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National Post
2 hours ago
- National Post
McGill researchers develop AI that predicts respiratory illness before symptoms show
Researchers at McGill University say they developed an artificial intelligence platform that can predict when someone is about to come down with a respiratory tract infection before they start to feel sick. Article content In what researchers are calling a 'world first,' the study involved participants who wore a ring, a watch and a T-shirt, all of which were equipped with sensors that recorded their biometric data. By analyzing the data, researchers were able to accurately predict acute systemic inflammation — an early sign of a respiratory infection such as COVID-19. Article content Article content Article content Published in The Lancet Digital Health, the study says the AI platform can one day help doctors address health problems much earlier than they normally would, particularly in patients who are fragile and for whom a new infection could have serious consequences. It could also potentially reduce costs for the health-care system by preventing complications and hospitalizations. Article content Article content 'We were very interested to see if physiological data measured using wearable sensors … could be used to train an artificial intelligence system capable of detecting an infection or disease resulting from inflammation,' explained the study's lead author, Prof. Dennis Jensen of McGill University's department of kinesiology and physical education. Article content 'We wondered if we could detect early changes in physiology and, from there, predict that someone is about to get sick.' Article content Jense says the AI model his team created is the first in the world to use physiological measures — including heart rate, heart rate variability, body temperature, respiratory rate, blood pressure _ rather than symptoms, to detect a problem. Article content Article content Acute systemic inflammation is a natural defence mechanism of the body that usually resolves on its own, but it can cause serious health problems, especially in populations with pre-existing conditions. Article content Article content 'The whole idea is kind of like an iceberg,' Jensen said. 'Kind of when the ice cracks the surface, that's like when you're symptomatic, and then it's too late to really do much to treat it.' Article content During the study, McGill researchers administered a weakened flu vaccine to 55 healthy adults to simulate infection in their bodies. The subjects were monitored seven days before inoculation and five days after. Article content Participants wore a smart ring, smart watch, and a smart T-shirt simultaneously throughout the study. As well, researchers collected biomarkers of systemic inflammation using blood samples, PCR tests to detect the presence of respiratory pathogens, and a mobile app to collect symptoms reported by participants. Article content In total, more than two billion data points were collected to train machine learning algorithms. Ten different AI models were developed, but the researchers chose the model that used the least amount of data for the remainder of the project. The chosen model correctly detected nearly 90 per cent of actual positive cases and was deemed more practical for daily monitoring.
CTV News
2 hours ago
- CTV News
‘Ozempic face' may be driving a cosmetic surgery boom
About two years ago, celebrity cosmetic dermatologist Dr. Paul Jarrod Frank noticed a new type of patient arriving at his New York practice. Amid an explosion in the number of Americans losing weight with drugs like Ozempic, he saw a 'dramatic spike' in clients experiencing unwelcome side effects. 'Although they felt much better losing weight, in some ways they felt they looked older,' he said via a voice note. 'And this was due to the loss of volume in their face.' Frank started using the term 'Ozempic face' — a label he believes he coined — to describe the phenomenon. It has since become a social media byword for the sagging skin and hollowed-out appearance that can accompany the use of GLP-1 medications like semaglutide (the active ingredient in branded drugs such as Ozempic and Wegovy). 'Usually, with people from their mid-40s and above, once you start losing 10-plus pounds, you can get this kind of deflated look,' said Frank, who is the founder of aesthetic health care brand PFRANKMD and the author of 'The Pro-Aging Playbook.' 'Certainly, people losing 20 or 30-plus pounds are going to have this problem.' Semaglutide works by stimulating the pancreas to trigger insulin production, curbing users' appetite and contributing to feelings of fullness. Although the U.S. Food and Drug Administration approved Ozempic to treat Type 2 diabetes, doctors now commonly prescribe it off-label for weight management. About 1 in 8 adults in the U.S. has used a GLP-1 drug, and of those, around 2 in 5 did so solely to lose weight, according to health policy non-profit KFF in 2024. Today, more than 20% of Frank's patients are using GLP-1s as part of what he called their 'longevity regimen.' The treatments sought after their weight loss include injectable dermal fillers to help restore facial volume, facelifts and fat transfers. 'You can only refill a deflated balloon so much, and often surgical intervention is necessary,' he said. But for many patients, he added, 'just upping the dosage of their volume replacement is more than enough. 'Someone who may have used one syringe of filler in the past is now using two or three.' 'It looked like I had melted' The American Society of Plastic Surgeons (ASPS), which publishes an annual report on surgery trends, recently found that 2 in 5 of its members' GLP-1 patients were considering undergoing cosmetic surgery — and 1 in 5 already had. Among the patients opting for a facelift was Kimberly Bongiorno, a local government land use administrator from Mount Arlington, New Jersey. Having lost weight after gastric sleeve surgery in 2019, she regained 40 pounds during the COVID-19 pandemic and was prescribed Wegovy last year. Despite describing the drug's impact as 'almost a miracle' — taking her weight from 170 to 125 pounds — the 55-year-old faced new concerns over her appearance. 