Journal of Cardiovascular Nursing最新文献

Background: Clinical guidelines emphasize the administration of intravenous loop diuretics to manage acute decompensated heart failure (ADHF) effectively. Faster administration of diuretics, a concept called door-to-diuretic (D2D) time, may be associated with reduced hospital stay, lower readmission rates, and improved mortality and morbidity outcomes. Despite its significance, the factors contributing to prolonged D2D time remain unclear. Our aim was to identify predictors of prolonged D2D time among patients with ADHF.

Methods: In this retrospective analysis, we examined electronic medical records of 198 patients (275 hospitalizations) admitted with ADHF to the emergency department and who received intravenous diuretics at a major academic medical center. Predictor variables were standardized using z scores, and multicollinearity was assessed using the variance inflation factor. Feature selection was performed using recursive feature elimination and Least Absolute Shrinkage and Selection Operator regression, followed by backward elimination to refine the final model. Logistic regression models were fitted for different D2D time thresholds (<60 minutes, <90 minutes, median), and bootstrap resampling was conducted to validate model stability.

Results: The average D2D time was 328.56 minutes, with only n = 26 (12.6%) of patients receiving a diuretic within 90 minutes. The cohort was predominantly older (mean age, 71 years) and 57% male. Key predictors of prolonged D2D time included lower heart rate, respiratory rate, and diastolic blood pressure, as well as the absence of peripheral edema.

Conclusions: Identifying these predictors provides valuable insights into factors contributing to treatment delays in ADHF. Tailored interventions targeting these risk factors could improve clinical outcomes by ensuring timely diuretic administration.

Background: Although outpatient cardiac rehabilitation (OCR) is associated with improved outcomes post myocardial infarction (MI), authors of limited US studies report OCR travel distance/time estimates with fewer providing rural-urban comparisons.

Objective: We examined travel distance/time to the closest OCR facility for each Tennessee county.

Methods: We identified n = 61 Tennessee OCR facilities through a Tennessee Association of Cardiovascular and Pulmonary Rehabilitation list and a data scraping process using cardiac rehabilitation-related keywords. County-level mean travel distance/time to the closest OCR facility was determined using geospatial analysis. We conducted Kruskal-Wallis tests to examine whether mean travel distance/time varied by rural/urban county status and also by MI hospitalization rate status (low, 0 to <33.33 percentile; medium, 33.33 to <66.66 percentile; high, ≥66.66 percentile).

Results: Of Tennessee's 95 counties, 62.3% of facilities were in its 42 urban counties. Mean (SD) county-level travel distance to the closest OCR was 16.6 (10.0) miles, and mean (SD) county-level travel time was 27.9 (13.6) minutes. Travel distance/time did not significantly differ by rural/urban county status (rural: 15.4 miles, 28.9 minutes; urban: 12.9 miles, 23.2 minutes) or by MI hospitalization rate status (low: 10.4 miles, 19.6 minutes; medium: 14.5 miles, 24.1 minutes; high: 18.8 miles, 30.7 minutes).

Conclusions: Our findings indicate that overall mean travel distance was around half an hour, but lack of OCR facilities in rural Tennessee counties did not correspond with significantly greater travel distance/time to OCR in rural versus urban counties. Additional efforts are warranted to help patients post-MI with actual or perceived high travel burden navigate personal and structural factors precluding OCR receipt.

Background: Several risk prediction models are used in intensive care units (ICUs) to detect delirium risk.

Objective: The aim of this study was to compare the sex-specific validity of the Prediction of Delirium in ICU patients (PRE-DELIRIC) and Early Prediction of Delirium in ICU patients (E-PRE-DELIRIC) models for predicting delirium in ICU patients after cardiac surgery.

Methods: Retrospective data from electronic medical records of ICU patients who underwent cardiac surgery between January 2019 and December 2022 were examined. Both models were evaluated using sensitivity, specificity, and positive and negative predictive values based on the highest Youden index for female and male patients. Receiver operating characteristic curve analysis was performed.

Results: Delirium incidence was 30.7% and 27.5% in female and male patients, respectively. In the PRE-DELIRIC model, the highest Youden index scores for female and male patients were 67.00 and 57.54, respectively, with sensitivities and specificities of 61% and 88%, and 72% and 79%, respectively. In the E-PRE-DELIRIC model, the highest scores for female and male patients were 14.25 and 14.05, with sensitivities and specificities of 78% and 50%, and 70% and 53%, respectively. The area under the curve of the PRE-DELIRIC model for female and male patients was 0.77 and 0.78, respectively, and that of the E-PRE-DELIRIC model was 0.67 and 0.63, respectively.

Conclusions: The PRE-DELIRIC model showed higher specificity and was more reliable for male patients, whereas the E-PRE-DELIRIC model demonstrated better sensitivity for female patients due to its inclusion of more female-sensitive factors. A combined approach is recommended for improved reliability and validity in delirium risk assessment in clinical settings.

