Posted on Patient Talk

A visit to ‘Dr. Google’ makes patients better at diagnosis

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Medical professionals often advise patients not to search the Internet for their symptoms before coming into the clinic, yet many people turn to “Dr. Google” when feeling sick. Concerns about “cyberchondria” — or increased anxiety induced by the Internet — have made the value of using Internet searches controversial. In a new study that used case vignettes, researchers from Brigham and Women’s Hospital and Harvard Medical School Department of Health Care Policy explored the impact Internet searches have on patients’ abilities to reach a correct diagnosis. They found that study outcomes suggest the Internet may not be so harmful after all. Participants across the board demonstrated modest improvements in reaching an accurate diagnosis after looking up symptoms on the Internet. Participants additionally showed no difference in reported anxiety nor in triage abilities. Results are published in JAMA Network Open.

“I have patients all the time, where the only reason they come into my office is because they Googled something and the Internet said they have cancer. I wondered, ‘Is this all patients? How much cyberchondria is the Internet creating?'” said corresponding author David Levine, MD, MPH, of the Division of General Internal Medicine & Primary Care at the Brigham.

In a study of 5,000 participants, each person was asked to read a short case vignette describing a series of symptoms and imagine someone close to them was experiencing the described symptoms. Participants were asked to provide a diagnosis based on the given information then look up their case symptoms on the Internet and again offer a diagnosis. Cases ranged from mild to severe, but described illnesses that commonly affect everyday people, such as viruses, heart attacks and strokes. In addition to diagnosing a given condition, participants each selected a triage level, ranging from “let the health issue get better on its own” to “call 911.” Study members then recorded their individual anxiety levels.

Notably, Levine and co-author Ateev Mehrota, MD, MPH, a hospitalist at Harvard Medical School, found that people were slightly better at diagnosing their cases correctly after performing an Internet search. Participants demonstrated no difference in their abilities to triage nor did they report a change in anxiety after using the Internet.

“Our work suggests that it is likely OK to tell our patients to ‘Google it,'” said Levine. “This starts to form the evidence base that there’s not a lot of harm in that, and, in fact, there may be some good.”

Authors note that a limitation to this study is that participants were asked to pretend as if a loved one was having the symptoms described by the case vignette. It isn’t completely clear that people would behave the same way upon experiencing symptoms themselves. Additionally, the authors note that this study is not representative of all people that use the Internet for health-related searches.

Levine also plans to expand the scope of this study by investigating the ability of artificial intelligence (AI) to use the Internet to correctly diagnose patients.

“This next study takes a generalized AI algorithm, trained on all of the open-source text of the Internet such as Reddit and Twitter, and then uses that to respond when prompted,” said Levine. “Can AI supplement how people use the Internet? Can it supplement how doctors use the Internet? That’s what we’re interested in investigating.”

Posted on Rheumatoid arthritis

Inflammation-fighting protein could improve treatment of rheumatoid arthritis

Study authors Mahamudul Haque, Salah-Uddin Ahmed, and Anil K. Singh look at a protein array in their lab at the WSU Health Sciences Spokane campus. CREDIT Photo by Cori Kogan, Washington State University Health Sciences Spokane

New research led by scientists at Washington State University has found that a protein known as GBP5 appears to play a key role in suppressing inflammation in rheumatoid arthritis, a potentially debilitating disease in which the immune system mistakenly attacks the body’s own joint tissues.

Published in the journal Arthritis & Rheumatology, the discovery could someday lead to new treatments to slow or halt the progress of the disease, which affects an estimated 1.5 million Americans. The researchers said it may also have applications in other inflammatory diseases.

First author Mahamudul Haque first stumbled upon GBP5 back in 2015, when he was working toward a Ph.D. in pharmaceutical sciences in WSU’s College of Pharmacy and Pharmaceutical Sciences. Now a postdoctoral research associate in the WSU Elson S. Floyd College of Medicine, Haque had been tasked with comparing the expression of different genes in joint tissue from rheumatoid arthritis patients and non-diseased joint tissue. Among the thousands of genes included in his analysis, one gene stood out in particular because its expression level was several times greater in rheumatoid arthritis tissue. That gene was guanylate binding protein 5 (GBP5), which helps produce the GBP5 protein.

“That caught our attention and interest,” said senior author Salah-Uddin Ahmed, a professor in the College of Pharmacy and Pharmaceutical Sciences who oversaw the work.

As far as Ahmed and Haque could tell, no other studies had looked at the role of GBP5 in rheumatoid arthritis or other auto-immune diseases, so they decided to take on the task.

The inflammation seen in rheumatoid arthritis causes painful swelling of joint tissues that can result in bone loss and deformed joints. Previous research conducted by Ahmed and his team has suggested that this inflammation is driven primarily by a cytokine protein known as interleukin-1 beta (IL-1 beta). To find out what role GBP5 plays, the researchers designed a series of experiments using rheumatoid arthritis synovial fibroblasts, a type of cell located in the tissue that lines joints and is known to play a role in inflammation and joint destruction. When they manipulated the cells to stop producing GBP5 and then added IL-1 beta to induce inflammation, they saw much higher levels of inflammation in cells that lacked GBP5 versus in non-manipulated cells. What’s more, when they increased levels of GBP5 in those same cells, inflammation triggered by IL-1 beta went down.

