Better to act young than to look young

Washington, Jun 20: Pregnant and postpartum women are usually at a high risk of depression and anxiety - one in seven women struggle with symptoms in the perinatal period and the coronavirus pandemic is exacerbating those struggles according to a recent study.

The study was published in Frontiers in Global Women's Health, which found that the likelihood of maternal depression and anxiety has substantially increased during the health crisis.

"The social and physical isolation measures that are critically needed to reduce the spread of the virus are taking a toll on the physical and mental health of many of us," said Dr. Margie Davenport of the University of Alberta, Canada, who co-authored the study.

For new moms, those stresses come with side effects.

"We know that experiencing depression and anxiety during pregnancy and the postpartum period can have detrimental effects on the mental and physical health of both mother and baby that can persist for years," said Davenport.

Such effects can include premature delivery, reduced mother-infant bonding, and developmental delays in infants.

The study surveyed 900 women - 520 of whom were pregnant and 380 of whom had given birth in the past year - and asked about their depression and anxiety symptoms before and during the pandemic.

Before the pandemic began, 29 percent of those women experienced moderate to high anxiety symptoms, and 15 percent experienced depressive symptoms. During the pandemic, those numbers increased - 72 percent experienced anxiety and 41percent experienced depression.

Because lockdown measures have affected daily routines and access to gyms, researchers also asked women whether their exercise habits had changed. Of the women surveyed, 64 percent reduced their physical activity since the pandemic began, while 15 percent increased and 21 percent experienced no change.

Exercise is a known way to ease depression symptoms, so limited physical activity may result in an uptick in depressive symptoms. Indeed, the study found that women who engaged in at least 150 minutes of moderate physical activity a week had significantly lower symptoms of depression and anxiety.

The findings are somewhat limited given the fact that researchers could not survey women before the pandemic began (since they could not know a pandemic would occur). The women surveyed could only offer their pre-pandemic symptoms in hindsight.

Also, while the researchers asked women about their symptoms using validated measures, only mental health care professionals can validly diagnose an individual with depression or anxiety.

The study was specifically interested in the impact of COVID-19 on new moms, but Davenport says maternal mental health is a critical issue no matter the time.

"Even when we are not in a global pandemic, many pregnant and postpartum women frequently feel isolated whether due to being hospitalized, not having family or friends around or other reasons," she said.

"It is critical to increase awareness of the impact of social (and physical) isolation on the mental health of pregnant and postpartum women," Davenport added.

Increased awareness makes diagnosis and treatment - the ultimate goal - more likely.

High-protein diets may help people lose weight and build muscle, but there is a downside to it --a greater heart attack risk. Researchers now report that high-protein diets boost artery-clogging plaque.

The research in mice showed that high-protein diets spur unstable plaque -- the kind most prone to rupturing and causing blocked arteries.

More plaque buildup in the arteries, particularly if it's unstable, increases the risk of heart attack.

"There are clear weight-loss benefits to high-protein diets, which has boosted their popularity in recent years," said senior author Babak Razani, associate professor at Washington University School of Medicine in St. Louis, Missouri.

"But animal studies and some large epidemiological studies in people have linked high dietary protein to cardiovascular problems. We decided to take a look at whether there is truly a causal link between high dietary protein and poorer cardiovascular health," Razani added.

The researchers studied mice who were fed a high-fat diet to deliberately induce atherosclerosis, or plaque buildup in the arteries.

Some of the mice received a high-fat diet that was also high in protein. And others were fed a high-fat, low-protein diet for comparison.

The mice on the high-fat, high-protein diet developed worse atherosclerosis -- about 30 per cent more plaque in the arteries -- than mice on the high-fat, normal-protein diet, despite the fact that the mice eating more protein did not gain weight, unlike the mice on the high-fat, normal-protein diet.

"A couple of a scoop of protein powder in a milkshake or smoothie adds something like 40 grams of protein -- almost equivalent to the daily recommended intake," Razani said.

"To see if protein has an effect on cardiovascular health, we tripled the amount of protein that the mice receive in the high-fat, high-protein diet -- keeping the fat constant. Protein went from 15 per cent to 46 per cent of calories for these mice".

Plaque contains a mix of fat, cholesterol, calcium deposits and dead cells. Past work by Razani's team and other groups has shown that immune cells called macrophages work to clean up plaque in the arteries.

But the environment inside plaque can overwhelm these cells, and when such cells die, they make the problem worse, contributing to plaque buildup and increasing plaque complexity.

"In mice on the high-protein diet, their plaques were a macrophage graveyard," Razani informed.

To understand how high dietary protein might increase plaque complexity, Razani and his colleagues also studied the path protein takes after it has been digested -- broken down into its original building blocks, called amino acids.

"This study is not the first to show a telltale increase in plaque with high-protein diets, but it offers a deeper understanding of the impact of high protein with the detailed analysis of the plaques," said Razani.

"This work not only defines the critical processes underlying the cardiovascular risks of dietary protein but also lays the groundwork for targeting these pathways in treating heart disease," he added.

New York, Feb 26:  A new wearable sensor that works in conjunction with artificial intelligence (AI) technology could help doctors remotely detect critical changes in heart failure patients days before a health crisis occurs, says a study.

The researchers said the system could eventually help avert up to one in three heart failure readmissions in the weeks following initial discharge from the hospital and help patients sustain a better quality of life.

"This study shows that we can accurately predict the likelihood of hospitalisation for heart failure deterioration well before doctors and patients know that something is wrong," says the study's lead author Josef Stehlik from University of Utah in the US.

"Being able to readily detect changes in the heart sufficiently early will allow physicians to initiate prompt interventions that could prevent rehospitalisation and stave off worsening heart failure," Stehlik added.

According to the researchers, even if patients survive, they have poor functional capacity, poor exercise tolerance and low quality of life after hospitalisations.

"This patch, this new diagnostic tool, could potentially help us prevent hospitalizations and decline in patient status," Stehlik said.

For the findings, published in the journal Circulation: Heart Failure, the researchers followed 100 heart failure patients, average age 68, who were diagnosed and treated at four veterans administration (VA) hospitals in Utah, Texas, California, and Florida.

After discharge, participants wore an adhesive sensor patch on their chests 24 hours a day for up to three months.

The sensor monitored continuous electrocardiogram (ECG) and motion of each subject.

This information was transmitted from the sensor via Bluetooth to a smartphone and then passed on to an analytics platform, developed by PhysIQ, on a secure server, which derived heart rate, heart rhythm, respiratory rate, walking, sleep, body posture and other normal activities.

Using artificial intelligence, the analytics established a normal baseline for each patient. When the data deviated from normal, the platform generated an indication that the patient's heart failure was getting worse.

Overall, the system accurately predicted the impending need for hospitalization more than 80 per cent of the time.

On average, this prediction occurred 10.4 days before a readmission took place (median 6.5 days), the study said.