16 research outputs found

    Atrial Fibrillation Symptom Clusters

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    Background: Atrial fibrillation (AF) is the most common arrhythmia in clinical practice. The majority of adults with AF are symptomatic, and symptoms are major determinants of quality-of-life. We proposed a theoretical model of symptom perception that involves both symptom detection and symptom interpretation. In order to better understand AF symptom perception, the aim of this body of work was to identify AF-specific symptom clusters, characterize individuals within clusters based on sociodemographic and clinical variables, and determine whether symptom cluster membership was associated with healthcare utilization (AF-related emergency department visits and hospitalizations). Methods/Results: Data sets from the Standard versus Atrial Fibrillation spEcific managemenT strategY (SAFETY) Trial (n=355) and Vanderbilt Atrial Fibrillation Registry (VAFR, n=1,501) were used to conduct cross-sectional secondary data analyses of adults with clinically verified AF. Symptom clusters were identified using self-reported symptoms and two statistical approaches: hierarchical cluster analysis and latent class analysis. Regression analyses were performed with VAFR to determine associations with healthcare utilization. Three symptom clusters were found using cluster analysis and SAFETY participants, 2 symptom clusters using cluster analysis and VAFR participants, and 4 symptom clusters using latent class analysis and VAFR participants. Symptom cluster membership was associated with gender, age, AF type, BMI, heart failure, coronary artery disease, current use of anti-arrhythmic medication, and history of ablation. Although the clusters differed between studies, when the results from the different studies were compared the results were complimentary. The symptom clusters found with VAFR were associated with an increased rate of AF-related emergency department visits and hospitalizations, either when compared to all individuals without that specific cluster (hierarchical cluster analysis), or when compared to an Asymptomatic cluster of patients (latent class analysis). Conclusions: Clinically meaningful symptom clusters were identified that were associated with increased rates of healthcare utilization. Both modifiable and non-modifiable sociodemographic and clinical characteristics are associated with cluster membership

    Razvojni prospekti bankarstva u novim i budućim zemljama članicama EU

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    Bank consolidation has substantially decreased the number of banks in European banking, which has had important implications for the banking sectors structure in all EU member countries. The consolidation processes have had a tremendous impact on the developments in banking sectors of new EU member countries, where major structural changes have been initiated mostly by new entrant banks from the old EU member countries. The future banking development in new EU member countries will very likely follow some main patterns known from the old EU members. Rather speculative conjectures, which are based on a comparison with banking sectors in other EU member countries indicate, that the total-asset-to-GDP ratio in new member countries should further improve in the future. The banking sector growth will be based mostly on the growth of the credit to non-banking sector, while banks are not expected anymore to use non-bank deposits as a predominant way of funding. Instead potentials for alternative funding possibilities should be activated. Although the non-bank financial intermediaries in new EU members represent a serious competition to banks, their relative underdevelopment prevents them from impacting the developments in banking sectors as known from old EU member countries.Konsolidacija banaka znatno je smanjila broj banaka u europskom bankarstvu, što ima značajne implikacije na bankarski sektor u svim zemljama članicama EU. Konsolidacija banaka imala je veliki utjecaj na razvoj bankarskog sektora svih novih zemalja članica, gdje su najveće strukturalne promjene inicirane stvaranjem novih banaka uz sudioništvo starih članica EU. Budući bankarski razvoj u novim zemljama članicama EU vjerojatno će se temeljiti na onom starih članica. Više spekulativna nagađanja, koja se temelje na usporedbi s bankarskim sektorima u drugim zemljama članicama, pokazuju da će se odnos kapitala prema BDP u novim zemljama članicama povećavati u budućnosti. Rast bankarskog sektora temeljit će se većim dijelom na rastu zajmova nebankarskim sektorima, a od banaka se očekuje da više ne rabe nebankarske depozite kao glavni oblik financiranja. Umjesto toga, trebaju se aktivirati mogućnosti za alternativnim financiranjem. Nebankarski financijski posrednici u novim zemljama članicama EU bankama predstavljaju ozbiljnu konkurenciju, međutim, njihova relativna nerazvijenost sprečava ih da utječu na razvoj u bankarskom sektoru kao što je to bio slučaj u starim zemljama članicama EU