Background: Cardiac amyloidosis is a life-limiting disease with poor prognosis if not identified and treated early. Heart failure related to amyloidosis carries high mortality, necessitating timely intervention.

Purpose: This review provides an overview of recent American College of Cardiology guidelines regarding the multidisciplinary approach to diagnosing and managing cardiac amyloidosis, highlighting the essential role of nurses in early recognition and differentiation from other heart failure types.

Clinical implications: Heart failure nurses-whether formally designated as navigators or not-effectively connect patients with specialized amyloid centers and advanced therapies. By coordinating appointments, treatments, genetic testing, insurance, and education, nurses enhance care delivery and outcomes.

Conclusions: Early diagnosis and referral to specialized amyloidosis centers is crucial. Heart failure nurses or nurse navigators facilitate evaluation, make appropriate referrals, and coordinate care to improve treatment and reduce outcome disparities.

Background: Coronary heart disease is a leading cause of death worldwide with treatments including invasive surgical procedures coronary artery bypass grafting and heart valve replacement surgery. The creation of innovative multimedia health programs has the potential to support patient engagement at the bedside. The MyStay Cardiac multimedia program was developed to support patient engagement in the acute phase of postoperative recovery.

Objective: The aim of this study was to evaluate the feasibility and acceptability of a multimedia program (MyStay Cardiac).

Methods: A prospective cohort study utilizing a concurrent mixed methods approach. Feasibility and acceptability were measured by determining (i) patient engagement and (ii) patient and external factors impacting individual use of MyStay Cardiac.

Results: A total of 19 participants were recruited and most participants independently used MyStay Cardiac. There was a significant association between participants' total score on Health Literacy Questionnaire Domain 8 "Ability to find good health information," the total number of postoperative complications experienced, and experiencing postoperative cardiac arrhythmias and independent use of MyStay Cardiac. Factors enabling feasibility and acceptability of MyStay Cardiac included (i) program design and resources, (ii) participant health literacy, and (iii) social supports. Factors impeding feasibility and acceptability of MyStay Cardiac included (i) unstable internet, (ii) patient acuity and postoperative complications, and (iii) inconsistencies in information provided between clinicians and MyStay Cardiac.

Conclusion: MyStay Cardiac is a feasible and acceptable multimedia program for patient engagement in the context of acute cardiac care. Further investigation is needed to evaluate if the implementation of multimedia health programs results in improved patient outcomes.

Background: Self-care is essential in adults living with heart failure (HF). The landscape of HF management has changed considerably over the past few years, and as such, we modernized an existing measure of HF self-care. The purpose of this study was to test the psychometric properties of the revised Self-Care of Heart Failure Index (SCHFI) version 8.0 using item response theory.

Methods: A cross-sectional descriptive study was designed and conducted in the United States to test the psychometric properties of the 26-item SCHFI 8.0. We used item response theory-based approaches to determine which items contributed sufficient information to our understanding of the 3 behavioral domains: self-care maintenance (ie, routine healthy behaviors), self-care monitoring (ie, monitoring for signs and symptoms), and self-care management (ie, responding to signs and symptoms when they occur). We also used classic test theory approaches to compare results between the SCHFI 8.0 and prior versions.

Results: Participants included 217 adults with HF (mean age = 43 ± 15 years; 54.4% male, 56.2% White, 58% HF with reduced ejection fraction). Based on item response theory, items providing insufficient information within each behavioral domain were identified and removed from the SCHFI 8.0 during recalibration resulting in an abbreviated 23-item measure. The SCHFI 8.0 was most reliable at middle-to-low levels of each behavioral domain. Based on classic test theory, the self-care maintenance, self-care monitoring, and self-care management domains had Cronbach α values of 0.86, 0.90, and 0.88, respectively, and the theoretical structure of the SCHFI 8.0 was confirmed with factor analysis.

Conclusions: The 23-item SCHFI 8.0 is a valid, reliable and abbreviated measure that is ready to use and freely available on the website www.self-care-measures.com.

Background: The prevalence and mortality rates of cardiovascular diseases have been consistently high over the past 10 years in Ulsan, South Korea. Given the importance of social determinants in cardiovascular health, it is imperative to determine clusters with social determinants by a cluster analysis and their relationships with cardiovascular health.

Objective: The aims of this study were to identity clusters with distinct social determinants and to compare cardiovascular health among the identified clusters.

Methods: Social determinants (age, sex, job, education, monthly income, living location, medical institution usage, and experience of public resources), awareness and knowledge of stroke and myocardial infarction warning symptoms, health behaviors, and current history of hypertension, diabetes, and dyslipidemia were obtained from 1224 adults dwelling in Ulsan. A two-step cluster analysis, χ 2 test, and logistic regressions were used for data analysis.

