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Early treatment with the antiviral drug remdesivir has been found to reduce viral load and prevent lung disease in macaques infected with SARS-CoV-2 that causes COVID-19, according to a study.

The findings, published in the journal Nature on Tuesday, support the early use of remdesivir treatment in patients with COVID-19 to prevent progression to pneumonia.

Researchers from the National Institutes of Health in the US noted that remdesivir has broad antiviral activity and has been shown to be effective against infections with SARS-CoV and MERS-CoV in animal models.

The drug is being tested in human clinical trials for the treatment of COVID-19, they said.

Researcher Emmie de Wit and colleagues investigated the effects of remdesivir treatment in rhesus macaques, a recently established model of SARS-CoV-2 infection.

Two sets of six macaques were inoculated with SARS-CoV-2.

One group was treated with remdesivir 12 hours later -- close to the peak of virus reproduction in the lungs -- and these macaques received treatment every 24 hours until six days after inoculation.

In contrast to the control group, the researchers found that macaques that received remdesivir did not show signs of respiratory disease, and had reduced damage to the lungs.

Viral loads in the lower respiratory tract were also reduced in the treated animals; viral levels were around 100 times lower in the lower-respiratory tract of remdesivir-treated macaques 12 hours after the first dose, they said.

The researchers said that infectious virus could no longer be detected in the treatment group three days after initial infection, but was still detectable in four out of six control animals.

Despite this virus reduction in the lower respiratory tract, no reduction in virus shedding was observed, which indicates that clinical improvement may not equate to a lack of infectiousness, they said.

Dosing of remdesivir in the rhesus macaques is equivalent to that used in humans, the researchers noted.

They cautioned that it is difficult to directly translate the timing of treatment used in corresponding disease stages in humans, because rhesus macaques normally develop only mild disease.

However, researchers said the results indicate that remdesivir treatment of COVID-19 should be initiated as early as possible to achieve the maximum treatment effect.

Taking multiple courses of antibiotics within a short span of time may do people more harm than good, suggests new research which discovered an association between the number of prescriptions for antibiotics and a higher risk of hospital admissions.

Patients who have had 9 or more antibiotic prescriptions for common infections in the previous three years are 2.26 times more likely to go to hospital with another infection in three or more months, said the researchers.

Patients who had two antibiotic prescriptions were 1.23 times more likely, patients who had three to four prescriptions 1.33 times more likely and patients who had five to eight 1.77 times more likely to go to hospital with another infection.

"We don't know why this is, but overuse of antibiotics might kill the good bacteria in the gut (microbiota) and make us more susceptible to infections, for example," said Professor Tjeerd van Staa from the University of Manchester in Britain.

The study, published in the journal BMC Medicine, is based on the data of two million patients in England and Wales.

The patient records, from 2000 to 2016, covered common infections such as upper respiratory tract, urinary tract, ear and chest infections and excluded long term conditions such as cystic fibrosis and chronic lung disease.

The risks of going to hospital with another infection were related to the number of the antibiotic prescriptions in the previous three years.

A course is defined by the team as being given over a period of one or two weeks.

"GPs (general physicians) care about their patients, and over recent years have worked hard to reduce the prescribing of antibiotics,""Staa said.

"But it is clear GPs do not have the tools to prescribe antibiotics effectively for common infections, especially when patients already have previously used antibiotics.

"They may prescribe numerous courses of antibiotics over several years, which according to our study increases the risk of a more serious infection. That in turn, we show, is linked to hospital admissions," Staa added.

It not clear why hospital admissions are linked to higher prescriptions and research is needed to show what or if any biological factors exist, said the research team.

"Our hope is that, however, a tool we are working for GPs, based on patient history, will be able to calculate the risks associated with taking multiple courses of antibiotics," said Francine Jury from the University of Manchester.

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.