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BackgroundThe relationship between physical and affective symptom clusters in heart failure (HF) is unclear.ObjectivesTo identify associations between physical and affective symptom clusters in HF and to quantify outcomes and determinants of symptom subgroups.MethodsThis was a secondary analysis of data from two cohort studies among adults with HF. Physical and affective symptom clusters were compared using cross-classification modeling. Cox proportional hazards modeling and multinomial logistic regression were used to identify outcomes and determinants of symptom subgroups, respectively.ResultsIn this young, mostly male sample (n = 274), physical and affective symptom clusters were cross-classified in a model with acceptable fit. Three symptom subgroups were identified: congruent-mild (69.3%), incongruent (13.9%), and congruent-severe (16.8%). Compared to the congruent-mild symptom group, the incongruent symptom group had significantly worse 180-day event-free survival.ConclusionCongruence between physical and affective symptom clusters should be considered when identifying patients at higher risk for poor outcomes.

BACKGROUND: Although current guidelines emphasize the importance of social support to the success of left ventricular assist device (LVAD) therapy, few studies examine the influence of the caregiver on patient outcomes or quantify the impact of LVAD caregiving on caregiver outcomes. The purpose of this analysis was to identify patient and caregiver determinants of patient quality of life (QOL) and caregiver strain in response to LVAD therapy. METHODS AND RESULTS: Data on patients receiving LVAD therapy and their caregivers (n=50 dyads) were prospectively collected pre-implantation and 1, 3, and 6 months post-implantation. Growth curve modeling was used to describe change in patient QOL (Kansas City Cardiomyopathy Questionnaire) and caregiver strain (Multidimensional Caregiver Strain Index). Patient QOL improved most in the first month (β=23.22±3.76, P

The lack of sex-specific variables, such as reproductive system history (RSH), in cardiovascular research studies is a missed opportunity to address the cardiovascular disease (CVD) burden, especially among women who face sex-specific risks of developing CVD. Collecting RSH data from women enrolled in research studies is an important step towards improving women's cardiovascular health. In this paper, we describe two approaches to collecting RSH in CVD research: extracting RSH from the medical record and participant self-report of RSH. We provide specific examples from our own research and address common data management and statistical analysis problems when dealing with RSH data in research. [ABSTRACT FROM AUTHOR]

Aims: Physical frailty is highly prevalent and predictive of worse outcomes in heart failure (HF). Candidate biomarker analysis may help in understanding the mechanisms underlying physical frailty in HF. We aimed to identify candidate biomarkers associated with physical frailty in HF using a multimarker strategy of distinct pathophysiological processes. Methods and results: We collected data and plasma samples from 113 adults with New York Heart Association Functional Class I–IV HF. Physical frailty was measured with the Frailty Phenotype Criteria. Plasma biomarkers included: N-terminal pro-B-type natriuretic peptide, norepinephrine, dihydroxyphenylglycol, soluble tumour necrosis factor alpha receptor-1, adiponectin, insulin, glucose, insulin-like growth factor-1 (IGF-1), and myostatin. Comparative statistics and multivariate linear regression were used to test group differences and associations. The average age was 63.5 ± 15.7 years, half were women (48%), and most had a non-ischaemic aetiology of HF (73%). Physical frailty was identified in 42% and associated with female sex, higher body mass index and percent body fat, more comorbidities, and HF with preserved ejection fraction. Adjusting for Seattle HF Model projected survival score, comorbidities, body composition, and sex, physical frailty was associated with significantly lower plasma adiponectin [β ± standard error (SE) −0.28 ± 0.14, P = 0.047], IGF-1 (β ± SE −0.21 ± 0.10, P = 0.032), and myostatin (β ± SE −0.22 ± 0.09, P = 0.011). In sex-stratified analyses, IGF-1 and myostatin were significantly associated with physical frailty in men but not women. Conclusion: We identified biomarkers involved in adipose tissue and skeletal muscle development, maintenance, and function that were associated with physical frailty in HF. Graphical Abstract Graphical Abstract Abbreviations: HF, heart failure [ABSTRACT FROM AUTHOR]