“Our initial thought had been that the GBP5 protein played a role in causing the disease, but as we worked to decipher the mechanism of GBP5 in rheumatoid arthritis we found that it was induced in response to inflammation and was trying to cut back inflammation before it goes out of control,” Ahmed said.

In addition, their research revealed how GBP5 interacts with interferon gamma, another cytokine that has been shown to fight inflammation under certain circumstances. When they silenced the GBP5 gene, the researchers found that it reduced interferon gamma’s ability to fight the inflammation triggered by IL-1 beta. This suggests that, on top of having its own anti-inflammatory effect, GBP5 also supports the anti-inflammatory function of interferon gamma.

Finally, the researchers confirmed their findings in a rodent model of rheumatoid arthritis, which showed that joint inflammation and bone loss increased when the GBP5 gene was turned off.

Ahmed said he and his team are conducting additional research to confirm that their findings hold up in other pre-clinical models of rheumatoid arthritis. Pending further, clinical studies to test this concept in rheumatoid arthritis patients at different stages of the disease, Ahmed said their findings could someday lead to the development of new combination therapies that could boost GBP5 levels to reduce inflammation and bone loss.

“What we would like to understand is, if we introduced this protein very early during the onset of rheumatoid arthritis, could we reverse or suppress the course of the disease?” Ahmed said.

Haque also suggested that researchers should take a closer look at the role of GBP5 in other conditions that involve inflammation. This includes other types of arthritis, such as gout and osteoarthritis.

Posted on Multiple Sclerosis

Machine learning helps spot gait problems in individuals with multiple sclerosis

Researchers Manuel Hernandez, left, Rachneet Kaur and Richard Sowers have developed a machine-learning algorithm that could help doctors spot gait problems in people with multiple sclerosis and determine if they are a result of the disease or healthy aging. CREDIT Photo by L. Brian Stauffer

 Monitoring the progression of multiple sclerosis-related gait issues can be challenging in adults over 50 years old, requiring a clinician to differentiate between problems related to MS and other age-related issues. To address this problem, researchers are integrating gait data and machine learning to advance the tools used to monitor and predict disease progression.

A new study of this approach led by University of Illinois Urbana Champaign graduate student Rachneet Kaur, kinesiology and community health professor Manuel Hernandez and industrial and enterprise engineering and mathematics professor Richard Sowers is published in the journal Institute of Electrical and Electronics Engineers Transactions on Biomedical Engineering.

Multiple sclerosis can present itself in many ways in the approximately 2 million people that it affects globally, and walking problems are a common symptom. About half of the patients need walking assistance within 15 years of onset, the study reports.

“We wanted to get a sense of the interactions between aging and concurrent MS disease-related changes, and whether we can also differentiate between the two in older adults with MS,” Hernandez said. “Machine-learning techniques seem to work particularly well at spotting complex hidden changes in performance. We hypothesized that these analysis techniques might also be useful in predicting sudden gait changes in persons with MS.”

Using an instrumented treadmill, the team collected gait data – normalized for body size and demographics – from 20 adults with MS and 20 age-, weight-, height- and gender-matched older adults without MS. The participants walked at a comfortable pace for up to 75 seconds while specialized software captured gait events, corresponding ground reaction forces and center-of-pressure positions during each walk. The team extracted each participant’s characteristic spatial, temporal and kinetic features in their strides to examine variations in gait during each trial.

Changes in various gait features, including a data feature called the butterfly diagram, helped the team detect differences in gait patterns between participants. The diagram gains its name from the butterfly-shaped curve created from the repeated center-of-pressure trajectory for multiple continuous strides during a subject’s walk and is associated with critical neurological functions, the study reports.

Click here to see a video describing this research.

“We study the effectiveness of a gait dynamics-based machine-learning framework to classify strides of older persons with MS from healthy controls to generalize across different walking tasks and over new subjects,” Kaur said. “This proposed methodology is an advancement toward developing an assessment marker for medical professionals to predict older people with MS who are likely to have a worsening of symptoms in the near term.”

Future studies can provide more thorough examinations to manage the study’s small cohort size, Sowers said.

“Biomechanical systems, such as walking, are poorly modeled systems, making it difficult to spot problems in a clinical setting,” Sowers said. “In this study, we are trying to extract conclusions from data sets that include many measurements of each individual, but a small number of individuals. The results of this study make significant headway in the area of clinical machine learning-based disease-prediction strategies.”

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Posted on Autism

Maternal exposure to chemicals linked to autistic-like behaviours in children

Grandparents may be first to spot autism in a child


A new study by Simon Fraser University’s Faculty of Health Sciences researchers – published today in the American Journal of Epidemiology – found correlations between increased expressions of autistic-like behaviours in pre-school aged children to gestational exposure to select environmental toxicants, including metals, pesticides, polychlorinated biphenyls (PCBs), phthalates, and bisphenol-A (BPA).

