Human Medicine

Testing shortages, long waits for results, and an over-taxed health care system have made headlines throughout the COVID-19 pandemic. These issues can be further exacerbated in small or rural communities in the US and globally. Additionally, respiratory symptoms of COVID-19 such as fever and cough are also associated with the flu, which complicates non-lab diagnoses during certain seasons. A new study by College of Health and Human Services researchers is designed to help identify which symptoms are more likely to indicate COVID during flu season. This is the first study to take seasonality into account.

Farrokh Alemi, principal investigator and professor of Health Administration and Policy, and other Mason researchers predict the probability that a patient has COVID-19, flu, or another respiratory illness prior to testing, depending on the season. This can help clinicians triage patients who are most suspected of having COVID-19.

“When access to reliable COVID testing is limited or test results are delayed, clinicians, especially those who are community-based, are more likely to rely on signs and symptoms than on laboratory findings to diagnose COVID-19,” said Alemi, who observed these challenges at points throughout the pandemic. “Our algorithm can help health care providers triage patient care while they are waiting on lab testing or help prioritize testing if there are testing shortages.”

The findings suggest that community-based health care providers should follow different signs and symptoms for diagnosing COVID depending on the time of year. Outside of flu season, fever is an even stronger predictor of COVID than during flu season. During flu season, a person with a cough is more likely to have the flu than COVID. The study showed that assuming anyone with a fever during flu season has COVID would be incorrect. The algorithm relied on different symptoms for patients in different age and gender. The study also showed that symptom clusters are more important in diagnosis of COVID-19 than symptoms alone.

The algorithms were created by analyzing the symptoms reported by 774 COVID patients in China and 273 COVID patients in the United States. The analysis also included 2,885 influenza and 884 influenza-like illnesses in US patients. “Modeling the Probability of COVID-19 Based on Symptom Screening and Prevalence of Influenza and Influenza-Like Illnesses” was published in Quality Management in Health Care’s April/June 2022 issue. The rest of the research team is also from Mason: Professor of Global Health and Epidemiology Health Amira Roess, Affiliate Faculty Jee Vang, and doctoral candidate Elina Guralnik.

Though helpful, the algorithms are too complex to expect clinicians to perform these calculations while providing care. The next step is to create an AI, web-based, calculator that can be used in the field. This would allow clinicians to arrive at a presumed diagnosis prior to the visit.”

Farrokh Alemi, Principal Investigator and Professor of Health Administration and Policy

From there, clinicians can make triage decisions on how to care for the patient while waiting for official lab results.

The study does not include any COVID-19 patients without respiratory symptoms, which includes asymptomatic people. Additionally, the study did not differentiate between the first and second week of onset of symptoms, which can vary.

This research was a prototype of how existing data can be used to find signature symptoms of a new disease. The methodology may have relevance beyond this pandemic.

“When there is a new outbreak, collecting data is time consuming. Rapid analysis of existing data can reduce the time to differentiate presentation of new diseases from illnesses with overlapping symptoms. The method in this paper is useful for rapid response to the next pandemic,” said Alemi.

A team led by the Zhu Family Center for Global Cancer Prevention at Harvard T.H. Chan School of Public Health and the Center for Cancer Equity and Engagement at the Dana-Farber/Harvard Cancer Center has launched Cancer FactFinder (https://cancerfactfinder.org/), a new website that provides accurate and reliable information about what does and does not cause cancer. For each topic on the website, the team, which includes scientific experts and community members, reviewed and summarized the best scientific, evidence-based information available. The team will continuously update website with new topics and additional information to existing topics.

For each of the more than 60 topics on the website, such as “Red Meat,” “Stress,” “Hormone Replacement Therapy,” or “Radon,” the summary provides information about:

• What you may have heard
• What science tells us
• How to reduce your risk
• What this means to me
• Sources and links for more information

Each claim about a topic, such as “Red meat causes cancer,” also comes with an interpretation of the team’s findings about a claim’s veracity:

• Most likely or definitely true: There is sufficient evidence to suggest that the claim is true.
• False—misinformation: There is sufficient evidence to suggest that the claim is false.
• We’re not sure yet—scientists are still working on it: There is not sufficient evidence to say whether the claim is or isn’t true.

