Use of cam, particularly biologic products, increased significantly after a cancer diagnosis. Further studies are required to examine the effect of cam use on the efficacy and safety of cancer therapies.
Background:Access to palliative care has been associated with improving quality of life and reducing the use of potentially aggressive end-of-life care. However, many challenges and barriers exist in providing palliative care to residents in northern and rural settings in Ontario, Canada.Aim:The purpose of this study was to examine access to palliative care and associations with the use of end-of-life care in a decedent cohort of northern and southern, rural and urban, residents.Design:Using linked administrative databases, residents were classified into geographic and rural categories. Regression methods were used to define use and associations of palliative and end-of-life care and death in acute care hospital.Setting/Participants:A decedent cancer cohort of Ontario residents (2007-2012).Results:Northern rural residents were less likely to receive palliative care (adjusted odds ratio [OR] = 0.90, 95% confidence interval [CI]: 0.83-0.97). Those not receiving palliative care were more likely to receive potentially aggressive end-of-life care and die in an acute care hospital (adjusted OR = 1.20, 95% CI: 1.02-1.41).Conclusions:Palliative care was significantly associated with reduced use of aggressive end-of-life care; however, disparities exist in rural locations, especially those in the north. Higher usage of emergency department (ED) and hospital resources at end of life in rural locations also reflects differing roles of rural community hospitals compared with urban hospitals. Improving access to palliative care in rural and northern locations is an important care issue and may reduce use of potentially aggressive end-of-life care.
A nonlinear autoregressive approach with exogenous input is used as a novel method for statistical forecasting of the disturbance storm time index, a measure of space weather related to the ring current which surrounds the Earth, and fluctuations in disturbance storm time field strength as a result of incoming solar particles. This ring current produces a magnetic field which opposes the planetary geomagnetic field. Given the occurrence of solar activity hours or days before subsequent geomagnetic fluctuations and the potential effects that geomagnetic storms have on terrestrial systems, it would be useful to be able to predict geophysical parameters in advance using both historical disturbance storm time indices and external input of solar winds and the interplanetary magnetic field. By assessing various statistical techniques it is determined that artificial neural networks may be ideal for the prediction of disturbance storm time index values which may in turn be used to forecast geomagnetic storms. Furthermore, it is found that a Bayesian regularization neural network algorithm may be the most accurate model compared to both other forms of artificial neural network used and the linear models employing regression analyses.
Increasing research into heliobiology and related fields has revealed a myriad of potential relationships between space weather factors and terrestrial biology. Additionally, many studies have indicated cyclicity in incidence of various diseases along with many aspects of cardiovascular function. The current study examined annual mortality associated with hypertensive diseases in Canada from 1979 to 2009 for periodicities and linear relationships with a range of heliophysical parameters. Analyses indicated a number of significant lagged correlations between space weather and hypertensive mortality, with solar wind plasma beta identified as the likely source of these relationships. Similar periodicities were observed for geomagnetic activity and hypertensive mortality. A significant rhythm was revealed for hypertensive mortality centered on a 9.6-year cycle length, while geomagnetic activity was fit with a 10.1-year cycle. Cross-correlograms of mortality with space weather demonstrated a 10.67-year periodicity coinciding with the average 10.6-year solar cycle length for the time period examined. Further quantification and potential implications are discussed.
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