This population study measured the levels of 25 chemicals in blood and urine samples collected from 1,861 Canadian women during the first trimester of pregnancy. A follow up survey was conducted with 478 participants, using the Social Responsiveness Scale (SRS) tool for assessing autistic-like behaviours in pre- school children.

The researchers found that higher maternal concentrations of cadmium, lead, and some phthalates in blood or urine samples was associated with increased SRS scores, and these associations were particularly strong among children with a higher degree of autistic-like behaviours. Interestingly, the study also noted that increased maternal concentrations of manganese, trans-Nonachlor, many organophosphate pesticide metabolites, and mono-ethyl phthalate (MEP) were most strongly associated with lower SRS scores.

The study’s lead author, Josh Alampi, notes that this study primarily “highlights the relationships between select environmental toxicants and increased SRS scores. Further studies are needed to fully assess the links and impacts of these environmental chemicals on brain development during pregnancy.”

The results were achieved by using a statistical analysis tool, called Bayesian quantile regression, that allowed investigators to determine which individual toxicants were associated with increased SRS scores in a more nuanced way than conventional methods.

“The relationships we discovered between these toxicants and SRS scores would not have been detected through the use of a means-based method of statistical analysis (such as linear regression),” noted Alampi. “Although quantile regression is not frequently used by investigators, it can be a powerful way to analyze complex population-based data.”

Posted on Autism

New research finds majority of autistic children may be ‘doing well’

Siblings and autism

One of the biggest longitudinal research studies of its kind in the world led by The Hospital for Sick Children (SickKids) and the Centre for Addiction and Mental Health (CAMH) suggests that positive outcomes for children with autism are more common than previously thought.

Autism refers to a group of neurodevelopmental conditions resulting in challenges related to communication, social understanding and behaviour. One in 100 people may have ASD and although a person can be diagnosed at any time, autism symptoms generally appear and are diagnosed in the first few years of life.

The multi-site study, published in JAMA Open on March 29, applied a strengths-based approach to outcome assessments in children with an autism diagnosis, measuring participants’ proficiency (level of competency) and growth (improvement over time) in five key developmental health areas: communication, socialization, activities of daily living and emotional health (internalizing and externalizing).

The study found that 80 per cent of children experienced growth or proficiency in at least one of the five domains and 23 per cent of children were doing well in four or more of the domains by mid childhood. Core to the study approach was shifting the definition of a ‘good outcome’ to ‘doing well’.

“It was encouraging to find that most autistic children were doing well by 10 years old by some measure. By using different criteria to track their development apart from those used to diagnose autism — such as autism signs and cognitive ability — we were able to reframe more holistically how we conceptualized progress in the autism field,” says co-author Dr. Peter Szatmari, Psychiatrist in Chief, Department of Psychiatry and Senior Scientist, Neurosciences & Mental Health at SickKids, and Chief of the Child and Youth Mental Health Collaborative between SickKids, CAMH and the University of Toronto.

“Specifying an outcome implies that there’s an end point, whereas doing well relates to an individual’s circumstances at a particular point in their life’s journey with autism — especially important since these kids are just at the start of a journey.”

Strengths-based approach provides more holistic view of “doing well”

Historically, research literature and outcome evaluations have focused on the deficits autistic peopple may experience in intellectual or skills development and less has been studied in the Canadian paediatric context.

The researchers followed 272 children diagnosed with autism from clinics across Canada from the ages of 2 to 10 years old, or mid childhood, a notable age as children transition to greater autonomy and increased social and academic demands.

Unique to the approach was the use of growth as a measurement, which allowed for comparison of whether an individual child improved in a domain against their younger selves.

“Changing the narrative away from a deficit-based system to one that recognizes growth and success can serve as a foundation for building up each unique child as they tackle new skills and developmental stages in life,” says Dr. Katherine Cost, co-author of the paper and Research Associate in the Department of Psychiatry at SickKids.

Family context may attribute to positive outcomes

The study also examined contextual factors such as household income, parent coping and family functioning (such as positive communication and support among family members).

The findings indicated that higher household income and better family functioning were important predictors in several aspects of doing well — suggesting that adequate income and a well-functioning family may help improve outcomes for a child with autism .

“Contextual factors like household and family functioning remind us that an autism diagnosis exists alongside the social context in which autistic children are growing up,” says Cost.

Cost says while social and environmental factors have been studied in relation to their effects on child development, there is little research among children with autism.

A strengths-based perspective on an autism diagnosis can help support a more flexible approach to developing future interventions that’s tailored to each child.

“There is no one way of doing well, but these findings open up a new avenue of research to assess what types of specific interventions, such as providing more income resources or alternative treatment planning for families at an earlier stage of development, may help increase the likelihood that more children with autism will do well over time,” says Szatmari.

The team – which also included researchers from Dalhousie University, McGill University, McMaster University, Simon Fraser University, Tel Aviv University, University of Alberta, University of British Columbia, University of Ottawa and University of Toronto – says future research will focus on outcomes among adolescents with autism as well as ways to further incorporate the perspectives of the participants themselves in outcome definition and measurement.