Kevin P.

ABSTRACT

Background:
Major Depressive Disorder (MDD) and Chronic Heart Failure (CHF) have in common heightening states of inflammation, manifested by elevated inflammatory biomarkers such as C-reactive protein (CRP). This study compared inflammatory biomarker profiles in CHF patients with MDD to those without MDD.

Methods:
The study recruited patients who were admitted to inpatient care for acute heart failure exacerbations, after psychiatric diagnostic interview. Patients… Show more

ABSTRACT

Background:
Major Depressive Disorder (MDD) and Chronic Heart Failure (CHF) have in common heightening states of inflammation, manifested by elevated inflammatory biomarkers such as C-reactive protein (CRP). This study compared inflammatory biomarker profiles in CHF patients with MDD to those without MDD.

Methods:
The study recruited patients who were admitted to inpatient care for acute heart failure exacerbations, after psychiatric diagnostic interview. Patients with Beck Depression Inventory (BDI) scores < 10 and with no prior history of depression served as controls (n = 25). MDD severity was defined as: Mild (BDI 10-15; n = 48); Moderate (BDI 16-23; n = 51); and Severe (BDI ≥ 24; n = 33). A Bio-Plex assay measured 18 inflammatory biomarkers. Ordinal logistic models were used to examine the association of MDD severity and biomarker levels.

Result:
Controlling for age, sex, statin use, BMI, LVEF, tobacco use, and NHYA class the MDD overall group variable was significantly associated with interleukin (IL)-1β (p = .011), IL-2 (p = .019), IL-4 (p = .02), IL-6 (p = .026), IL-17 (p < .001), Interferon (INF)-γ (p = .010), monocyte chemoattractant protein (MCP-1) (p = .002), macrophage inflammatory protein (MIP-1β) (p = .003) and tumor necrosis factor (TNF)-α (p = .004). MDD severity subgroups had a greater probability of elevated IL-6, IL-8, IFN-γ, MCP-1, MIP-1β, and TNF-α compared to control group. Non-depressed group had greater probability of elevated IL-17 (p < 0.001) and IL-1β (p < 0.01).

Conclusions:
MDD in CHF patients was associated with higher inflammation. Whether effective depression treatment will normalize the altered inflammatory biomarkers requires further study.

Key Words: Heart Failure, Depression, Inflammatory Biomarkers
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Abstract
Objectives: The aim of this study was to examine the associations between depressive symptoms and mental stress–induced myocardial ischemia (MSIMI) in patients with coronary heart disease (CHD).

Methods: Adult patients with documented CHD were recruited for baseline mental stress and exercise stress screening testing as a part of the enrollment process of the Responses of Myocardial Ischemia to Escitalopram Treatment trial. Patients were administered the Beck Depression… Show more

Abstract
Objectives: The aim of this study was to examine the associations between depressive symptoms and mental stress–induced myocardial ischemia (MSIMI) in patients with coronary heart disease (CHD).

Methods: Adult patients with documented CHD were recruited for baseline mental stress and exercise stress screening testing as a part of the enrollment process of the Responses of Myocardial Ischemia to Escitalopram Treatment trial. Patients were administered the Beck Depression Inventory II and the Center for Epidemiologic Studies Depression Scale. After a 24–48-hour β-blocker withdrawal, participants completed three mental stress tests followed by a treadmill exercise test. Ischemia was defined as a) any development or worsening of any wall motion abnormality and b) reduction of left ventricular ejection fraction at least 8% by transthoracic echocardiography and/or ischemic ST-segment change by electrocardiography during stress testing. MSIMI was considered present when ischemia occurred in at least one mental test. Data were analyzed using logistic regression adjusting for age, sex, and resting left ventricular ejection fraction.

Results: One hundred twenty-five (44.2%) of 283 patients were found to have MSIMI, and 93 (32.9%) had ESIMI. Unadjusted analysis showed that Beck Depression Inventory II scores were positively associated with the probability of MSIMI (odds ratio = 0.1.30: 95% confidence interval = 1.06–1.60, p = .013) and number of MSIMI-positive tasks (all p < .005). These associations were still significant after adjustment for covariates (p values <.05).

Conclusions: In patients with CHD, depressive symptoms were associated with a higher probability of MSIMI. These observations may enhance our understanding of the mechanisms contributing to the association of depressive symptoms to future cardiovascular events.

Trial Registration: Clinicaltrials.gov identifier: NCT00574847. Show less

Abstract

Objective To examine the influence of childhood economic strains on substance use in young adulthood and to assess the mediating roles of self-control as well as positive parenting during adolescence in a nationally representative longitudinal cohort. Methods The study included data from participants (n = 1,285) in the Panel Study of Income Dynamics, Child Development Supplement, and Transition to Adult. Structural equation modeling was used to evaluate the associations among… Show more

Abstract

Objective To examine the influence of childhood economic strains on substance use in young adulthood and to assess the mediating roles of self-control as well as positive parenting during adolescence in a nationally representative longitudinal cohort. Methods The study included data from participants (n = 1,285) in the Panel Study of Income Dynamics, Child Development Supplement, and Transition to Adult. Structural equation modeling was used to evaluate the associations among risk factors during childhood and adolescence that predicted substance use in early adulthood. Results Conditions of economic strains, especially poverty, during childhood were associated with an increased likelihood of regular smoking in adulthood, which was partially mediated by poorer self-control during adolescence. Conclusions Self-control is negatively affected by economic strains and serves as a mediator between poverty and risk of regular smoking. Additional research is needed to better understand how economic strains effect the development of self-control. Show less

Not every big data problem requires Hadoop or Spark. This talk/tutorial will primarily focus on the dask library but introduce several options for working with datasets that exceed a machine's available memory including Turi's (former Dato) SFrame, h20.ai's Python library, and portions of the ever popular scikit-learn framework.