Incorporating reproductive system history data into cardiovascular nursing research to advance women's health.

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.

Use of wearables for monitoring cardiometabolic health: A systematic review.

INTRODUCTION: Cardiometabolic disorders (CMD) such as hyperglycemia, obesity, hypertension, and dyslipidemia are the leading causes of mortality and significant public health concerns worldwide. With the advances in wireless technology, wearables have become popular for health promotion, but its impact on cardiometabolic health is not well understood. PURPOSE: A systematic literature review aimed to describe the features of wearables used for monitoring cardiometabolic health and identify the impact of using wearables on those cardiometabolic health indicators. METHODS: A systematic search of PubMed, CINAHL, Academic Search Complete, and Science and Technology Collection databases was performed using keywords related to CMD risk indicators and wearables. The wearables were limited to sensors for blood pressure (BP), heart rate (HR), electrocardiogram (ECG), glucose, and cholesterol. INCLUDED STUDIES: 1) were published from 2016 to March 2021 in English, 2) focused on wearables external to the body, and 3) examined wearable use by individuals in daily life (not by health care providers). Protocol, technical, and non-empirical studies were excluded. RESULTS: Out of 53 studies, the types of wearables used were smartwatches (45.3%), patches (34.0%), chest straps (22.6%), wristbands (13.2%), and others (9.4%). HR (58.5%), glucose (28.3%), and ECG (26.4%) were the predominant indicators. No studies tracked BP or cholesterol. Additional features of wearables included physical activity, respiration, sleep, diet, and symptom monitoring. Twenty-two studies primarily focused on the use of wearables and reported direct impacts on cardiometabolic indicators; seven studies used wearables as part of a multi-modality approach and presented outcomes affected by a primary intervention but measured through CMD-sensor wearables; and 24 validated the precision and usability of CMD-sensor wearables. CONCLUSION: The impact of wearables on cardiometabolic indicators varied across the studies, indicating the need for further research. However, this body of literature highlights the potential of wearables to promote cardiometabolic health.

Are Physical and Depressive Symptoms Different Between Women and Men With Heart Failure?: An Exploration Using Two Analytic Techniques.

BACKGROUND: Adults with heart failure (HF) experience a constellation of symptoms; however, understanding of gender differences in HF symptoms remain elusive. The aim of this study was to determine whether there are gender differences in physical and depressive symptoms and symptom patterns in HF using 2 different analytic techniques. METHODS: We performed a secondary analysis of combined data from 6 studies of adults with HF. Physical symptoms were measured with the HF Somatic Perception Scale, and depressive symptoms were measured with the Patient Health Questionnaire-9. First, we performed propensity matching with the nearest neighbor to examine the average treatment effect for HF Somatic Perception Scale and Patient Health Questionnaire-9 in the matched sample of women and men. Next, we used the entire data set in a latent class mixture model to determine patterns of symptoms. Finally, we calculated predictors of class membership with multinomial logistic regression. RESULTS: The sample (n = 524, 86.5% systolic HF) was 37% women with a mean age of 58.3 ± 13.9 years and mean number of years with HF of 6.9 ± 6.9. Three hundred sixty-six participants were matched on propensity scores; there were no significant gender differences in symptom scores between matched women (n = 183) and men (n = 183). Among all 524 participants, 4 distinct latent classes of symptom patterns indicate that many patients with HF are fatigued, some have more depressive symptoms, and others have significantly more edema or cough. Gender did not predict membership to any symptom pattern. CONCLUSIONS: There were significant gender differences in sociodemographics, health behaviors, and clinical characteristics, but not HF symptoms or symptom patterns, using either analytic technique.

Sex differences in the impact of physical frailty on outcomes in heart failure.

