Aim Self-reported cognitive function has been described as an important complement to performance-based measurements but has seldom been investigated in cardiac arrest (CA) survivors. Therefore, the aim was to describe self-reported cognitive function and its association with health status, psychological distress, and life satisfaction. Methods This study utilised data from the Swedish Register of Cardiopulmonary Resuscitation (2018–2021), registered 3–6 months post-CA. Cognitive function was assessed by a single question: “How do you experience your memory, concentration, and/or planning abilities today compared to before the cardiac arrest?”. Health status was measured using the EQ VAS, psychological distress with the Hospital Anxiety and Depression Scale, and overall life satisfaction with the Life Satisfaction checklist. Data were analysed using binary logistic regression. Results Among 4026 identified survivors, 1254 fulfilled the inclusion criteria. The mean age was 65.9 years (SD = 13.4) and 31.7% were female. Self-reported cognitive function among survivors was reported as: ‘Much worse’ by 3.1%, ‘Worse’ by 23.8%, ‘Unchanged’ by 68.3%, ‘Better’ by 3.3%, and ‘Much better’ by 1.5%. Declined cognitive function was associated with lower health status (OR = 2.76, 95% CI = 2.09–3.64), symptoms of anxiety (OR = 3.84, 95% CI = 2.80–5.24) and depression (OR = 4.52, 95% CI = 3.22–6.32), and being dissatisfied with overall life (OR = 2.74, 95% CI = 2.11–3.54). These associations remained significant after age, sex, place of CA, aetiology, initial rhythm, initial witnessed status, and cerebral performance were controlled. Conclusions Survivors experiencing declined cognitive function post-CA are at a higher risk of poorer health status, increased psychological distress, and reduced life satisfaction, and these risks should be acknowledged by healthcare professionals.

Aims Due to insufficient evidence and a lack of cohesive guidelines, the management and use of fluid restriction in patients with heart failure (HF) may vary among healthcare professionals. However, the extent of this variation is unknown. The aim of this study was to describe physicians' and registered nurses' (RN) clinical practice regarding fluid intake and fluid restriction in adult patients with HF. Methods and results Physicians and RNs treating patients with HF at 75 hospitals across all healthcare regions in Sweden were invited to answer a web-based survey regarding management on fluid intake and fluid restriction. Data were analysed with descriptive statistics and chi-square test. A total of 646 physicians and RNs across 45 hospitals in Sweden completed the survey. Significant differences in recommendations and management were found in relation to professional role, care setting and work experience. Overall, 93.8% recommend fluid restriction for all or some patients with HF. RNs recommend fluid restriction for all patients with HF to a significantly higher extent compared with physicians (34.5% vs. 14.9%; P < 0.001). Additionally, 49.2% believe that fluid restriction is an effective treatment strategy to prevent congestion, and 29.3% recommend fluid restriction routinely. One-third lacked knowledge of existing local guidelines regarding fluid restriction. Conclusions This study shows that there are differences in clinical practice regarding healthcare professionals' recommendations on fluid intake and fluid restriction. These differences may result in patients with HF receiving varied and inconsistent care. Recommendations were primarily based on each healthcare professional's individual opinion rather than on evidence and guidelines.

PurposeNew research shows the benefits of mobile health (mHealth) interventions for older adults. However, older adults adopt digital technology less than younger ones. This study measures the task effectiveness, perceived usability, and acceptability of a mHealth intervention (i.e., Get FIT +) consisting of a wearable activity tracker, access to the MyFitnessPal app, and personalized text messages to promote healthy behaviors in older adults.MethodsParticipants used the Get FIT + intervention for 12 weeks and engaged in monthly clinic visits with an advanced practice nurse (APRN) to monitor their progress. The monthly sessions instructed them to use the think-aloud process while doing specific tasks (e.g., using the app). Participants also completed the USABILITY Survey and provided feedback on the intervention's acceptability after the 12-week trial.ResultsThirty older adults (mean age 66.6 +/- 5.9 years, 60% female, 60% married, 50% Asian, 37% White, and 13% Hispanic) participated in this sub-analysis. Participants were able to complete the assigned tasks efficiently. The usability satisfaction assessment suggests a high level of satisfaction. The participants responded positively to Get FIT + and successfully incorporated it into their routines.ConclusionsOur findings show that Get FIT + technologies, including smartphones, smartphone-based applications, and integrated sensors, are practical, usable, and acceptable for older adults at risk for cardiovascular disease. These scalable, low-cost technologies offer methods to monitor and promote a healthy lifestyle and enhance overall well-being.

Background: Heart failure (HF) is a common and deadly disease, precipitated by physical inactivity and sedentary behavior. Although the 1-year survival rate after the first diagnosis is high, physical inactivity and sedentary behavior are associated with increased mortality and negatively impact the health-related quality of life (HR-QoL).

Objective: We tested the recruitment frequency, implementation fidelity, and feasibility of outcomes of the Activity Coach app that was developed using an existing mobile health (mHealth) tool, Optilogg, to support older adults with HF to be more physically active and less sedentary.

