Can we improve outcomes in AF patients by early therapy?

Atrial fibrillation affects at least 1% of the population and causes marked society-wide morbidity and mortality. Current management of atrial fibrillation including antithrombotic therapy and management of concomitant conditions in all patients, rate control therapy in most patients, and rhythm control therapy in patients with severe atrial fibrillation-related symptoms can alleviate atrial fibrillation-related symptoms but can neither effectively prevent recurrent atrial fibrillation nor suppress atrial fibrillation-related complications. Hence, there is a need for better therapy of atrial fibrillation

Ambulatory assessment of psychophysiological stress among police officers: A proof-of-concept study.

Occupational stress has been widely recognized as a global challenge and has received increased attention by the academic community. Ambulatory Assessment methodologies, combining psychophysiological measures of stress, offer a promising avenue for future prevention and/or rehabilitation stress research. Considering that policing is well known for being a particularly stressful occupation, Emergency Responders Officers (EROs) stress levels were investigated. Particularly, this study analyzed: (i) physiological stress data obtained during shifts and compared these data with baseline levels (days off), as well as (ii) with normative values for healthy populations; (iii) stress symptoms differences from beginning to end of shift; (iv) stress events and events intensity and (v) the acceptability and feasibility of this proof-of-concept study in a highly stressful occupation. A Geo-location event system was used to help retrospective accounts of psychological stress, combined with electrocardiogram (ECG) data and mobile self-reports, that include stress symptoms, event types and event intensity. Results suggest that EROs experience high levels of stress (both on-duty and off duty) when compared to healthy populations. Stress symptoms increase from the beginning to end of the shift. However, the mean events intensity was very low. It can be concluded that stress may not always be diagnosed when using merely self-reports. These findings highlight the importance of combining both self-report and physiological stress measures in occupational health contexts. Finally, results confirm the acceptability and feasibility of the multi-method used. Key implications for policy makers and applied practitioners in the area of occupational health and future research directions are discussed

The impact of adjuvant therapy on contralateral breast cancer risk and the prognostic significance of contralateral breast cancer: a population based study in the Netherlands

Background The impact of age and adjuvant therapy on contralateral breast cancer (CBC) risk and prognostic significance of CBC were evaluated. Patients and Methods In 45,229 surgically treated stage I–IIIA patients diagnosed in the Netherlands between 1989 and 2002 CBC risk was quantified using standardised incidence ratios (SIRs), cumulative incidence and Cox regression analysis, adjusted for competing risks. Results Median follow-up was 5.8 years, in which 624 CBC occurred <6 months after the index cancer (synchronous) and 1,477 thereafter (metachronous). Older age and lobular histology were associated with increased synchronous CBC risk. Standardised incidence ratio (SIR) of CBC was 2.5 (95% confidence interval (95% CI) 2.4–2.7). The SIR of metachronous CBC decreased with index cancer age, from 11.4 (95% CI 8.6–14.8) when <35 to 1.5 (95% CI 1.4–1.7) for ≥60 years. The absolute excess risk of metachronous CBC was 26.8/10,000 person-years. The cumulative incidence increased with 0.4% per year, reaching 5.9% after 15 years. Adjuvant hormonal (Hazard rate ratio (HR) 0.58; 95% CI 0.48–0.69) and chemotherapy (HR 0.73; 95% CI 0.60–0.90) were associated with a markedly decreased CBC risk. A metachronous CBC worsened survival (HR 1.44; 95% CI 1.33–1.56). Conclusion Young breast cancer patients experience high synchronous and metachronous CBC risk. Adjuvant hormonal or chemotherapy considerably reduced the risk of CBC. CBC occurrence adversely affects prognosis, emphasizing the necessity of long-term surveillance directed at early CBC-detection

Developing a Citizen Social Science approach to understand urban stress and promote wellbeing in urban communities

This paper sets out the future potential and challenges for developing an interdisciplinary, mixed-method Citizen Social Science approach to researching urban emotions. It focuses on urban stress, which is increasingly noted as a global mental health challenge facing both urbanised and rapidly urbanising societies. The paper reviews the existing use of mobile psychophysiological or biosensing within urban environments—as means of ‘capturing’ the urban geographies of emotions. Methodological reflections are included on primary research using biosensing in a study of workplace and commuter stress for university employees in Birmingham (UK) and Salzburg (Austria) for illustrative purposes. In comparing perspectives on the conceptualisation and measurement of urban stress from psychology, neuroscience and urban planning, the difficulties of defining scientific constructs within Citizen Science are discussed to set out the groundwork for fostering interdisciplinary dialogue. The novel methods, geo-located sensor technologies and data-driven approaches to researching urban stress now available to researchers pose a number of ethical, political and conceptual challenges around defining and measuring emotions, stress, human behaviour and urban space. They also raise issues of rigour, participation and social scientific interpretation. Introducing methods informed by more critical Citizen Social Science perspectives can temper overly individualised forms of data collection to establish more effective ways of addressing urban stress and promoting wellbeing in urban communities

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available