BACKGROUND: Physical frailty is strongly related to adverse outcomes in heart failure (HF), and women are more likely to be physically frail than men; however, it is unknown if this sex difference affects outcomes. OBJECTIVES: To determine if there are sex differences in the associations between physical frailty and health-related quality of life (HRQOL) and clinical outcomes in HF. METHODS: We conducted a prospective study of adults with HF. Physical frailty was assessed using the Frailty Phenotype Criteria. HRQOL was assessed using the Minnesota Living with HF Questionnaire. One-year clinical events (all-cause death or cardiovascular hospitalization or emergency department visit) were ascertained. We used generalized linear modeling to quantify associations between physical frailty and HRQOL, and Cox proportional hazards modeling to quantify associations between physical frailty and clinical events, adjusting for Seattle HF Model scores. RESULTS: The sample (n = 115) was 63.5 ± 15.7 years old and 49% women. Physical frailty was associated with significantly worse total HRQOL among women (p = 0.005) but not men (p = 0.141). Physical frailty was associated with worse physical HRQOL among both women (p < 0.001) and men (p = 0.043). There was a 46% higher clinical event risk for every one-point increase in physical frailty score among men (p = 0.047) but not women (p = 0.361). CONCLUSIONS: Physical frailty is associated with worse overall HRQOL among women and higher clinical event risk among men, indicating a need to better understand contributors to sex-specific health differences associated with physical frailty in HF.

Candidate biomarkers of physical frailty in heart failure: an exploratory cross-sectional study.

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 [ß ± standard error (SE) -0.28 ± 0.14, P = 0.047], IGF-1 (ß ± SE -0.21 ± 0.10, P = 0.032), and myostatin (ß ± 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.

Frequency and Predictors of Falls Among Adults With Heart Failure: A Prospective Study.

OBJECTIVE: Adults with heart failure (HF) may be at high risk for falling due to age, comorbidities and frailty; however, few studies have examined falls in HF. The purpose of this study was to quantify the frequency and predictors of falls over 1 year among adults with HF. METHODS: We conducted a prospective study of adults with New York Heart Association (NYHA) functional class I-IV HF. After baseline assessment of physical frailty and clinical characteristics, participants self-reported falls every 3 months during 1 year. Comparative statistics were used to identify baseline differences between those who fell vs those who did not. A stepwise negative binomial regression model was used to identify predictors of fall rate over 1 year. RESULTS: The sample (n = 111) was 63.4 ± 15.7 years old, 48% were women, 28% had HF with preserved ejection fraction, and 41% were frail. Over 1 year, 43 (39%) of participants reported at least 1 fall and 28 (25%) of participants reported 2+ falls. Among those who fell, 29 (67%) reported injurious falls. Those who fell had significantly higher body mass indexes and were more likely to have NYHA class III/IV, type 2 diabetes and HF with preserved ejection fraction and to meet slowness and physical exhaustion criteria than those who did not fall. The fall rate was elevated among those with type 2 diabetes and those meeting the slowness and physical exhaustion criteria for physical frailty. CONCLUSIONS: Nearly 40% of adults with HF experienced a fall within 1 year. Screening for comorbidities, slowness and exhaustion may help to identify those at risk for a fall.

Using a Virtual Platform for Conducting Grandfamily Research.

BACKGROUND: Because of the COVID-19 pandemic, our research team quickly pivoted from planned face-to-face interaction with participants to virtual interactions. During this transition, we discovered invaluable new practices for conducting research remotely, including collecting physiological data. OBJECTIVE: Our objective was to describe the methodological challenges we encountered when conducting this research virtually with grandparent-grandchild dyads and describe the strategies we developed to overcome those challenges. Of primary focus were procedures for finger-stick blood sample collection. Of secondary focus were procedures for conducting virtual-based research with older adults and across multiple generations. METHODS: During an observational study utilizing a virtual platform with 11 grandparent-grandchild dyads (mean age: 64.2 ± 5.0 years for grandparents and 9.3 ± 1.9 years for grandchildren), we documented lessons learned (based on the discussion within our team and feedback we have received from participants) that could be applicable for other, similar research endeavors. RESULTS: We found several challenges in collecting blood samples, including staff were unfamiliar with providing online instruction and participants needed to develop familiarity with the blood sample collection process (without having in-person assistance), and we had to develop methods for delivering blood sample collection kits to participants safely. We also found that it took longer than expected to run procedures-a challenge that might be encountered when conducting any type of dyadic research utilizing a virtual platform-particularly involving older adults and across multiple generations. In addition, it was challenging to keep child participants engaged in the virtual interactions. We document how we employed targeted strategies to overcome those obstacles. Recommendations for strategies from our team include to provide comprehensive and clear instruction/materials on blood sampling procedure, offer generous support throughout the blood collection process, be prepared to divide study visits into more than one session as needed, proactively anticipate potential roadblocks, and carefully consider the participants' developmental stages and attention span. DISCUSSION: The insights we gained will help inform future research with grandparent-grandchild dyads in remote or rural populations utilizing virtual platforms.

