Long working hours bad for your heart

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.

Washington D.C., May 9: Do the middle age feel much stressful now, and seems to have changed over time, if compared to the life in the 90s? Well, this recent study indicates that it might be true.

The study has signalled to the fact that life may become more stressful majorly for middle-aged people than it was in the 1990s. The researchers reached this analysis even before the novel coronavirus started sweeping the globe.

A team of researchers led by Penn State found that across all ages, there was a slight increase in daily stress in the 2010s compared to the 1990s. But when researchers restricted the sample to people between the ages of 45 and 64, there was a sharp increase in daily stress.

"On average, people reported about 2 percent more stressors in the 2010s compared to people in the past," said David M. Almeida, professor of human development and family studies at Penn State.

"That's around an additional week of stress a year. But what really surprised us is that people at mid-life reported a lot more stressors, about 19 percent more stress in 2010 than in 1990. And that translates to 64 more days of stress a year."

Almeida said the findings were part of a larger project aiming to discover whether health during the middle of Americans' lives has been changing over time.

"Certainly, when you talk to people, they seem to think that daily life is more hectic and less certain these days," Almeida said.

For the study, the researchers collected data from 1,499 adults in 1995 and 782 different adults in 2012.

Almeida said the goal was to study two cohorts of people who were the same age at the time the data was collected but born in different decades. All study participants were interviewed daily for eight consecutive days.

During each daily interview, the researchers asked the participants about their stressful experiences throughout the previous 24 hours.

They asked questions related to arguments with family or friends or feeling overwhelmed at home or work, so and so. The participants were also asked how severe their stress was and whether those stressors were likely to impact other areas of their lives.

"We were able to estimate not only how frequently people experienced stress, but also what those stressors mean to them," Almeida said.

"For example, did this stress affect their finances or their plans for the future. And by having these two cohorts of people, we were able to compare daily stress processes in 1990 with daily stress processes in 2010," Almeida added.

After analyzing the data, the researchers found that participants reported significantly more daily stress and lower well-being in the 2010s compared to the 1990s.

Additionally, participants reported a 27 percent increase in the belief that stress would affect their finances and a 17 percent increase in the belief that stress would affect their future plans.

Almeida said he was surprised not that people were more stressed now than in the 90s, but at the age group that was mainly affected.

"We thought that with economic uncertainty, life might be more stressful for younger adults. But we didn't see that. We saw more stress for people at mid-life," Almeida said.

"And maybe that's because they have children who are facing an uncertain job market while also responsible for their own parents. So it's this generational squeeze that's making stress more prevalent for people at mid-life," he concluded.

Lower neighbourhood socioeconomic status and greater household crowding increase the risk of becoming infected with SARS-CoV-2, the virus that causes COVID-19, warn researchers.

"Our study shows that neighbourhood socioeconomic status and household crowding are strongly associated with risk of infection," said study lead author Alexander Melamed from Columbia University in the US.

"This may explain why Black and Hispanic people living in these neighbourhoods are disproportionately at risk for contracting the virus," Melamed added.

For the findings, published in the journal JAMA, the researchers examined the relationships between COVID-19 infection and neighbourhood characteristics in 396 women who gave birth during the peak of the Covid-19 outbreak in New York City. Since March 22, all women admitted to the hospitals for delivery have been tested for the virus, which gave the researchers the opportunity to detect all infections -- including infections with no symptoms -- in a defined population

The strongest predictor of COVID-19 infection among these women was residence in a neighbourhood where households with many people are common.The findings showed that women who lived in a neighbourhood with high household membership were three times more likely to be infected with the virus. Neighbourhood poverty also appeared to be a factor, the researchers said.Women were twice as likely to get COVID-19 if they lived in neighbourhoods with a high poverty rate, although that relationship was not statistically significant due to the small sample size.

The study revealed that there was no association between infection and population density.

"New York City has the highest population density of any city in the US, but our study found that the risks are related more to density in people's domestic environments rather than density in the city or within neighbourhoods," says co-author Cynthia Gyamfi-Bannerman."

The knowledge that SARS-CoV-2 infection rates are higher in disadvantaged neighbourhoods and among people who live in crowded households could help public health officials target preventive measures," the authors wrote.

Recently, another study published in the Journal of the American Planning Association, showed that dense areas were associated with lower COVID-19 death rates.