Exploring Cytokine Networks in Resistant Hypertension

Background Controlling high blood pressure (BP) continues to be a major concern because the associated complications can lead to an increased risk of heart, brain, and kidney disease. Those with hypertension, despite lifestyle and diet modifications and pharmacotherapy, defined as resistant hypertension, are at increased risk for further risk for morbidity and mortality. Understanding inflammation in this population may provide novel avenues for treatment. Objectives This study aimed to examine a broad range of cytokines in adults with cardiovascular disease and identify specific cytokines associated with resistant hypertension. Methods A secondary data analysis was conducted. The parent study included 156 adults with a history of myocardial infarction within the past 3–7 years and with a multiplex plasma analysis yielding a cytokine panel. A network analysis with lasso penalization for sparsity was performed to explore associations between cytokines and BP. Associated network centrality measures by cytokine were produced, and a community graph was extracted. A sensitivity analysis BP was also performed. Results Cytokines with larger node strength measures were sTNFR2 and CX3. The graphical network highlighted six cytokines strongly associated with resistant hypertension. Cytokines IL-29 and CCL3 were found to be negatively associated with resistant hypertension, whereas CXCL12, MMP3, sCD163, and sIL6Rb were positively associated with resistant hypertension. Discussion Understanding the network of associations through exploring oxidative stress and vascular inflammation may provide insight into treatment approaches for resistant hypertension.

Happy Family, Healthy Kids: A Healthy Eating and Stress Management Program in Low-Income Parent–Preschooler Dyads

Background Substantial effort has been invested to combat childhood obesity, but overall effects are disappointing, especially in low-income racial minority children. One possible reason is a lack of focus on the important stress–eating connection. Stress can negatively influence eating behaviors, leading to an increased appetite for high-fat and energy-dense foods. Objective This study aimed to evaluate the preliminary effects of a healthy eating and stress management program targeting multiple theoretical variables on improving eating behavior (dyads’ fruit/vegetable intake, emotional eating), food insecurity, anthropometric characteristics (dyads’ body mass index, % body fat), cardiovascular health (dyads’ blood pressure), and mental well-being (parental stress). Methods A one-group, quasi-experimental pilot study was conducted among 107 low-income parent–preschooler dyads. The 14-week program included a parent component, a parent–preschooler learning component, and a day care-based preschooler component. Results The program had positive effects on improving dyads’ fruit/vegetable intake, food insecurity, body mass index, and blood pressure and parents’ nutrition knowledge, self-efficacy, support, food resource management behavior, problem-focused coping, and home eating environment. The overall satisfaction rate was 95.2%, and 88.1% stated that the program assisted their families with having a healthy lifestyle. Discussion Results support the preliminary effects of the program on improving health outcomes in rural and urban low-income families. Although warranting further investigation with a more rigorous randomized controlled trial, the healthy eating and stress management program provides a potential solution to the current coexistence of an obesity epidemic and mental health crisis.

Symptoms in Patients Receiving Noninvasive Ventilation in the Intensive Care Unit

Background Although a multitude of studies have demonstrated the effectiveness of noninvasive ventilation (NIV) for treatment of respiratory insufficiency, there have been few investigations of patients’ experiences while receiving this common treatment. Identification of the presence, intensity, and distress of symptoms during NIV will inform the development and testing of interventions to best manage them and improve patients’ intensive care unit (ICU) experiences. Objective The objectives of this study were (a) to identify the presence, intensity, and distress of symptoms in patients receiving NIV in the ICU using a modified version of the Edmonton Symptom Assessment Scale (MESAS) and (b) to describe the most common and distressing symptoms experienced by patients. Methods A cross-sectional descriptive design was used with a convenience sample of 114 participants enrolled from three ICUs at one Midwestern medical center. Participants were approached if they were English-speaking, were 18 years old or older, and had an active order for NIV; exclusions included use of personal NIV equipment, severe cognitive impairment, or problems communicating. Demographic and clinical data were obtained from the electronic health record. Presence, intensity, and distress of patient-reported symptoms were obtained once using a modified, 11-item version of the MESAS. Results The mean age of participants was 68 years old, and 54.4% were male. The primary type of NIV was bi-level positive airway pressure; a nasal/oral mask was most frequently used. The symptoms experienced by most of the participants were thirst, anxiety, tiredness, and restlessness; these symptoms were rated as moderate or severe in both intensity and distress by most participants experiencing the symptoms. Discussion Patients in the ICU experience both intense and distressful symptoms that can be severe while undergoing treatment with NIV. Future research is warranted to determine these symptoms’ interrelatedness and develop interventions to effectively manage patient-reported symptoms.

Realist Approach to Qualitative Data Analysis

Background A realist approach has gained popularity in evaluation research, particularly in understanding causal explanations of how a program works (or not), the circumstances, and the observed outcomes. In qualitative inquiry, the approach has contributed to better theoretically based explanations regarding causal interactions. Objective The aim of this study was to discuss how we conducted a realist-informed data analysis to explore the causal interactions within qualitative data. Methods We demonstrated a four-step realist approach of retroductive theorizing in qualitative data analysis using a concrete example from our empirical research rooted in the critical realism philosophical stance. These steps include (a) category identification, (b) elaboration of context-mechanism-outcome configuration, (c) demi-regularities identification, and (d) generative mechanism refinement. Results The four-step qualitative realist data analysis underpins the causal interactions of important factors and reveals the underlying mechanisms. The steps produce comprehensive causal explanations that can be used by related parties—especially when making complex decisions that may affect wide communities. Discussion The core process of realist data analysis is retroductive theorizing. The four-step qualitative realist data analysis facilitates this theorizing by allowing the researcher to identify (a) patterns, (b) fluctuation of patterns, (c) mechanisms from collected data, and (d) to confirm proposed mechanisms.