Results: Three clusters were identified and named "middle-aged male workers" (n = 379, 31.0%), "young professionals" (n = 482, 39.4%), and "older female dependents" (n = 363, 29.7%). Among the 3 clusters, there were significant differences in self-reported awareness of stroke and myocardial infarction warning symptoms, smoking, alcohol consumption, and eating habits related to salt intake (all P s ≤ .001). In logistic regressions, "middle-aged male workers" versus "young professionals" had an odds ratio of 6.41 ( P  < .001) for hypertension and a 6.30 for diabetes ( P  < .001), whereas odds ratios for "older female dependents" versus "young professionals" were 10.23 for hypertension ( P  < .001), 7.64 for diabetes ( P  < .001), and 5.04 for dyslipidemia ( P  < .001).

Conclusions: Understanding subgroups vulnerable to cardiovascular health with distinct social determinants should be prioritized, and on the basis of this, a public health promotion program is warranted.

Background: Self-care is vital for recovery and long-term health in postcardiac surgery patients. The Self-Care of Chronic Illness Inventory Version 4.c (SC-CII-V4c) is widely used to assess self-care, but the psychometric properties in these patients remain underexplored.

Objective: The aim of this study was to evaluate psychometric properties of the SC-CII-V4c in Thai post cardiac surgery.

Methods: A cross-sectional study was conducted with 200 patients who underwent cardiac surgery at a tertiary care hospital in Thailand. The Thai SC-CII-V4c, assessing self-care across 3 domains, was administered. Psychometric testing involved exploratory and confirmatory factor analysis for structural validity. Internal reliability was estimated with Cronbach α , McDonald's ω, and composite reliability. Measurement error analysis was performed to evaluate scale precision.

Results: Exploratory factor analysis confirmed factor solutions with sufficient correlations for analysis. Confirmatory factor analysis demonstrated structural validity with good model fit for unidimensional Self-Care Maintenance, unidimensional Self-Care Monitoring, and bidimensional Self-Care Management scales. The Self-Care Maintenance structure and items allocations in the Self-Care Management dimensions differed from the previous US and Thai models. A simultaneous model combining all items supported the first-order structure, whereas the second-order model had partial support. Internal reliability was adequate across all scales ( α  = .86-.90, ω = 0.86-0.90; composite reliability, 0.85-0.90). Measurement error analysis demonstrated thresholds for meaningful score change.

Conclusions: The SC-CII-V4c is valid, reliable, and suitable for clinical practice and research to address self-care maintenance, monitoring, and management in Thai postcardiac surgery.

Background: A comprehensive understanding of the strategies that promote adherence is important for achieving optimal health outcomes in patients after percutaneous coronary intervention.

Objective: The aim of this study was to investigate the associations within Adherence Theory for patients with chronic disease after percutaneous coronary intervention during a long-term follow-up.

Design: A descriptive and exploratory study design was used in this study, with a survey conducted at 2 time points over 6 years.

Methods: Structural equation modeling was used to evaluate the model with baseline data from 2013 (n = 416) and follow-up data from 2019 (n = 167). The instruments used included the Adherence of Patients with Chronic Diseases and Social Support of People with Coronary Heart Disease questionnaires.

Results: Adherence Theory for patients with chronic disease showed a robust structure with no significant differences between 2013 and 2019. However, significant gender differences were observed in both years. Motivation was directly associated with adherence in 2013. For men, indirect associations were found between informational support, sense of normality, support from next of kin, and results of care. Adherence for women was not influenced by any identifiable factors in 2019, as observed in 2013. Among men, motivation was directly associated with adherence and indirectly linked to a sense of normality, fear of complications, and support from next of kin.

Conclusions: The results underscore the importance of critically reassessing nursing theories to ensure their relevance. This research-based knowledge can then be used to develop nursing interventions that promote person-centered care.

Background: Electronic health record (EHR) outcome ascertainment may introduce challenges if measurements are inconsistently or infrequently captured.

Objective: To evaluate the effects of the "Balance" intervention on EHR-derived secondary/exploratory outcomes and assess outcome frequency, timing, and variability.

Methods: Balance was a 2-arm, 12-month pragmatic randomized trial of a digital weight gain prevention intervention (N = 443). Cardiometabolic outcomes (eg, blood pressure, hemoglobin A1c, triglycerides, and total cholesterol) were extracted from the EHR and analyzed using linear mixed models.

Results: The intervention arm (n = 223) had lower systolic (-3.4 mm Hg, 95% confidence interval [CI]: -6.7 to -0.2) and diastolic blood pressure (-2.4 mm Hg, 95% CI: -4.3 to -0.6) at 6 months. Effects attenuated by 12 and 24 months. Other outcomes showed no significant differences. Blood pressure was measured 11.9 times per participant, 4.2 months apart. Other outcomes were measured 12 to 17.4 months apart. Variability averaged 1.0 standardized units.

Conclusions: Trials using EHR data should account for data variability and sparsity in trial planning, implementation, and analysis.