Andrew J. Dimond, David S. Krantz, Andrew J. Waters, Romano Endrighi, Stephen S. Gottlieb

Transcription

1 Andrew J. Dimond, David S. Krantz, Andrew J. Waters, Romano Endrighi, Stephen S. Gottlieb Uniformed Services University, Bethesda MD and University of Maryland Hospital, Baltimore MD

2 Heart Failure Serious chronic condition Characterized by fatigue, breathlessness, and fluid build-up Exacerbations and remissions Repeated hospitalizations, up to 35% within 30 days Fluctuations in symptoms Medical/behavioral predictors of worsening include: Poor medication compliance Hypertensive episodes Coronary heart disease

3 HF Measurement Measures of HF worsening: Self-report of HF symptoms (e.g., shortness of breath, fatigue) Biomarkers (e.g., inflammatory markers, BNP) Functional status (e.g., activities of daily living, Six- Minute Walk Test) Hospitalizations for HF-related clinical events

4 Anger State anger: an acute emotional state, varying in intensity Trait anger: a stable disposition to experience state anger Trait anger is associated with the development of CHD and worsened CHD prognosis (Chida & Steptoe, 2009) Acute anger episodes important as triggering (i.e., precipitating) factor Incidence of ACS or MI increased between fold within 2 hours after an anger outburst (Mostofsky et al., 2014) Few studies of short-term anger as a possible precipitating factor in HF

5 Acute and Chronic Stress Recent findings in our lab demonstrated relationships between chronic and acutely elevated perceived stress and HF worsening When stress was assessed repeatedly over 3 month period (Endrighi et al., 2015) Adverse events: predicted by chronically elevated stress Functional status: predicted by bi-weekly fluctuations in stress Symptoms: predicted by both chronic stress and fluctuations in stress

6 Study Purpose 1. Determine effects of acute anger on short-term (2 week) changes in HF severity using 3 measures of HF outcomes 2. Compare effects of state anger to those of perceived stress

7 Methods Project BETRHEART 150 study participants recruited from: Heart Failure Clinic at the University of Maryland Hospital in Baltimore, MD Eligibility: Current diagnosis of heart failure and > 21 years of age Baseline interview included measures for: Demographics Medical status Psychosocial variables (e.g., chronic and acute anger, perceived stress, depression, social support, etc.)

8 Methods Measurement of stress Perceived Stress Scale (PSS; Cohen et al., 1983) Measurement of state anger State Trait Anger Expression Inventory-II (STAXI-II; Spielberger et al., 1985) Measurement of perceived symptoms Kansas City Cardiomyopathy Questionnaire (KCCQ) Summary Score: Measures physical symptoms, social interference, selfefficacy, and quality of life (Green et al., 2000) Measurement of functional status Six-Minute Walk Test (6-MWT) Adverse Events: Hospitalizations for cardiac causes (including HF) or participant death

9 Clinic Assessment: Baseline (PSS, Anger, KCCQ, 6MWT) n = 144 *At each interview, patients scoring in the top & bottom 30% of PSS were scheduled for up to 5 clinic visits 2 Week (PSS, Anger, Adverse Events) n = Week (PSS, Anger, Adverse Events) n = Week (PSS, Anger, Adverse Events) n = Week (PSS, Anger, Adverse Events) n = Week (PSS, Anger, Adverse Events) n = 126 *Clinic (KCCQ & 6MWT) n = 81 Clinic (KCCQ & 6MWT) n = 79 Clinic (KCCQ & 6MWT) n = 73 Clinic (KCCQ & 6MWT) n = 72 Clinic (KCCQ & 6MWT) n = 83 Clinic Assessment: 3 Month (PSS, Anger, Adverse Events, KCCQ, 6MWT) n = Month (Adverse Events) n = 96

10 Data Analytic Plan Linear mixed models (SAS) prospective associations modelled as: Mean IV (aggregated over all assessments); Do patients with higher Mean IV scores have worse outcome? (a between-subject level analysis) Deviation IV (difference between IV score at each assessment and Mean IV ); At assessments in which patients have a higher IV score compared to their average do they have a worse subsequent outcome? (a within-subject level analysis)

11 Results Patient characteristics Variable Mean ± SD or % Age (yrs) 57.51± Male sex (%) 77.0 BMI (kg/m 2 ) ± 7.50 NYHA class II (%) III (%) IV (%) Hypertension yes (%) no (%) Income $ <15k (%) 15-30k (%) 30-70k (%) >70k (%) Race Caucasian (%) African American (%) American Indian (%)

12 State Anger and Stress Associations Outcome Variable Assessment Level State Anger Stress Adverse Events Between-subjects Within-subjects KCCQ (Symptoms) Between-subjects Within-subjects MWT (Functional status) Between-subjects Within-subjects p <

13 State Anger and Stress Associations Outcome Variable Assessment Level State Anger Stress Adverse Events Between-subjects Within-subjects KCCQ (Symptoms) Between-subjects Within-subjects MWT (Functional status) Between-subjects Within-subjects p <

14 State Anger and Stress Associations Outcome Variable Assessment Level State Anger Stress Adverse Events Between-subjects Within-subjects KCCQ (Symptoms) Between-subjects Within-subjects MWT (Functional status) Between-subjects Within-subjects p < Endrighi et al., 2015

15 Covariate Associations Outcome Variable Predictor (Mean IV) Between- Subjects Within- Subjects Adverse Events State anger controlling for stress Stress controlling for state anger KCCQ (Symptoms) State anger controlling for stress Stress controlling for state anger MWT (Functional status) State anger controlling for stress Stress controlling for state anger

16 Covariate Associations Outcome Variable Predictor (Mean IV) Between- Subjects Within- Subjects Adverse Events State anger controlling for stress Stress controlling for state anger KCCQ (Symptoms) State anger controlling for stress Stress controlling for state anger MWT (Functional status) State anger controlling for stress Stress controlling for state anger

17 Covariate Associations Outcome Variable Predictor (Mean IV) Between- Subjects Within- Subjects Adverse Events State anger controlling for stress Stress controlling for state anger KCCQ (Symptoms) State anger controlling for stress Stress controlling for state anger MWT (Functional status) State anger controlling for stress Stress controlling for state anger

18 Results Summary Greater mean state anger associated with worse symptoms and sharp increases in state anger associated with reduced functional status When controlling for stress, state anger was not associated with any HF measures When controlling for state anger, chronic stress was related to adverse events, acute stress was related to functional status, and both were related to symptoms

19 Study Limitations Generalizability to other populations; AA and low SES Only top and bottom thirds on stress performed 6- MWT and completed KCCQ on bi-weekly basis Two week assessment period may be too long to measure effects of acute anger

20 Conclusion State anger is associated with short-term fluctuations in functional status and mean worsened symptom status in HF patients Perceived stress is more strongly associated with these endpoints and adverse events than state anger After controlling for stress, state anger was not associated with short-term HF outcomes Effects of state anger may operate through its associations with perceived stress Mechanisms for these associations may involve physiological changes associated with perceived stress and state anger, and/or effects of stress and emotion on psychological (e.g., depression) or behavioral factors (e.g., compliance with medications), etc.

21 Questions