“There is a lot of misinformation and confusion in social media and through word of mouth about what causes cancer. Being able to access accurate information about cancer causes can help people make health and lifestyle choices that minimize their future cancer risk,” said Timothy Rebbeck, Vincent L. Gregory, Jr. Professor of Cancer Prevention and director of the Zhu Family Center at Harvard Chan School and professor of medical oncology at Dana-Farber Cancer Institute.

In addition to Harvard Chan School and the Dana-Farber/Harvard Cancer Center, the Cancer FactFinder team includes community advocates and experts from BayState Health, Boston Cancer Support, Boston University, Men of Color Health Awareness, Silent Spring Institute, and Yale University.

Higher unemployment insurance benefits not only lower the likelihood that an unemployed person will become self-employed, but it also extends the length of time before they transition to self-employment, according to new research published in the Strategic Entrepreneurship Journal.

Author Wenjian Xu, an assistant professor in finance at Shanghai Jiao Tong University, used information from the U.S. Department of Labor on each state’s maximum weekly UI benefits, and surveyed states’ labor departments to understand policy details about how starting a new business would affect UI eligibility.

The research also showed that the negative effects of UI benefits -; especially generous benefits -; are concentrated on the formation of unincorporated businesses. “This result is a little surprising at first glance, as we would have thought that higher unemployment benefits might offer support to those people who try to start their own business, leading to more new businesses,” Xu says. However, most states require business profits to be deducted from unemployment benefits, which disincentives the creation of new businesses. Plus, he says, higher benefits usually discourage people from transitioning out of unemployment.

Yet the study found that unincorporated businesses that are created by unemployed people in higher-benefit state-periods tend to be more successful, as measured by profit and survival rate. It suggests that higher benefits act as a screening device that deters the creation of lower-quality businesses.

The negative effects that Xu identified in his study were particularly high during recession periods, as this is when entrepreneurs are pessimistic about future profits. “Since the disincentive effect resulting from the profit deduction requirement mainly concentrates on businesses with smaller profits, the effect will be larger when there are more businesses that expect to make smaller profits,” he says. In fact, Xu’s empirical results found that the negative effect of UI benefits on the transition from unemployment to entrepreneurship during recessions is three times as large as during non-recession periods.

From a policy perspective, the research shows that removing the profit deduction requirement from the UI system would mitigate the negative effects and encourage more unemployed entrepreneurs to experiment and explore business creation, which Xu says could foster a vibrant local economic environment. Self-employment assistance (SEA) programs aim to achieve this incentive, as they allow unemployed people to start businesses without any profit deduction and they waive the job search requirement.

As of 2016, only eight states had this program, Xu found, and the ratio of unemployed people joining this program in these states was small because of restrictive conditions. To foster more entrepreneurship and create jobs, Xu’s study suggests that policymakers should adopt the SEA program and relax the conditions to cover more unemployed people -; especially during recessions, when the disincentive effect of UI benefits is larger on would-be entrepreneurs, and when it is more difficult to find a new job.

During the COVID-19 pandemic, the share of new entrepreneurs who were initially unemployed reached the highest level (30%) recorded in 25 years. Hence, it becomes urgent and important for policymakers to remove obstacles and smooth such a transition.”

Wenjian Xu, assistant professor in finance, Shanghai Jiao Tong University

Apr 1 2022

Obese mice that were fed a high-fat diet and that received prednisone one time per week had improved exercise endurance, got stronger, increased their lean body mass and lost weight, reports a new Northwestern Medicine study published in The Journal of Experimental Medicine.

The once-weekly prednisone promoted nutrient uptake into the muscles, and the mice also had increased muscle metabolism.

Investigators also found these mice had increased adiponectin levels, a fat-derived hormone that appears to play an important role in protecting against diabetes and insulin resistance.

The scientists also showed mice that were already obese from eating a high-fat diet also had benefit after once-weekly prednisone, experiencing increased strength, running capacity and lower blood glucose.

