1.3323.790.34 to 42.040.278
Block 2. Clinical variables
 Age0.0191.020.99 to 1.040.137
 Gender (male)−0.5010.610.30 to 1.220.162
 White ethnicity (AA)1.6455.181.19 to 22.490.028
 Other ethnicity (AA)1.4030.070.34 to 48.320.266
 NYHA class III/IV (class I/II)0.9912.691.27 to 5.700.01
 Current smoker (non-smoker)0.1081.110.57 to 2.130.755
 CAD (no CAD)−0.8720.420.21 to 0.820.011
 Hypertension (no hypertension)−0.1760.840.46 to 1.540.569
 BMI−0.0510.950.90 to 1.000.05
 LVEF−0.0400.960.94 to 0.990.002
 Antidepressant use (compared to none)2.1458.553.57 to 21.39<0.001
Block 3. Patient categories based on diabetes and depressive symptoms
 Age0.0241.031.00 to 1.050.067
 Gender (male)−0.6830.510.24 to 1.050.067
 White ethnicity (AA)1.7895.981.38 to 25.990.02
 Other ethnicity (AA)1.4904.440.37 to 53.500.241
 NYHA class III/IV (class I/II)0.9742.651.23 to 5.690.013
 Current smoker (non-smoker)−0.0250.980.48 to 1.980.946
 CAD (no CAD)−1.1910.301.47 to 0.630.001
 Hypertension (no hypertension)−0.2860.360.41 to 1.380.358
 BMI−0.0620.940.89 to 0.990.02
 LVEF−0.0390.960.94 to 0.990.002
 Antidepressant use (compared to none)2.0547.83.02 to 20.16<0.001
 Depressive symptoms only (No depressive symptoms and no diabetes)0.8272.291.00 to 5.210.05
 Diabetes only (No depressive symptoms and no diabetes)0.8102.250.94 to 5.400.070
 Both depressive symptoms and diabetes (No depressive symptoms and no diabetes)1.3123.711.49 to 9.250.005

Cox regression—Overall Model χ2=82.10, df=14, p<0.001.

Comparison group in parentheses.

AA, African-American; BMI, body mass index; CAD, coronary artery disease; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association.

Figure 1

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

Predictors of all-cause mortality (n=663) Cox regression—Overall Model χ2=82.10, df=14, p<0.001. Comparison group in parentheses. AA, African-American; BMI, body mass index; CAD, coronary artery disease; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association. 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.
Table 4

Predictors of rehospitalization (n=663)

BExp. B95% CIp Value
Block 1. Demographic variables
 Age−0.0021.00.98 to 1.020.819
 Gender (male)−0.3460.710.45 to 1.110.130
 White ethnicity (AA)−0.3450.710.42 to 1.190.191
 Other ethnicity (AA)0.2461.280.38 to 4.320.693
Block 2. Clinical variables
 Age−0.0081.00.97 to 1.010.391
 Gender (male)−0.3280.720.45 to 1.160.180
 White ethnicity (AA)−0.5740.560.33 to 0.960.034
 Other ethnicity (AA)0.2081.230.36 to 4.270.743
 NYHA class III/IV (class I/II)0.2331.260.84 to 1.900.263
 Current smoker (non-smoker)0.3651.440.90 to 2.300.127
 CAD (no CAD)0.4291.540.99 to 2.390.059
 Hypertension (no hypertension)0.2301.260.81 to 1.960.312
 BMI−0.0200.980.95 to 1.010.180
 LVEF−0.0100.990.98 to 1.010.195
 Antidepressant use (none)0.6271.871.24 to 2.830.003
Block 3. Patient categories based on diabetes and depressive symptoms
 Age−0.0070.990.98 to 1.010.473
 Gender (male)−0.3450.710.44 to 1.150.165
 White ethnicity (AA)−0.5060.600.35 to 1.030.065
 Other ethnicity (AA)−0.3731.450.42 to 5.050.558
 NYHA class III/IV (class I/II)0.1111.120.73 to 1.710.608
 Current smoker (non-smoker)0.4181.520.94 to 2.450.087
 CAD (no CAD)0.3161.370.87 to 2.160.172
 Hypertension (no hypertension)0.1701.190.87 to 1.860.458
 BMI−0.0240.980.95 to 1.010.116
 LVEF−0.0100.990.95 to 1.010.220
 Antidepressant use (none)0.5481.731.13 to 2.660.012
 Depressive symptoms only (No depressive symptoms and no diabetes)0.2122.290.68 to 2.260.490
 Diabetes only (No depressive symptoms and no diabetes)0.1641.180.71 to 1.960.527
 Both depressive symptoms and diabetes (No depressive symptoms and no diabetes)0.8572.361.27 to 4.390.007

Cox regression—Overall Model χ2=42.23, df=14; p<0.001.

Comparison group in parentheses.

AA, African-American; BMI, body mass index; CAD, coronary artery disease; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association.