'Everything just kind of hung and was very loose,' she said over Zoom, recalling seeing her face in a photo shared by a friend. 'I no longer felt like I had cheeks, and I had a lot of loose skin under my neck. 'It looked like I had melted. It was horrifying,' she added. 'It was so disheartening to see how my face looked and how it had changed, I thought I looked a lot older than I am.' After consulting plastic surgeon Dr. Anthony Berlet at his New Jersey office, Bongiorno underwent a deep plane facelift that lifted her skin and repositioned some of the deeper muscles and connective tissues. She also opted for a neck lift that refined and smoothed her neck contours while addressing excess skin left by her weight loss. 'Before I did this, I probably looked closer to 60, or maybe even older. And now I have people who I've recently met think I am in my 40s,' Bongiorno said, adding: 'People I haven't seen in a while say, 'You look so healthy and happy.' And that's nice to hear, because for a while, I didn't look healthy and certainly wasn't happy.' The number of facelifts performed in the U.S. jumped 8% between 2022 and 2023, according to ASPS data. The use of hyaluronic acid fillers has meanwhile doubled from 2.6 million Americans in 2017 — the year Ozempic was first cleared for diabetes — to over 5.2 million in 2023. The organization could not attribute these upticks exclusively to GLP-1 use, but its former president, Dr. Steven Williams, said the medications have had 'a global effect on aesthetic surgery.' 'Now we have a brand-new tool that actually has efficacy for so many patients,' said Williams, a board-certified plastic surgeon and founder of California's Tri Valley Plastic Surgery, over Zoom. He noted that GLP-1s come 'without substantial drawbacks' when compared with invasive procedures like gastric bypass surgery. 'We can now have an honest conversation with patients about a nonsurgical tool that's effective in weight loss,' he added. 'And as part of that conversation, there's an obligation to say, 'Look, this is really going to work, so you have to be prepared for what looking 20 or 50 pounds slimmer is going to be.'' The term 'Ozempic face' may speak to our times, but its symptoms — caused by a decrease in the subcutaneous fat that makes our faces plump — are nothing new. Cosmetic surgeons have long been treating the side effects of significant weight loss. In fact, one popular brand of dermal filler, Sculptra, was originally developed in the 1990s for HIV patients. As an adult, 'your body actually doesn't make more fat cells,' Williams said. 'As we lose or gain weight, those fat cells aren't multiplying or decreasing; they're getting bigger or smaller. And so as we lose weight, those fat cells now have decreased volume, and there's just less fullness.' Preventive measures Age can determine how patients' faces react to weight loss. People in their 20s and 30s, for instance, are far less likely to experience the appearance of aging due to GLP-1 use, Frank said. 'Because they have good skin elasticity, the skin rebounds much better,' he said. Patients aged 20 to 39 accounted for 14% of hyaluronic acid filler use in the U.S. and just 2% of facelift procedures last year, according to the ASPS. But both figures are on the rise. Gabriela Vasquez, 29, is among the younger patients using GLP-1 to undergo cosmetic procedures after rapid weight loss. An employee of one of Williams' Tri Valley Plastic Surgery clinics, she has dropped around 50 pounds since starting Ozempic in November. Although Vasquez is still working toward her target weight, she sought preventative Botox injections (more visible lines and wrinkles are, along with thinning lips, among the other side effects of GLP-1 use). She has also recently undergone microneedling, a procedure used to stimulate collagen production. 'One of my concerns was my jowls, because I felt I saw them when I was a little heavier,' she said over Zoom from the Bay Area. 'I think the microneedling definitely helped. 'I never had a jaw line,' she added. 'And a couple weeks ago, someone took a picture of me, and I had one, and I was like, 'Well, that's new.'' Vasquez did not rule out further cosmetic procedures as she continues losing weight — and not only to her face and neck. 'I'm seeing little things in my body that I'm like, 'Whoa, that would be nice to take care of,'' she said, referencing the appearance of excess skin under her arms. 'I could see myself — later down the line, once I get to my goal weight — doing something to kind of tighten everything up.' Frank, the cosmetic dermatologist, noted that 'Ozempic face' may be accompanied by a phenomenon he dubbed 'Ozempic body,' adding: 'One of the other major side effects of weight loss, particularly when it's done at a rate of more than one to two pounds a week, is muscle loss. And we see this all over the body.' The ASPS similarly notes the emerging term 'Ozempic makeover,' a suite of procedures that might also include tummy tucks, breast lifts and arm, thigh and buttock lifts. For instance, Bongiorno, the New Jersey facelift patient, has also undergone several other procedures with Dr. Berlet, including arm and thigh lifts, to address her excess skin. She estimates that after her upcoming breast lift, fat grafting and lower eyelid surgery, she will have spent about $80,000 on cosmetic procedures. 'Skin is heavy and uncomfortable,' she said. 