These studies were done in mice. However, if these same pathways hold true in humans, then once-weekly prednisone could benefit obesity.”

Elizabeth McNally, MD, PhD, senior author, the Elizabeth J. Ward Professor of Genetic Medicine and director of the Center for Genetic Medicine

McNally is also a Northwestern Medicine physician a professor of Medicine in the Division of Cardiology and of Biochemistry and Molecular Genetics.

“Daily prednisone is known to promote obesity and even metabolic syndrome — a disorder with elevated blood lipids and blood sugar and weight gain,” McNally said. “So, these results, in which we intermittently ‘pulse’ the animals with once-weekly prednisone, are strikingly different. Obesity is a major problem, and the idea that once-weekly prednisone could promote nutrient uptake into muscle might be an approach to treating obesity.”

Most of what we know about steroids like prednisone come from studies looking at what happens when prednisone, a glucocorticoid steroid, is taken every day.

“We see a very different outcome when it is taken once a week,” McNally said. “We need to fine tune dosing to figure out the right amount to make this work in humans, but knowing adiponectin might be one marker could provide a hint at determining what the right human dose is.”

McNally described the weekly dose as “a bolus, or spike, of nutrients going into your muscle.”

“We think there is something special about promoting this spike of nutrients into muscle intermittently, and that it may be an efficient way to improve lean body mass,” she added.

“What is exciting to me about this work is the finding that a simple change in the dosing frequency can transform glucocorticoid drugs from inducers to preventers of obesity,” said corresponding author Mattia Quattrocelli, PhD. “Chronic once-daily intake of these drugs is known to promote obesity. Here we show that dosing the same type of drug intermittently — in this case, once weekly — reverses this effect, promotes muscle metabolism and energy expenditure, and curtails the metabolic stress induced by a fat-rich diet.”

Quattrocelli, who initiated the research while at Northwestern, is now assistant professor at Cincinnati Children’s Hospital Medical Center and department of pediatrics at the University of Cincinnati.

Can weekly dose still benefit patients with immune conditions?

Many patients take prednisone daily for different immune conditions. Known side effects of daily prednisone include weight gain and even muscle atrophy with weakness. Investigators want to determine whether patients can get the same immune benefit with intermittent prednisone dosing, which could be much more beneficial to the muscle.

Research began in muscular dystrophy

In previously published research, McNally’s team discovered giving prednisone intermittently was helpful for muscular dystrophy, showing once weekly prednisone improved strength.

The group also recently reported findings from a pilot trial in humans with muscular dystrophy in which one weekly dose of prednisone improved lean mass.

Not one-size-fits-all for prednisone dosing

People have different responses to prednisone dosing.

McNally wants to determine which biomarkers are most critical to mark having a beneficial response to prednisone.

“If we can determine how to choose the right dose of prednisone that minimizes atrophy factors and maximizes positive markers like adiponectin, then we can really personalize the dosing of prednisone,” she said.

The group also recently showed that weekly prednisone uses strikingly different molecular pathways to strengthen the muscle in male versus female mice, based on a new study just published in the Journal of Clinical Investigation by Isabella Salamone, a graduate student in McNally’s lab.

The circadian connection

The benefits of weekly prednisone are linked to circadian rhythms, according to another new study from Northwestern and University of Cincinnati published last month in Science Advances.

Human cortisol and steroid levels spike early in the morning before you wake up.

“If you don’t give the drug at the right time of day, you don’t get the response,” Quattrocelli said. “In mice, we obtained good effects with intermittent prednisone in muscle mass and function when we dose them at the beginning of their daytime. Mice have a circadian rhythm inverted to us, as they generally sleep during the daytime and are active at night. This could mean that the optimal dosing time for humans during the day could be in the late afternoon/early evening, but this needs to be appropriately tested.”

Do stronger, leaner mice equal stronger, leaner humans?

The major caveat is that these studies are conducted in mice, McNally said.

“While we are encouraged by the pilot study in humans with muscular dystrophy, mouse muscles have more fast-twitch fibers than humans, and slow-twitch muscle could be different,” McNally said. “More studies are needed to try to better understand whether these same mechanisms work in human muscles.”