European journal of cardiovascular nursing最新文献

Aims: To explore the possible latent classifications of pre-hospital delayed intention at high risk of stroke and to analyse the characteristics of different profiles.

Methods and results: A cross-sectional study was conducted in one community in Shanghai, China. Four hundred and seventy individuals at high risk of stroke were recruited, and self-reported questionnaires (including socio-demographic, stroke knowledge, health belief, and pre-hospital delay behaviour intention scale) were distributed between April and June 2023. A latent profile analysis was employed to identify the delay intention clusters, and multinomial logistic regression was utilized to ascertain the factors influencing the latent classes of delay intention. Four hundred and fifty-seven high-risk populations with a response rate of 97.23% were finally enrolled in this study. Four distinct classes were identified: high warning signs-low delay intention (26.3%), low warning signs-low delay intention (17.7%), moderate level of delay intention (37.3%), and high level of delay intention (18.7%). The influencing factors included stroke knowledge, health belief, age, education background, the nearest distance to the medical institution, and household income.

Conclusion: The pre-hospital delay intention among high-risk populations of stroke was classified into four distinct classes. It is crucial for individuals at high risk to remain vigilant towards stroke symptoms and to take prompt action. Health promotion education may be explored as a strategy to bridge the gap between the recognition of stroke symptoms and the low pre-hospital delay intention.

Aims: Depression and anxiety occur frequently in individuals with cardiovascular disease and are associated with poor prognosis. This Cochrane systematic review and meta-analysis assessed the effectiveness of psychological interventions on psychological and clinical outcomes in adults with coronary heart disease (CHD), heart failure (HF) or atrial fibrillation (AF).

Methods and results: CENTRAL, MEDLINE, Embase, PsycINFO, and CINAHL databases were searched from January 2009 to July 2022 for randomized controlled trials of psychological interventions vs. controls in adults with CHD, HF, or AF. Twenty-one studies (n = 2591) were assessed using random-effects models. We found psychological interventions reduced depression [standardized mean difference (SMD) -0.36; 95% confidence interval (CI) -0.65 to -0.06; P = 0.02], anxiety (SMD -0.57; 95% CI -0.96 to -0.18; P = 0.004), and improved mental health-related quality of life (HRQoL) (SMD 0.63, 95% CI 0.01 to 1.26; P = 0.05) (follow-up 6-12 months), but not physical health-related quality of life, all-cause mortality or major adverse cardiovascular events compared with controls. High heterogeneity was present across meta-analyses. Meta-regression analysis showed that psychological interventions designed to target anxiety, were more effective than non-targeted interventions.

Conclusion: This review found that psychological interventions improved depression, anxiety and mental HRQoL, with those targeting anxiety to show most benefit. Given the statistical heterogeneity, the precise magnitude of effects remains uncertain. Increasing use of multifactorial psychological interventions shows promise for incorporating patient needs and preferences. Investigation of those at high risk of poor outcomes, comparison of intervention components and those with AF is warranted.

Aims: Smartphone applications for heart rate and rhythm assessment are increasingly used for the management of atrial fibrillation (AF). Although the use of a photoplethysmography (PPG)-based smartphone application with subsequent (tele)consultations for AF management has been proven feasible in the TeleCheck-AF project, specific needs, and expectations of patients with AF are unclear. The aim of this study is to evaluate patients' perspectives on the use of remote PPG-based electronical health (eHealth) integrated in regular care pathways for AF.

Methods and results: A qualitative study was conducted among patients with known AF, who have used a PPG-based smartphone application around scheduled (tele)consultations. Semi-structured interviews were audio-recorded and transcribed verbatim. Data were analysed according to conventional content analysis.In total, 14 patients were interviewed. Five main themes were defined after analysis, i.e. smartphone application usability, requirements for eHealth implementation, remote self-assessment, patient engagement, and blended care (i.e. combining digital and face-to-face care). Overall, the participants were positive about the use of the PPG-based smartphone application and subsequent (tele)consultation. Using this application made the participants feel involved and led to active participation. In addition, the healthcare provider-patient relationship appeared an important aspect for adequate implementation. Particularly, timely consultation was found important, to discuss the results with their healthcare provider.

Conclusion: The results of this study emphasize the importance of blended care for the implementation of remote PPG-based eHealth in AF management. The use of a PPG-based smartphone application in regular care can support patient engagement and subsequently the process of shared decision making.

The electronic health record (EHR) contains valuable patient data and offers opportunities to administer and analyse patients' individual needs longitudinally. However, most information in the EHR is currently stored in unstructured text notations. Natural language processing (NLP), a branch of artificial intelligence that enables computers to understand, interpret, and generate human language, can be used to delve into unstructured text data to uncover valuable insights and knowledge. This article discusses different types of NLP, the potential of NLP for cardiovascular nursing, and how to get started with NLP as a clinician.