    Energy expenditure in chronic stroke patients playing Wii Sports: a pilot study

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    Background: Stroke is one of the leading causes of long-term disability in modern western countries. Stroke survivors often have functional limitations which might lead to a vicious circle of reduced physical activity, deconditioning and further physical deterioration. Current evidence suggests that routine moderate- or vigorous-intensity physical activity is essential for maintenance and improvement of health among stroke survivors. Nevertheless, long-term participation in physical activities is low among people with disabilities. Active video games, such as Nintendo Wii Sports, might maintain interest and improve long-term participation in physical activities; however, the intensity of physical activity among chronic stroke patients while playing Wii Sports is unknown. We investigated the energy expenditure of chronic stroke patients while playing Wii Sports tennis and boxing. Methods: Ten chronic ([greater than or equal to] 6 months) stroke patients comprising a convenience sample, who were able to walk independently on level ground, were recruited from a rehabilitation centre. They were instructed to play Wii Sports tennis and boxing in random order for 15 minutes each, with a 10-minute break between games. A portable gas analyzer was used to measure oxygen uptake (VO2) during sitting and during Wii Sports game play. Energy expenditure was expressed in metabolic equivalents (METs), calculated as VO2 during Wii Sports divided by VO2 during sitting. We classified physical activity as moderate (3-6 METs) or vigorous (>6 METs) according to the American College of Sports Medicine and the American Heart Association Guidelines. Results: Among the 10 chronic stroke patients, 3 were unable to play tennis because they had problems with timing of hitting the ball, and 2 were excluded from the boxing group because of a technical problem with the portable gas analyzer. The mean ([plus/minus]SD) energy expenditure during Wii Sports game play was 3.7 ([plus/minus]0.6) METs for tennis and 4.1 ([plus/minus]0.7) METs for boxing. All 8 participants who played boxing and 6 of the 7 who played tennis attained energy expenditures >3 METs. Conclusions: With the exception of one patient in the tennis group, chronic stroke patients played Wii Sports tennis and boxing at moderate-intensity, sufficient for maintaining and improving health in this population

    Atrial fibrillation symptom profiles associated with healthcare utilization: A latent class regression analysis

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    Background Symptoms drive healthcare use among adults with atrial fibrillation, but limited data are available regarding which symptoms are most problematic and which patients are most at‐risk. The purpose of this study was to: (1) identify clusters of patients with similar symptom profiles, (2) characterize the individuals within each cluster, and (3) determine whether specific symptom profiles are associated with healthcare utilization. Methods We conducted a cross‐sectional secondary data analysis of 1,501 adults from the Vanderbilt Atrial Fibrillation Registry. Participants were recruited from Vanderbilt cardiology clinics, emergency department, and in‐patient services. Subjects included in our analysis had clinically verified atrial fibrillation and a completed symptom survey. Symptom and healthcare utilization data were collected with the University of Toronto Atrial Fibrillation Severity Scale. Latent class regression analysis was used to identify symptom clusters, with clinical and demographic variables included as covariates. We used Poisson regression to examine the association between latent class membership and healthcare utilization. Results Participants were predominantly male (67%) with a mean age of 58.4 years (±11.9). Four latent classes were evident, including an Asymptomatic cluster (N = 487, 38%), Highly Symptomatic cluster (N = 142, 11%), With Activity cluster (N = 326, 25%), and Mild Diffuse cluster (N = 336, 26%). Highly Symptomatic membership was associated with the greatest rate of emergency department visits and hospitalizations (incident rate ratio 2.4, P < 0.001). Conclusions Clinically meaningful atrial fibrillation symptom profiles were identified that were associated with increased rates of emergency department visits and hospitalizations

    Atrial fibrillation symptom clusters and associated clinical characteristics and outcomes: a cross-sectional secondary data analysis