Background and Design of the Biological and Physiological Mechanisms of Symptom Clusters in Heart Failure (BIOMES-HF) Study.

BACKGROUND: Symptoms, which often cluster together, are a significant problem in heart failure (HF). There is considerable heterogeneity in symptom burden, particularly in the vulnerable transition period after a hospitalization for HF, and the biological underpinnings of symptoms during transitions are unclear. The purpose of this article is to describe the background and design of a study that addresses these knowledge gaps, entitled Biological and Physiological Mechanisms of Symptom Clusters in Heart Failure (BIOMES-HF). METHODS AND RESULTS: BIOMES-HF is a prospective gender- and age-balanced longitudinal study of 240 adults during the 6-month transition period after a HF hospitalization. The aims are to (1) identify clusters of change in physical symptoms, (2) quantify longitudinal associations between biomarkers and physical symptoms, and (3) quantify longitudinal associations between physical frailty and physical symptoms among adults with HF. We will measure multiple symptoms, biomarkers, and physical frailty at discharge and then at 1 week and 1, 3, and 6 months after hospitalization. We will use growth mixture modeling and longitudinal mediation modeling to examine changes in symptoms, biomarkers, and physical frailty after HF hospitalization and associations therein. CONCLUSIONS: This innovative study will advance HF symptom science by using a multibiomarker panel and the physical frailty phenotype to capture the multifaceted nature of HF. Using advanced quantitative modeling, we will characterize heterogeneity and identify potential mechanisms of symptoms in HF. As a result, this research will pinpoint amenable targets for intervention to provide better, individualized treatment to improve symptom burden in HF. LAY SUMMARY: Adults with heart failure may have significant symptom burden. This study is designed to shed light on our understanding of the role of biological and physiological mechanisms in explaining heart failure symptoms, particularly groups of co-occurring symptoms, over time. We explore how symptoms, biomarkers, and physical frailty change after a heart failure hospitalization. The knowledge generated from this study will be used to guide the management and self-care for adults with heart failure.

Characterizing Sex Differences in Physical Frailty Phenotypes in Heart Failure.

BACKGROUND: Although women with heart failure (HF) are potentially more likely to be physically frail compared with men with HF, the underlying contributors to this sex difference are poorly understood. The purpose of this study was to characterize sex differences in physical frailty phenotypes in HF. METHODS: We prospectively enrolled adults with class I-IV HF. Physical frailty was measured with the frailty phenotype criteria. Symptoms of dyspnea, sleep-related impairment, pain interference, depression, and anxiety were assessed. Body composition was measured using dual-energy x-ray absorptiometry. Simple comparative statistics and stepwise regression modeling were used. RESULTS: The average age of the sample (n=115) was 63.6±15.7 years, 49% were women, and 73% had nonischemic cause. Forty-three percent of the sample was physically frail. Women had a 4.6 times greater odds of being physically frail compared with men, adjusting for covariates (odds ratio=4.63 [95% CI, 1.81-11.84], P=0.001). Both physically frail men and women were characterized by more type 2 diabetes, higher comorbidity burden, and worse dyspnea symptoms. Physically frail women had significantly worse symptoms compared with non-physically frail women but no difference in body composition characteristics. Physically frail men had significantly lower appendicular muscle mass, higher percent fat, lower hemoglobin, and more depressive symptoms compared with non-physically frail men. CONCLUSIONS: Women are significantly more likely to be physically frail compared with men in HF. Physical frailty in both women and men is characterized by comorbidities and worse symptoms; physical frailty in men is characterized by worse physiological characteristics.