As the U.S. population is disproportionately aging, a specific research area that has garnered recent attention is the link between major depressive disorder (MDD) and heart failure (HF) since both are highly prevalent conditions and also highly comorbid. Prevalence of MDD among HF patients ranges from 11% to 25% in outpatients and 35% to 70% in hospitalized patients. Further, co-morbid depressive disorder is a predictor of mortality, re-hospitalization and worsening HF. Despite this, appropriate management of co-morbid depression in HF patients remains under-appreciated in routine clinical care. While several studies have examined the prevalence of depression in HF, and a few have also investigated the incidence of depression, the """"""""temporal relationship"""""""" between incident MDD and incident HF is undetermined and under-studied. Understanding this temporal relationship will provide insight as to whether incident MDD is a risk factor for incident HF, a consequence of incident HF, and/or a comorbid factor that exacerbates HF, or vice versa. To address this critical gap, in this proposed study, we will leverage robust and longitudinal electronic health record (EHR) systems at Mayo Clinic, along with our extensive experience and decades of research in EHR data mining, and epidemiological studies in MDD and HF, to understand (1) the bidirectional risk association between MDD and HF, (2) the role of co-existing conditions in MDD and HF, and (3) patient outcomes and healthcare utilization for MDD and HF.

Public Health Relevance

Major Depressive Disorder (MDD) and Heart Failure (HF) are very common and often co-exist. While numerous mechanistic pathways have been implicated citing an intricate association between these chronic conditions, the causal relationship between MDD and HF remains understudied and inconclusive. To address this critical gap, in this community-based cohort study we will investigate the temporal relationship between MDD and HF to understand whether incident MDD is a risk factor for incident HF, a consequence of incident HF, and/or a comorbid factor that exacerbates HF, or vice versa.

Agency
National Institute of Health (NIH)
Institute
Agency for Healthcare Research and Quality (AHRQ)
Type
Research Project (R01)
Project #
1R01HS023077-01
Application #
8724760
Study Section
Special Emphasis Panel (ZHS1)
Program Officer
Basu, Jayasree
Project Start
2014-06-01
Project End
2015-11-30
Budget Start
2014-06-01
Budget End
2015-11-30
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Mayo Clinic, Rochester
Department
Type
DUNS #
City
Rochester
State
MN
Country
United States
Zip Code
55905
Ryu, Euijung; Chamberlain, Alanna M; Pendegraft, Richard S et al. (2016) Quantifying the impact of chronic conditions on a diagnosis of major depressive disorder in adults: a cohort study using linked electronic medical records. BMC Psychiatry 16:114
Panahiazar, Maryam; Taslimitehrani, Vahid; Pereira, Naveen et al. (2015) Using EHRs and Machine Learning for Heart Failure Survival Analysis. Stud Health Technol Inform 216:40-4
Panahiazar, Maryam; Taslimitehrani, Vahid; Pereira, Naveen L et al. (2015) Using EHRs for Heart Failure Therapy Recommendation Using Multidimensional Patient Similarity Analytics. Stud Health Technol Inform 210:369-73