Polatstanton6361
Complete right bundle branch block (CRBBB) occurs in 0.2% to 1.3% of the general population, but its prognostic significance in the geriatric population is unknown. We prospectively investigated the prevalence and prognostic value of CRBBB in individuals aged ≥65 years in a community-based population in Taiwan. A total of 5,830 community-dwelling individuals were prospectively recruited from 7 regions across Taiwan starting in December 2008 through March 2013. Those aged ≥65 years were included in the analysis (N=3,383). All subjects underwent a home visit and standardized medical exams and were followed up annually until the end of April 2019; cause of death was documented by citizen death records. The mean age of the study cohort was 73.5±5.9 years (65-104), and 47.21% were men. Among these individuals, 171 (5.05%) had CRBBB; the prevalence was higher in men (7.08%) than in women (3.25%). Subjects with CRBBB were older than those without CRBBB (75.4±6.5 vs. 73.4±5.9), and the frequency of CRBBB increased with age. Survival analysis revealed that all-cause mortality and cardiac mortality were similar in individuals with and without CRBBB during a mean follow-up of 92.6±23.6 months. CRBBB is not associated with increased risk of mortality in the geriatric population.
Information and communication technology may provide domiciliary care programs with continuity of care. However, evidence about the effectiveness and cost-effectiveness of information and communication technology in the context of integrated care models is relatively scarce.
The objective of our study was to provide evidence on the clinical effectiveness and cost-effectiveness of the BeyondSilos project for patients enrolled in the Badalona city pilot site in Spain.
A quasi-experimental study was used to assess the cost-effectiveness of information and communication technology-enhanced integration of health and social care, including the third sector (intervention), compared to basic health and social care coordination (comparator). The study was conducted in Badalona between 2015 and 2016. Participants were followed for 8 months.
The study included 198 patients 98 in the intervention group and 100 in the comparator group. The mean Barthel index remained unchanged in the intervention group (mean changhow/ NCT03111004.
With an estimated prevalence of around 3% and an about 2.5-fold increased risk of stroke, atrial fibrillation (AF) is a serious threat for patients and a high economic burden for health care systems all over the world. Patients with AF could benefit from screening through mobile health (mHealth) devices. Thus, an early diagnosis is possible with mHealth devices, and the risk for stroke can be markedly reduced by using anticoagulation therapy.
The aim of this work was to assess the cost-effectiveness of algorithm-based screening for AF with the aid of photoplethysmography wrist-worn mHealth devices. Even if prevented strokes and prevented deaths from stroke are the most relevant patient outcomes, direct costs were defined as the primary outcome.
A Monte Carlo simulation was conducted based on a developed state-transition model; 30,000 patients for each CHA
DS
-VASc (Congestive heart failure, Hypertension, Age≥75 years, Diabetes mellitus, Stroke, Vascular disease, Age 65-74 years, Sex category [female]) rates led to higher numbers of prevented strokes. The use of mHealth (assuming a 75% ECG confirmation rate) resulted in 25 (7), -68 (-54), 98 (-5), 266 (182), 346 (271), 642 (440), 722 (599), 1111 (815), and 1116 (928) prevented strokes (fatal) for CHA
DS
-VASc score of 1 to 9, respectively. Higher device accuracy in terms of sensitivity led to even more prevented fatal strokes.
The use of mHealth devices to screen for AF leads to increased costs but also a reduction in the incidence of stroke. In particular, in patients with high CHA
DS
-VASc scores, the risk for stroke and death from stroke can be markedly reduced.
The use of mHealth devices to screen for AF leads to increased costs but also a reduction in the incidence of stroke. In particular, in patients with high CHA2DS2-VASc scores, the risk for stroke and death from stroke can be markedly reduced.
Tobacco smoking remains the leading cause of preventable death and disease worldwide. Digital interventions delivered through smartphones offer a promising alternative to traditional methods, but little is known about their effectiveness.
Our objective was to test the preliminary effectiveness of Quit Genius, a novel digital therapeutic intervention for smoking cessation.
A 2-arm, single-blinded, parallel-group randomized controlled trial design was used. Participants were recruited via referrals from primary care practices and social media advertisements in the United Kingdom. A total of 556 adult smokers (aged 18 years or older) smoking at least 5 cigarettes a day for the past year were recruited. Of these, 530 were included for the final analysis. Participants were randomized to one of 2 interventions. Treatment consisted of a digital therapeutic intervention for smoking cessation consisting of a smartphone app delivering cognitive behavioral therapy content, one-to-one coaching, craving tools, and ttment arm had not smoked in the preceding 7 days compared with 28.7% (76/265) in the control group (risk ratio 1.55, 95% CI 1.23-1.96; P<.001; intention-to-treat, n=530). Self-reported 7-day abstinence agreed with carbon monoxide measurement (carbon monoxide <10 ppm) in 96% of cases (80/83) where carbon monoxide readings were available. https://www.selleckchem.com/products/incb28060.html No harmful effects of the intervention were observed.
The Quit Genius digital therapeutic intervention is a superior treatment in achieving smoking cessation 4 weeks post quit date compared with very brief advice.
International Standard Randomized Controlled Trial Number (ISRCTN) 65853476; https//www.isrctn.com/ISRCTN65853476.
International Standard Randomized Controlled Trial Number (ISRCTN) 65853476; https//www.isrctn.com/ISRCTN65853476.
Engagement emerges as a predictor for the effectiveness of digital health interventions. However, a shared understanding of engagement is missing. Therefore, a new scale has been developed that proposes a clear definition and creates a tool to measure it. The TWente Engagement with Ehealth Technologies Scale (TWEETS) is based on a systematic review and interviews with engaged health app users. It defines engagement as a combination of behavior, cognition, and affect.
This paper aims to evaluate the psychometric properties of the TWEETS. In addition, a comparison is made with the experiential part of the Digital Behavior Change Intervention Engagement Scale (DBCI-ES-Ex), a scale that showed some issues in previous psychometric analyses.
In this study, 288 participants were asked to use any step counter app on their smartphones for 2 weeks. They completed online questionnaires at 4 time points T0=baseline, T1=after 1 day, T2=1 week, and T3=2 weeks. At T0, demographics and personality (conscientiousness and intellect/imagination) were assessed; at T1-T3, engagement, involvement, enjoyment, subjective usage, and perceived behavior change were included as measures that are theoretically related to our definition of engagement.