'This wasn't something I did to go out there and be a supermodel. It was just to be comfortable, so I could get clothes on and not feel like I was dragging around all this extra weight.' Ongoing questions The long-term effect of GLP-1 medications on cosmetic medicine is yet to be fully understood. The assumption they might reduce demand for liposuction, for instance, has not come to bear: It remains the most common cosmetic surgical procedure in the US, growing in popularity by 1% last year, per ASPS data. What also remains to be seen is the effect that 'Ozempic rebound' — when patients regain weight after stopping the drugs — has on people who sought cosmetic procedures. A recent peer-reviewed study found that most people using the drugs for weight loss quit within a year. Data presented at this year's European Congress on Obesity meanwhile suggested that patients typically returned to their original weight within 10 months of stopping use, with University of Oxford researchers calling the findings a 'cautionary note' about using medication 'without a more comprehensive approach' to weight loss. For Williams, this further demonstrates why he and his plastic surgeon colleagues must take responsibility for their patients' 'entire journey,' not just their cosmetic procedures. 'We don't want these patients to be on these medications for a lifetime. We want it to be a temporary bridge to a healthier lifestyle,' he said, adding: 'It's our obligation to work harder with those patients, to talk about lifestyle changes, to get them plugged in to dietitians and to make sure that they're building muscle and exercising.' By Oscar Holland, CNN
CTV News
2 hours ago
- CTV News
McGill University team develops AI that can detect infection before symptoms appear
Participants wore a smart ring, a smart watch, and a smart T-shirt that monitored multiple physiological parameters and activities. In the photo, an Apple Watch in 2015 in Tokyo. (Koji Sasahara, File/AP Photo) MONTRÉAL — Researchers at McGill University say they developed an artificial intelligence platform that can predict when someone is about to come down with a respiratory tract infection before they start to feel sick. In what researchers are calling a 'world first,' the study involved participants who wore a ring, a watch and a T-shirt, all of which were equipped with censors that recorded their biometric data. By analyzing the data, researchers were able to accurately predict acute systemic inflammation — an early sign of a respiratory infection such as COVID-19. Published in The Lancet Digital Health, the study says the AI platform can one day help doctors address health problems much earlier than they normally would, particularly in patients who are fragile and for whom a new infection could have serious consequences. It could also potentially reduce costs for the health-care system by preventing complications and hospitalizations. 'We were very interested to see if physiological data measured using wearable sensors … could be used to train an artificial intelligence system capable of detecting an infection or disease resulting from inflammation,' explained the study's lead author, Prof. Dennis Jensen of McGill University's department of kinesiology and physical education. 'We wondered if we could detect early changes in physiology and, from there, predict that someone is about to get sick.' Jense says the AI model his team created is the first in the world to use physiological measures — including heart rate, heart rate variability, body temperature, respiratory rate, blood pressure — rather than symptoms, to detect a problem. Acute systemic inflammation is a natural defence mechanism of the body that usually resolves on its own, but it can cause serious health problems, especially in populations with pre-existing conditions. 'The whole idea is kind of like an iceberg,' Jensen said. 'Kind of when the ice cracks the surface, that's like when you're symptomatic, and then it's too late to really do much to treat it.' During the study, McGill researchers administered a weakened flu vaccine to 55 healthy adults to simulate infection in their bodies. The subjects were monitored seven days before inoculation and five days after. Participants wore a smart ring, smart watch, and a smart T-shirt simultaneously throughout the study. As well, researchers collected biomarkers of systemic inflammation using blood samples, PCR tests to detect the presence of respiratory pathogens, and a mobile app to collect symptoms reported by participants. In total, more than two billion data points were collected to train machine learning algorithms. Ten different AI models were developed, but the researchers chose the model that used the least amount of data for the remainder of the project. The chosen model correctly detected nearly 90 per cent of actual positive cases and was deemed more practical for daily monitoring. On their own, Jensen said, none of the data collected from the ring, watch, or T-shirt alone is sensitive enough to detect how the body is responding. 'An increase in heart rate alone may only correspond to two beats per minute, which is not really clinically relevant,' he explained. 'The decrease in heart rate variability can be very modest. The increase in temperature can be very modest. So the idea was that by looking at … several different measurements, we would be able to identify subtle changes in physiology.' The algorithms also successfully detected systemic inflammation in four participants infected with COVID-19 during the study. In each case, the algorithms flagged the immune response up to 72 hours before symptoms appeared or infection was confirmed by PCR testing. Ultimately, the researchers hope to develop a system that will inform patients of possible inflammation so they can contact their health-care provider. 'In medicine, we say that you have to give the right treatment to the right person at the right time,' Jensen said. By expanding the therapeutic window in which doctors can intervene, he added, they could save lives and achieve significant savings by avoiding hospitalizations and enabling home management of chronic conditions or even aging. 'In a way, we hope to revolutionize personalized medicine.' This report by The Canadian Press was first published July 30, 2025. By Jean-Benoit Legault, The Canadian Press
