Monthly Archives: May 2017

Heart disease designed by new digital instrument

“Exercise reduces cardiovascular risk, improves body composition and physical fitness, and lowers mortality and morbidity,” said lead author Professor Dominique Hansen, associate professor in exercise physiology and rehabilitation of internal diseases at Hasselt University, Diepenbeek, Belgium. “But surveys have shown that many clinicians experience great difficulties in prescribing specific exercise programmes for patients with multiple cardiovascular diseases and risk factors.”

The European Association of Preventive Cardiology Exercise Prescription in Everyday Practice and Rehabilitative Training (EXPERT) tool generates exercise prescriptions for patients with different combinations of cardiovascular risk factors or cardiovascular diseases. The tool was designed by cardiovascular rehabilitation specialists from 11 European countries, in close collaboration with computer scientists from Hasselt University.

EXPERT can be installed on a laptop or personal computer (PC). During a consultation, the clinician inputs the patient’s characteristics and cardiovascular risk factors, cardiovascular diseases and other chronic conditions, medications, adverse events during exercise testing, and physical fitness (from a cardiopulmonary exercise test).

The tool automatically designs a personalized exercise programme for the patient. It includes the ideal exercise type, intensity, frequency, and duration of each session. Safety precautions are also given for patients with certain conditions. The advice can be printed out and given to the patient to carry out at home, and reviewed by the clinician in a few months.

Professor Hansen said: “EXPERT generates an exercise prescription and safety precautions since certain patients are not allowed to do certain exercises. For example a diabetic patient with retinopathy should not do high-intensity exercise.”

“This tool is the first of its kind,” said Professor Hansen. “It integrates all the international recommendations on exercise to calculate the optimum training programme for an individual patient. It really is personalized medicine.”

There are different exercise goals for each cardiovascular risk factor and cardiovascular disease. In a patient who has diabetes, is overweight and has hypertension the three goals are to reduce blood glucose, fat mass, and blood pressure. The tool takes all three goals into account.

Professor Hansen said: “EXPERT provides the exercise prescription a patient needs to meet their particular exercise goals, which should ultimately help them to feel better and reduce their risks of morbidity and mortality. By prescribing an exercise programme that really works patients are more likely to be motivated to continue because they see that it is improving their health.”

The next step is to test the impact of EXPERT on patient outcomes in a clinical trial. Professor Hansen said: “Our hypothesis is that clinicians using the tool will prescribe exercise interventions with much greater clinical benefits. That will lead to greater reductions in body weight, blood pressure, blood glucose, and lipids, and improvements in physical fitness, with a positive impact on morbidity and mortality.”

A study comparing acceptance rates

“There are a number of questions and concerns related to gender bias in computer programming, but this project was focused on one specific research question: To what extent does gender bias exist when pull requests are judged on GitHub?” says Emerson Murphy-Hill, corresponding author of a paper on the study and an associate professor of computer science at North Carolina State University.

GitHub is an online programming community that fosters collaboration on open-source software projects. When people identify ways to improve code on a given project, they submit a “pull request.” Those pull requests are then approved or denied by “insiders,” the programmers who are responsible for overseeing the project.

For this study, researchers looked at more than 3 million pull requests from approximately 330,000 GitHub users, of whom about 21,000 were women.

The researchers found that 78.7 percent of women’s pull requests were accepted, compared to 74.6 percent for men.

However, when looking at pull requests by people who were not insiders on the relevant project, the results got more complicated.

Programmers who could easily be identified as women based on their names or profile pictures had lower pull request acceptance rates (58 percent) than users who could be identified as men (61 percent). But woman programmers who had gender neutral profiles had higher acceptance rates (70 percent) than any other group, including men with gender neutral profiles (65 percent).

“Our results indicate that gender bias does exist in open-source programming,” Murphy-Hill says. “The study also tells us that, in general, women on GitHub are strong programmers. We don’t think that’s because gender affects one’s programming skills, but likely stems from strong self-selection among women who submit pull requests on the site.

“We also want to note that this paper builds on a previous, un-peer-reviewed version of the paper, which garnered a lot of input that improved the research,” Murphy-Hill says.

The paper, “Gender Differences and Bias in Open Source: Pull Request Acceptance of Women Versus Men,” is published in the open-access journal PeerJ Computer Science. The paper was co-authored by Josh Terrell, a former undergraduate at Cal Poly; Andrew Kofink, a former undergraduate at NC State; Justin Middleton, a Ph.D. student at NC State; Clarissa Rainear, an undergraduate at NC State; Chris Parnin, an assistant professor of computer science at NC State; and Jon Stallings, an assistant professor of statistics at NC State. The work was done with support from the National Science Foundation under grant number 1252995.