Methods: In this pilot clinical randomized controlled trial (RCT), patients with HF who were already using Optilogg to enhance self-care behavior were recruited from 5 primary care health centers in Sweden. Participants were randomized to either have their mHealth tool updated with the Activity Coach app (intervention group) or a sham version (control group). The intervention duration was 12 weeks, and in weeks 1 and 12, the participants wore an accelerometer daily to objectively measure their physical activity. The HR-QoL was measured with the Kansas City Cardiomyopathy Questionnaire (KCCQ), and subjective goal attainment was assessed using goal attainment scaling. Baseline data were collected from the participants’electronic health records (EHRs).

Results: We found 67 eligible people using the mHealth tool, of which 30 (45%) initially agreed to participate, with 20 (30%) successfully enrolled and randomized to the control and intervention groups in a ratio of 1:1. The participants’ daily adherence to registering physical activity in the Activity Coach app was 69% (range 24%-97%), and their weekly adherence was 88% (range 58%-100%). The mean goal attainment score was –1.0 (SD 1.1) for the control group versus 0.6 (SD 0.6) for the intervention group (P=.001). The mean change in the overall HR-QoL summary score was –9 (SD 10) for the control group versus 3 (SD 13) in the intervention group (P=.027). There was a significant difference in the physical limitation scores between the control (mean 45, SD 27) and intervention (mean 71, SD 20) groups (P=.04). The average length of sedentary bouts increased by 27 minutes to 458 (SD 84) in the control group minutes and decreased by 0.70 minutes to 391 (SD 117) in the intervention group (P=.22). There was a nonsignificant increase in the mean light physical activity (LPA): 146 (SD 46) versus 207 (SD 80) minutes in the control and intervention groups, respectively (P=.07).

Conclusions: The recruitment rate was lower than anticipated. An active recruitment process is advised if a future efficacy study is to be conducted. Adherence to the Activity Coach app was high, and it may be able to support older adults with HF in being physically active.

Trial Registration: ClinicalTrials.gov NCT05235763; https://clinicaltrials.gov/study/NCT05235763

AimThis paper describes the trajectory during 1 year of four patient-reported outcomes (PROs), namely, sleep, depressive symptoms, health-related quality of life (HrQoL), and well-being, in patients with heart failure (HF), their relationship and the patient characteristics associated with changes in these PROs.Methods and resultsData analyses of PROs from 603 patients (mean age 67 years; 29% female, 60% NYHA II) enrolled in the HF-Wii study. On short term, between baseline and 3 months, 16% of the patients experienced continuing poor sleep, 11% had sustained depressive symptoms, 13% had consistent poor HrQoL, and 13% consistent poor well-being. Across the entire 1-year period only 21% of the patients had good PRO scores at all timepoints (baseline, 3, 6, and 12 months). All others had at least one low score in any of the PROs at some timepoint during the study. Over the 12 months, 17% had consistently poor sleep, 17% had sustained symptoms of depression, 15% consistently rated a poor HrQoL, and 13% poor well-being. Different patient characteristics per PRO were associated with a poor outcomes across the 12 months. Age, education, New York Heart Association, and length of disease were related to two PRO domains and submaximal exercise capacity (6 min test), co-morbidity, and poor physical activity to one.ConclusionIn total, 79% of the patients with HF encountered problems related to sleep, depressive symptoms, HrQoL, and well-being at least once during a 1-year period. This underscores the need for continuous monitoring and follow-up of patients with HF and the need for dynamic adjustments in treatment and care regularly throughout the HF trajectory.

There are important differences in epidemiology, pathophysiology, heart failure (HF) type, prognosis, and treatment. Women with HF have a higher incidence of HF with preserved ejection fraction (HFpEF) but in general treatment recommendation for guideline directed therapy are similar for men and women. There are still gaps in the management of women with HF. Self-care behaviour is vital for optimal outcomes for patients with HF and although there is no difference in the content of self-care advice, the challenges for optimal self-care might be different for women. A person-centred approach to treat and support women with HF is needed to attain optimal outcomes.

Aims The aims of this study were (i) to evaluate the effects of using an m-health tool on self-care behaviour at 3 and 12 months and (ii) to explore the experiences and perceptions of heart failure (HF) patients about the m-health tool.Methods and results In this pre-post interventional study with a mixed-method analysis, 71 patients diagnosed with HF [49% female, mean age 76.7 years, New York Heart Association (NYHA) II 31%, NYHA III 69%] were enrolled and had the m-health tool installed in their home for 1 year. The tool consisted of a pre-programmed tablet including a weighing scale and interactive education about HF self-care. At baseline, and at 3 and 12 months, self-care was assessed using the European Heart Failure Self-care Behaviour (EHFScB-9) Scale, an eight-item self-administered questionnaire assessing the experiences of the m-health tool. The mean EHFScB-9 at baseline was 63.8 +/- 2.8 and it improved to 67.6 +/- 7.6 after 3 months (P < 0.05). After 1 year, the score had decreased to 63.2 +/- 7.1 (P = 0.68). Most patients rated the tool as 'good', both at 3 months (92%) and after 12 months (93%). Some found the system to be unnecessary to some degree, and this number increased between 3 and 12 months (P < 0.001). Most patients felt that m-health increased their feelings of security, and 85% responded that the system increased their family members' sense of security.Conclusion The m-health tool significantly improved patients' self-care behaviour after 3 months, but this effect did not persist after 1 year. For achieving long-term effects and outcomes, additional and regularly updated self-care support may be needed.