Figure 2

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

Predictors of rehospitalization (n=663) Cox regression—Overall Model χ2=42.23, df=14; p<0.001. Comparison group in parentheses. AA, African-American; BMI, body mass index; CAD, coronary artery disease; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association. All-cause mortality according to comorbid symptoms of diabetes and depression. 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.
  38 in total

1.  Assessment and treatment of depression in patients with cardiovascular disease: National Heart, Lung, and Blood Institute working group report.

Authors:  Karina W Davidson; David J Kupfer; J Thomas Bigger; Robert M Califf; Robert M Carney; James C Coyne; Susan M Czajkowski; Ellen Frank; Nancy Frasure-Smith; Kenneth E Freedland; Erika S Froelicher; Alexander H Glassman; Wayne J Katon; Peter G Kaufmann; Ronald C Kessler; Helena C Kraemer; K Ranga R Krishnan; François Lespérance; Nina Rieckmann; David S Sheps; Jerry M Suls
Journal:  Ann Behav Med       Date:  2006-10

2.  Impact of clustered depression and anxiety on mortality and rehospitalization in patients with heart failure.

Authors:  Tsuyoshi Suzuki; Tsuyoshi Shiga; Kazue Kuwahara; Sayaka Kobayashi; Shinichi Suzuki; Katsuji Nishimura; Atsushi Suzuki; Yuichiro Minami; Jun Ishigooka; Hiroshi Kasanuki; Nobuhisa Hagiwara
Journal:  J Cardiol       Date:  2014-04-20       Impact factor: 3.159

3.  Determinants of adherence to diabetes treatment.

Authors:  Amy T Larkin; Christina Hoffman; Adrienne Stevens; Andrew Douglas; Zachary Bloomgarden
Journal:  J Diabetes       Date:  2015-03-04       Impact factor: 4.006

Review 4.  Depression after heart failure and risk of cardiovascular and all-cause mortality: a meta-analysis.

Authors:  Hongjie Fan; Weidong Yu; Qiang Zhang; Hui Cao; Jun Li; Junpeng Wang; Yang Shao; Xinhua Hu
Journal:  Prev Med       Date:  2014-03-13       Impact factor: 4.018

5.  A national survey of cardiovascular physicians' beliefs and clinical care practices when diagnosing and treating depression in patients with cardiovascular disease.

Authors:  Robert E Feinstein; Michael Blumenfield; Barbara Orlowski; William H Frishman; Simon Ovanessian
Journal:  Cardiol Rev       Date:  2006 Jul-Aug       Impact factor: 2.644

6.  'It could be worse ... lot's worse!' Why health-related quality of life is better in older compared with younger individuals with heart failure.

Authors:  Debra K Moser; Seongkum Heo; Kyoung Suk Lee; Muna Hammash; Barbara Riegel; Terry A Lennie; Cynthia Arslanian-Engoren; Gia Mudd-Martin; Nancy Albert; John Watkins
Journal:  Age Ageing       Date:  2013-07-05       Impact factor: 10.668

7.  Prognostic impact of diabetes mellitus in patients with heart failure according to the etiology of left ventricular systolic dysfunction.

Authors:  D L Dries; N K Sweitzer; M H Drazner; L W Stevenson; B J Gersh
Journal:  J Am Coll Cardiol       Date:  2001-08       Impact factor: 24.094

8.  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.

Authors:  R L Spitzer; K Kroenke; J B Williams
Journal:  JAMA       Date:  1999-11-10       Impact factor: 56.272

9.  Depression, heart rate variability, and acute myocardial infarction.

Authors:  R M Carney; J A Blumenthal; P K Stein; L Watkins; D Catellier; L F Berkman; S M Czajkowski; C O'Connor; P H Stone; K E Freedland
Journal:  Circulation       Date:  2001-10-23       Impact factor: 29.690

Review 10.  Epidemiology of depression and diabetes: a systematic review.

Authors:  Tapash Roy; Cathy E Lloyd
Journal:  J Affect Disord       Date:  2012-10       Impact factor: 4.839

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  4 in total

1.  Comorbid Chronic Physical Illnesses in Type 1 Diabetes Adolescents: Personal, Caregiver, and Family Functioning.

Authors:  Demivette Gómez-Rivera; Eduardo Cumba-Avilés
Journal:  Salud Conducta Humana       Date:  2021-12-23

2.  Association of depression with evolution of heart failure in patients with type 2 diabetes mellitus.

Authors:  Ying Wang; Hong Yang; Mark Nolan; John Burgess; Kazuaki Negishi; Thomas H Marwick
Journal:  Cardiovasc Diabetol       Date:  2018-01-24       Impact factor: 9.951

3.  Quality of life among patients with cardiac disease: the impact of comorbid depression.

Authors:  Mandreker Bahall; George Legall; Katija Khan
Journal:  Health Qual Life Outcomes       Date:  2020-06-17       Impact factor: 3.186

4.  Depression, diabetes, comorbid depression and diabetes and risk of all-cause and cause-specific mortality: a prospective cohort study.

Authors:  Regina Prigge; Sarah H Wild; Caroline A Jackson
Journal:  Diabetologia       Date:  2022-05-27       Impact factor: 10.460

  4 in total

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