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New EPI Healthcare Study By June O'Neill Shows Uninsured 'Crisis' Wildly Overestimated
The Employment Policies Institute (EPI) released a new study which shows that the widely employed estimate of 47 million uninsured Americans is a misleading representation of the problem. The study, authored by Drs. June and David O"Neill of Baruch College and City University of New York, shows that more than 43 percent, or 18 million, of uninsured Americans ages 18-64 could likely afford health coverage and are actually "voluntarily uninsured." June O"Neill served as Director of the Congressional Budget Office (CBO) from 1995-1999.
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New York Times Examines Trend Of Posting Childbirth Videos On YouTube
The New York Times on Thursday examined how thousands of women have posted videos on YouTube showing themselves giving birth. According to the Times, the women believe the videos help "demystify" childbirth by candidly presenting the process in a manner that pregnant women and their partners otherwise might not see. Along with YouTube, Web sites like Internet chat rooms and pregnancy blogs are helping to shift dynamics between pregnant women and their care providers, the Times reports. Eileen Ehudin Beard, an adviser for the American College of Nurse-Midwives, said, "The more information you have, the more s you have, the more informed you are, the better questions you ask." However, she added that the videos could have negative effects, particularly if they make women more fearful of childbirth. The childbirth videos are relatively controversial because of their graphic nature, which has challenged some of YouTube"s rules and raised issues of propriety. Victoria Grand, the head of policy for YouTube, said that nudity generally is banned from YouTube but that the site "make[s] exceptions for videos that are educational, documentary or scientific." Most childbirth videos on YouTube are age restricted to ages 18 and older. A majority of them show home births because most U.S. hospitals prohibit patients from recording births due to liability concerns, the Times reports. Although childbirth education classes have shown edited videos of births since the 1970s, the Internet and YouTube could change the way such classes are taught, according to Jeanette Schwartz, president of the International Childbirth Education Association. She noted that most videos currently used in childbirth classes are heavily edited and out of date, adding that the YouTube videos "create a wonderful opportunity to show free, real life, candid videos in a classroom setting." Eugene Declercq, a professor at the Boston University School of Public Health, said, "A hundred and fifty years ago, women viewed birth on a pretty regular basis -- they saw their sisters of neighbors give birth." He said that changed with a trend toward hospital births beginning in the late 19th century. "But now, with YouTube, we"ve come back around and women have this opportunity to view births again," Declercq said (Wollan, New York Times, 6/11).
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Xenophon Attacks South Australian Aged Care Nurses
Australian Nursing Federation (ANF) Federal Secretary Ged Kearney said comments made by Senator Nick Xenophon today display a lack of understanding of the award modernisation process and the benefits this process brings to nursing staff, employers and the aged care industry.
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Optimizing Molecular Signatures For Predicting Prostate Cancer Recurrence

UroToday.com - The mortality rate for prostate cancer is declining due to improvements in earlier detection and in local therapy strategies, however, the ability to predict the metastatic behavior of a patient"s cancer, as well as to detect and eradicate disease recurrence remains some of the greatest clinical challenges in oncology. It is estimated that 25-40% of men undergoing radical prostatectomy will have disease relapse, often termed a biochemical recurrence as the first clinical indication a rising serum level of prostate specific antigen (PSA). The accurate identification of patients at risk for relapse would greatly facilitate the rational application of adjuvant treatment strategies. The advent of microarray gene expression technology has greatly enabled the search for predictive disease biomarkers. Numerous exploratory studies have demonstrated the potential value of gene expression signatures in assessing the risk of post-surgical disease recurrence beyond the current clinical systems. However, existing molecular predictive models were derived using relatively simple computational algorithms, and the critical issue of whether proposed gene signatures are ready for randomized, prospective clinical validation trials is still under debate in the oncology community. Key to resolving this issue is the development of advanced algorithms that are capable of identifying relevant genes (features in bioinformatic terms) in a background of tens of thousands of genes, and on the basis of a limited number of patient tissue samples. This process is known as feature selection, and achieving this in high-dimensional data remains a major challenge in bioinformatics and machine learning. In order to overcome current restraints, we have derived a feature selection algorithm that addresses several major issues with prior work including computational efficiency and solution accuracy. We have experimentally demonstrated that our algorithm is capable of handling problems with extremely large input data dimensionality, to a point far beyond that needed for gene expression data analysis of genetically complex organisms. In the study published in The Prostate journal, we conducted a computational analysis to investigate whether the application of our computational algorithm can lead to the derivation of more accurate prognostic molecular signatures for predicting prostate cancer recurrence. To this end, we used a rigorous experimental protocol to compare the prognostic performance of newly identified genetic signatures with those previously derived. Receiver operator characteristic (ROC) curves and survival data analyses demonstrate the superior performance of the new gene signature over previous work. We further derived a hybrid prognostic signature, obtained by integrating gene expression data and clinical variables, that significantly outperformed both the gene signature and the predictive nomogram. Our results demonstrate that advanced computational modeling can significantly improve the accuracy of molecular prognostic signatures for prostate cancer. Written by Steve Goodison, MD as part of Beyond the Abstract on UroToday.com UroToday - the only urology website with original content written by global urology key opinion leaders actively engaged in clinical practice. To access the latest urology news releases from UroToday, go to: www.urotoday.com Copyright © 2009 - UroToday Copyright: Medical News Today Not to be reproduced without permission of Medical News Today


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