AIM: The aim of this study is to examine whether a conceptual model including the associations between continuity of care, perceived control and self-care could explain variations in health-related quality of life and hospital readmissions in people with chronic cardiac conditions after hospital discharge.

DESIGN: Correlational design based on cross-sectional data from a multicentre survey study.

METHODS: People hospitalized due to angina, atrial fibrillation, heart failure or myocardial infarction were included at four hospitals using consecutive sampling procedures during 2017-2019. Eligible people received questionnaires by regular mail 4-6 weeks after discharge. A tentative conceptual model describing the relationship between continuity of care, self-care, perceived control, health-related quality of life and readmission was developed and evaluated using structural equation modelling.

RESULTS: In total, 542 people (mean age 75 years, 37% females) were included in the analyses. According to the structural equation model, continuity of care predicted self-care, which in turn predicted health-related quality of life and hospital readmission. The association between continuity of care and self-care was partly mediated by perceived control. The model had an excellent model fit: RMSEA = 0.06, 90% CI, 0.05-0.06; CFI = 0.90; TLI = 0.90.

CONCLUSION: Interventions aiming to improve health-related quality of life and reduce hospital readmission rates should focus on enhancing continuity of care, perceived control and self-care.

IMPACT: This study reduces the knowledge gap on how central factors after hospitalization, such as continuity of care, self-care and perceived control, are associated with improved health-related quality of life and hospital readmission in people with cardiac conditions. The results suggest that these factors together predicted the quality of life and readmissions in this sample. This knowledge is relevant to researchers when designing interventions or predicting health-related quality of life and hospital readmission. For clinicians, it emphasizes that enhancing continuity of care, perceived control and self-care positively impacts clinical outcomes.

PATIENT OR PUBLIC CONTRIBUTION: People and healthcare personnel evaluated content validity and were included in selecting items for the short version.

Background There are calls to integrate serial recordings of health related quality of life (HRQoL) into routine care, clinical trials and prognosis. Little is known about the relationship between change in HRQoL and outcomes in heart failure (HF) patients by age, sex and HF subtype. Method From the Swedish Heart Failure Registry (SwedeHF; 2008-2019), patients were categorised by reduced (<40%, HFrEF), mildly-reduced (40-49%, HFmrEF) and preserved (>= 50%, HFpEF) ejection fraction. HRQoL was measured using Euro-QoL-5D visual analogue scale (EQ5D-vas), collected at baseline and 1-year. Baseline EQ5Dvas scores were categorised by: "best" (76-100), "good" (51-75), "bad" (26-50), and "worst" (0-25). Change in EQ5D-vas was categorised as 'no significant change' (<5 points increase/decrease); some worsening (5-9 points decrease); considerable worsening (>= 10 points decrease); some improvement (5-9 points increase); considerable improvement (>= 10 points increase). Associations with admission and death were estimated and interactions with patient sub-groups tested. Findings Among 23,553 patients (median age 74 [66-81] years, 8000 [34%] female), baseline EQ5D-vas was worse in older patients, women, and those with HFpEF compared to their respective counterparts. Compared to patients with the "best" EQ5D-vas, the adjusted associations for admission for those with "good", "bad" and "worst" EQ5D-vas were, respectively: HR 1.09 (1.04, 1.14), 1.27 (1.21, 1.33) and 1.39 (1.28, 1.51). Compared to no significant change in EQ5D-vas, the adjusted estimates for admission following some improvement, considerable improvement, some worsening and considerable worsening were, respectively: HR 0.91 (0.82, 1.01), 0.75 (0.70, 0.81), 1.04 (0.92, 1.16) and 1.25 (1.16, 1.35). Results were similar amongst groups and for HF admission and death. Interpretation Change in HRQoL was an independent indicator of risk of admission and death in people with all HF subtypes, irrespective of age and sex.

To improve the practical application of measuring exercise capacity, the purpose of this study was to compare the 6 min walk distance (6MWD) obtained at a 30 m track with the guidance of healthcare professionals vs. the 6MWD obtained by participants themselves using an app. In total, 37 participants performed both tests. The mean of the differences between the 6MWD on the tests was -4 +/- 45 m (95% limits of agreement: 84 to -99 m). The overall agreement between the two 6MWD measures was 97% with an intraclass correlation coefficient of 0.96 (95% confidence interval: 0.91-0.98, P < 0.001). The use of an app is feasible, reliable, and valid to assess the 6MWD.