Wearable sensor to predict worsening heart failure

News Network
February 26, 2020

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.

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Agencies
June 22,2020

A team of scientists has produced first open source all-atom models of full-length COVID-19 Spike protein that facilitates viral entry into host cells – a discovery that can facilitate a faster vaccine and antiviral drug development.

The group from Seoul National University in South Korea, University of Cambridge in the UK and Lehigh University in the US produced the first open-source all-atom models of a full-length S protein.

The researchers say this is of particular importance because the S protein plays a central role in viral entry into cells, making it a main target for vaccine and antiviral drug development.

"Our models are the first full-length SARS-CoV-2 spike (S) protein models that are available to other scientists," said Wonpil Im, a professor in Lehigh University.

"Our team spent days and nights to build these models very carefully from the known cryo-EM structure portions. Modeling was very challenging because there were many regions where simple modeling failed to provide high-quality models," he wrote in a paper published in The Journal of Physical Chemistry B.

Scientists can use the models to conduct innovative and novel simulation research for the prevention and treatment of Covid-19.

Though the coronavirus uses many different proteins to replicate and invade cells, the Spike protein is the major surface protein that it uses to bind to a receptor.

The total number of global COVID-19 cases was nearing 9 million, while the deaths have increased to over 467,000, according to the Johns Hopkins University.

With 2,279,306 cases and 119,967 deaths, the US continues with the world's highest number of COVID-19 infections and fatalities, according to the CSSE.

Brazil comes in the second place with 1,083,341 infections and 50,591 deaths.

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Agencies
June 21,2020

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.

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Agencies
January 16,2020

Thiruvananthapuram, Jan 16: Kerala Tourism on Wednesday shared a recipe of a popular meat dish in the Central Travancore region of Kerala, Beef Ularthiyathu, which is a special delicacy in the region.

Taking to its Twitter handle, the Kerala Tourism wrote, "Tender chunks of beef, slow-roasted with aromatic spices, coconut pieces, and curry leaves. A recipe for the most classic dish, Beef Ularthiyathu, the stuff of legends, from the land of spices, Kerala."

The State Tourism also shared the recipe of the delicacy with Twitteratis.

The tweet which has garnered 3.5 thousand likes so far had received a mixed response

While some said "beef is not Kerala's culture", others termed the recipe 'a match made in heaven".

Dr Vireandta Jilowa wrote, "Surprised to see it, that beef is being consumed despite BJP government in the Centre."

"We are not slaves of BJP at the Centre....people eat whatever they like in this state, including beef, pork, mutton and fish," another user Tatheesh Vijayakumar wrote.

In 2017, The Minister for Environment, Forest and Climate Change Harsh Vardhan had ordered that the ministry has notified the Prevention of Cruelty to Animals (Regulation of Livestock Markets) Rules, 2017 to ensure that the sale of cattle is not meant for slaughter purposes.

Regulating animal trade is a state business, but animal welfare is a central subject.

In lieu of this, there was widespread opposition of the order, with many states openly denying accepting the notification.

Porotta and Kappa biriyani with beef are counted as delicacies by Keralites. 

Also Read: The Art of Prepping Meat

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