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    Background: Symptom clusters among adults with atrial fibrillation have previously been identified but no study has examined the relationship between symptom clusters and outcomes. Aims: The purpose of this study was to identify atrial fibrillation-specific symptom clusters, characterize individuals with each cluster, and determine whether symptom cluster membership is associated with healthcare utilization. Methods: This was a cross-sectional secondary data analysis of 1501 adults from the Vanderbilt Atrial Fibrillation Registry with verified atrial fibrillation. Self-reported symptoms were measured with the University of Toronto Atrial Fibrillation Severity Scale. We used hierarchical cluster analysis (Ward’s method) to identify clusters and dendrograms, pseudo F, and pseudo T-squared to determine the ideal number of clusters. Next, we used regression analysis to examine the association between cluster membership and healthcare utilization. Results: Males predominated (67%) and the average age was 58.4 years. Two symptom clusters were identified, a Weary cluster (3.7%, n=56, fatigue at rest, shortness of breath at rest, chest pain, and dizziness) and an Exertional cluster (32.7%, n=491, shortness of breath with activity and exercise intolerance). Several sociodemographic and clinical characteristics varied by symptom cluster group membership, including age, gender, atrial fibrillation type, body mass index, comorbidity status, and treatment strategy. Women were more likely to experience either cluster (p<0.001). The Weary cluster was associated with nearly triple the rate of emergency department utilization (incident rate ratio [IRR] 2.8, p<0.001) and twice the rate of hospitalizations (IRR 1.9, p<0.001). Conclusion: We identified two symptom clusters. The Weary cluster was associated with a significantly increased rate of healthcare utilization

    Atrial fibrillation symptom profiles associated with healthcare utilization: a latent class regression analysis

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    Background Symptoms drive healthcare use among adults with atrial fibrillation, but limited data are available regarding which symptoms are most problematic and which patients are most at‐risk. The purpose of this study was to: (1) identify clusters of patients with similar symptom profiles, (2) characterize the individuals within each cluster, and (3) determine whether specific symptom profiles are associated with healthcare utilization. Methods We conducted a cross‐sectional secondary data analysis of 1,501 adults from the Vanderbilt Atrial Fibrillation Registry. Participants were recruited from Vanderbilt cardiology clinics, emergency department, and in‐patient services. Subjects included in our analysis had clinically verified atrial fibrillation and a completed symptom survey. Symptom and healthcare utilization data were collected with the University of Toronto Atrial Fibrillation Severity Scale. Latent class regression analysis was used to identify symptom clusters, with clinical and demographic variables included as covariates. We used Poisson regression to examine the association between latent class membership and healthcare utilization. Results Participants were predominantly male (67%) with a mean age of 58.4 years (±11.9). Four latent classes were evident, including an Asymptomatic cluster (N = 487, 38%), Highly Symptomatic cluster (N = 142, 11%), With Activity cluster (N = 326, 25%), and Mild Diffuse cluster (N = 336, 26%). Highly Symptomatic membership was associated with the greatest rate of emergency department visits and hospitalizations (incident rate ratio 2.4, P < 0.001). Conclusions Clinically meaningful atrial fibrillation symptom profiles were identified that were associated with increased rates of emergency department visits and hospitalizations

    State of the Science: The Relevance of Symptoms in Cardiovascular Disease and Research: A Scientific Statement from the American Heart Association

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    Symptoms of cardiovascular disease drive health care use and are a major contributor to quality of life. Symptoms are of fundamental significance not only to the diagnosis of cardiovascular disease and appraisal of response to medical therapy but also directly to patients' daily lives. The primary purpose of this scientific statement is to present the state of the science and relevance of symptoms associated with cardiovascular disease. Symptoms as patient-reported outcomes are reviewed in terms of the genesis, manifestation, and similarities or differences between diagnoses. Specifically, symptoms associated with acute coronary syndrome, heart failure, valvular disorders, stroke, rhythm disorders, and peripheral vascular disease are reviewed. Secondary aims include (1) describing symptom measurement methods in research and application in clinical practice and (2) describing the importance of cardiovascular disease symptoms in terms of clinical events and other patient-reported outcomes as applicable
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