22 research outputs found
Evidence for Planet-induced Chromospheric Activity on HD 179949
We have detected the synchronous enhancement of Ca II H & K emission with the
short-period planetary orbit in HD 179949. High-resolution spectra taken on
three observing runs extending more than a year show the enhancement coincides
with phi ~ 0 (the sub-planetary point) of the 3.093-day orbit with the effect
persisting for more than 100 orbits. The synchronous enhancement is consistent
with planet-induced chromospheric heating by magnetic rather than tidal
interaction. Something which can only be confirmed by further observations.
Independent observations are needed to determine whether the stellar rotation
is sychronous with the planet's orbit. Of the five 51 Peg-type systems
monitored, HD 179949 shows the greatest chromospheric H & K activity. Three
others show significant nightly variations but the lack of any phase coherence
prevents us saying whether the activity is induced by the planet. Our two
standards, tau Ceti and the Sun, show no such nightly variations.Comment: 10 pages, 6 figures. Submitted to Ap
International longitudinal registry of patients with atrial fibrillation and treated with rivaroxaban: RIVaroxaban Evaluation in Real life setting (RIVER)
Background
Real-world data on non-vitamin K oral anticoagulants (NOACs) are essential in determining whether evidence from randomised controlled clinical trials translate into meaningful clinical benefits for patients in everyday practice. RIVER (RIVaroxaban Evaluation in Real life setting) is an ongoing international, prospective registry of patients with newly diagnosed non-valvular atrial fibrillation (NVAF) and at least one investigator-determined risk factor for stroke who received rivaroxaban as an initial treatment for the prevention of thromboembolic stroke. The aim of this paper is to describe the design of the RIVER registry and baseline characteristics of patients with newly diagnosed NVAF who received rivaroxaban as an initial treatment.
Methods and results
Between January 2014 and June 2017, RIVER investigators recruited 5072 patients at 309 centres in 17 countries. The aim was to enroll consecutive patients at sites where rivaroxaban was already routinely prescribed for stroke prevention. Each patient is being followed up prospectively for a minimum of 2-years. The registry will capture data on the rate and nature of all thromboembolic events (stroke / systemic embolism), bleeding complications, all-cause mortality and other major cardiovascular events as they occur. Data quality is assured through a combination of remote electronic monitoring and onsite monitoring (including source data verification in 10% of cases). Patients were mostly enrolled by cardiologists (n = 3776, 74.6%), by internal medicine specialists 14.2% (n = 718) and by primary care/general practice physicians 8.2% (n = 417). The mean (SD) age of the population was 69.5 (11.0) years, 44.3% were women. Mean (SD) CHADS2 score was 1.9 (1.2) and CHA2DS2-VASc scores was 3.2 (1.6). Almost all patients (98.5%) were prescribed with once daily dose of rivaroxaban, most commonly 20 mg (76.5%) and 15 mg (20.0%) as their initial treatment; 17.9% of patients received concomitant antiplatelet therapy. Most patients enrolled in RIVER met the recommended threshold for AC therapy (86.6% for 2012 ESC Guidelines, and 79.8% of patients according to 2016 ESC Guidelines).
Conclusions
The RIVER prospective registry will expand our knowledge of how rivaroxaban is prescribed in everyday practice and whether evidence from clinical trials can be translated to the broader cross-section of patients in the real world
CT Scan Screening for Lung Cancer: Risk Factors for Nodules and Malignancy in a High-Risk Urban Cohort
Low-dose computed tomography (CT) for lung cancer screening can reduce lung cancer mortality. The National Lung Screening Trial reported a 20% reduction in lung cancer mortality in high-risk smokers. However, CT scanning is extremely sensitive and detects non-calcified nodules (NCNs) in 24-50% of subjects, suggesting an unacceptably high false-positive rate. We hypothesized that by reviewing demographic, clinical and nodule characteristics, we could identify risk factors associated with the presence of nodules on screening CT, and with the probability that a NCN was malignant.We performed a longitudinal lung cancer biomarker discovery trial (NYU LCBC) that included low-dose CT-screening of high-risk individuals over 50 years of age, with more than 20 pack-year smoking histories, living in an urban setting, and with a potential for asbestos exposure. We used case-control studies to identify risk factors associated with the presence of nodules (n=625) versus no nodules (n=557), and lung cancer patients (n=30) versus benign nodules (n=128).The NYU LCBC followed 1182 study subjects prospectively over a 10-year period. We found 52% to have NCNs >4 mm on their baseline screen. Most of the nodules were stable, and 9.7% of solid and 26.2% of sub-solid nodules resolved. We diagnosed 30 lung cancers, 26 stage I. Three patients had synchronous primary lung cancers or multifocal disease. Thus, there were 33 lung cancers: 10 incident, and 23 prevalent. A sub-group of the prevalent group were stable for a prolonged period prior to diagnosis. These were all stage I at diagnosis and 12/13 were adenocarcinomas.NCNs are common among CT-screened high-risk subjects and can often be managed conservatively. Risk factors for malignancy included increasing age, size and number of nodules, reduced FEV1 and FVC, and increased pack-years smoking. A sub-group of screen-detected cancers are slow-growing and may contribute to over-diagnosis and lead-time biases
HANDLING IMPRECISION IN QUALITATIVE DATA WAREHOUSE: URBAN BUILDING SITES ANNOYANCE ANALYSIS USE CASE
Data warehouse means a decision support database allowing integration, organization, historisation, and management of data from
heterogeneous sources, with the aim of exploiting them for decision-making. Data warehouses are essentially based on
multidimensional model. This model organizes data into facts (subjects of analysis) and dimensions (axes of analysis). In classical
data warehouses, facts are composed of numerical measures and dimensions which characterize it. Dimensions are organized into
hierarchical levels of detail. Based on the navigation and aggregation mechanisms offered by OLAP (On-Line Analytical Processing)
tools, facts can be analyzed according to the desired level of detail. In real world applications, facts are not always numerical, and can
be of qualitative nature. In addition, sometimes a human expert or learned model such as a decision tree provides a qualitative
evaluation of phenomenon based on its different parameters i.e. dimensions. Conventional data warehouses are thus not adapted to
qualitative reasoning and have not the ability to deal with qualitative data. In previous work, we have proposed an original approach
of qualitative data warehouse modeling, which permits integrating qualitative measures. Based on computing with words
methodology, we have extended classical multidimensional data model to allow the aggregation and analysis of qualitative data in
OLAP environment. We have implemented this model in a Spatial Decision Support System to help managers of public spaces to
reduce annoyances and improve the quality of life of the citizens. In this paper, we will focus our study on the representation and
management of imprecision in annoyance analysis process. The main objective of this process consists in determining the least
harmful scenario of urban building sites, particularly in dense urban environments