BackgroundAtrial fibrillation (AF) is associated with substantial morbidity, in particular stroke. Despite good evidence for the reduction of stroke risk with anticoagulant therapy, there remains significant undertreatment. The main aim of the current study was to investigate whether a clinical decision support tool (CDS) for stroke prevention integrated in the electronic health record could improve adherence to guidelines for stroke prevention in patients with AF.Methods and findingsWe conducted a cluster-randomized trial where all 43 primary care clinics in the county of Östergötland, Sweden (population 444,347), were randomized to be part of the CDS intervention or to serve as controls. The CDS produced an alert for physicians responsible for patients with AF and at increased risk for thromboembolism (according to the CHA2DS2-VASc algorithm) without anticoagulant therapy. The primary endpoint was adherence to guidelines after 1 year. After randomization, there were 22 and 21 primary care clinics in the CDS and control groups, respectively. There were no significant differences in baseline adherence to guidelines regarding anticoagulant therapy between the 2 groups (CDS group 70.3% [5,186/7,370; 95% CI 62.9%–77.7%], control group 70.0% [4,187/6,009; 95% CI 60.4%–79.6%], p = 0.83). After 12 months, analysis with linear regression with adjustment for primary care clinic size and adherence to guidelines at baseline revealed a significant increase in guideline adherence in the CDS (73.0%, 95% CI 64.6%–81.4%) versus the control group (71.2%, 95% CI 60.8%–81.6%, p = 0.013, with a treatment effect estimate of 0.016 [95% CI 0.003–0.028]; number of patients with AF included in the final analysis 8,292 and 6,508 in the CDS and control group, respectively). Over the study period, there was no difference in the incidence of stroke, transient ischemic attack, or systemic thromboembolism in the CDS group versus the control group (49 [95% CI 43–55] per 1,000 patients with AF in the CDS group compared to 47 [95% CI 39–55] per 1,000 patients with AF in the control group, p = 0.64). Regarding safety, the CDS group had a lower incidence of significant bleeding, with events in 12 (95% CI 9–15) per 1,000 patients with AF compared to 16 (95% CI 12–20) per 1,000 patients with AF in the control group (p = 0.04). Limitations of the study design include that the analysis was carried out in a catchment area with a high baseline adherence rate, and issues regarding reproducibility to other regions.ConclusionsThe present study demonstrates that a CDS can increase guideline adherence for anticoagulant therapy in patients with AF. Even though the observed difference was small, this is the first randomized study to our knowledge indicating beneficial effects with a CDS in patients with AF.Trial registrationClinicalTrials.gov NCT02635685
In this article, we present Power Agent-a pervasive game designed to encourage teenagers and their families to reduce energy consumption in the home. The ideas behind this mobile phonebased game are twofold; to transform the home environment and its devices into a learning arena for hands-on experience with electricity usage and to promote engagement via a team competition scheme. We report on the game's evaluation with six teenagers and their families who played the game for ten days in two cities in Sweden. Data collection consisted of home energy measurements before, during, and after a game trial, in addition to interviews with participants at the end of the evaluation. The results suggest that the game concept was highly efficient in motivating and engaging the players and their families to change their daily energy-consumption patterns during the game trial. Although the evaluation does not permit any conclusions as to whether the game had any postgame effects on behavior, we can conclude that the pervasive persuasive game approach appears to be highly promising in regard to energy conservation and similar fields or issues.
Smart electricity meters and home displays are being installed in people's homes with the assumption that households will make the necessary efforts to reduce their electricity consumption. However, present solutions do not sufficiently account for the social implications of design. There is a potential for greater savings if we can better understand how such designs affect behaviour. In this paper, we describe our design of an energy awareness artefact-the Energy AWARE Clock-and discuss it in relation to behavioural processes in the home. A user study is carried out to study the deployment of the prototype in real domestic contexts for three months. Results indicate that the Energy AWARE Clock played a significant role in drawing households' attention to their electricity use. It became a natural part of the household and conceptions of electricity became naturalized into informants' everyday language.
Sepsis is a major health concern with global estimates of 31.5 million cases per year. Case fatality rates are still unacceptably high, and early detection and treatment is vital since it significantly reduces mortality rates for this condition. Appropriately designed automated detection tools have the potential to reduce the morbidity and mortality of sepsis by providing early and accurate identification of patients who are at risk of developing sepsis. In this paper, we present “LiSep LSTM”; a Long Short-Term Memory neural network designed for early identification of septic shock. LSTM networks are typically well-suited for detecting long-term dependencies in time series data. LiSep LSTM was developed using the machine learning framework Keras with a Google TensorFlow back end. The model was trained with data from the Medical Information Mart for Intensive Care database which contains vital signs, laboratory data, and journal entries from approximately 59,000 ICU patients. We show that LiSep LSTM can outperform a less complex model, using the same features and targets, with an AUROC 0.8306 (95% confidence interval: 0.8236, 0.8376) and median offsets between prediction and septic shock onset up to 40 hours (interquartile range, 20 to 135 hours). Moreover, we discuss how our classifier performs at specific offsets before septic shock onset, and compare it with five state-of-the-art machine learning algorithms for early detection of sepsis.
In this article, we present Power Agent-a pervasive game designed to encourage teenagers and their families to reduce energy consumption in the home. The ideas behind this mobile phonebased game are twofold; to transform the home environment and its devices into a learning arena for hands-on experience with electricity usage and to promote engagement via a team competition scheme. We report on the game's evaluation with six teenagers and their families who played the game for ten days in two cities in Sweden. Data collection consisted of home energy measurements before, during, and after a game trial, in addition to interviews with participants at the end of the evaluation. The results suggest that the game concept was highly efficient in motivating and engaging the players and their families to change their daily energy-consumption patterns during the game trial. Although the evaluation does not permit any conclusions as to whether the game had any postgame effects on behavior, we can conclude that the pervasive persuasive game approach appears to be highly promising in regard to energy conservation and similar fields or issues.
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