Over 46,000 Mumbaikars have succumbed to TB in the last 6 years: Report

Singapore, May 25: COVID-19 patients are no longer infectious after 11 days of getting sick even though some may still test positive, according to a new study by infectious disease experts in Singapore.

A positive test "does not equate to infectiousness or viable virus," a joint research paper by Singapore's National Centre for Infectious Diseases and the Academy of Medicine, Singapore said. The virus "could not be isolated or cultured after day 11 of illness."

The paper was based on a study of 73 patents in the city-state.

The latest findings may have implications on the country's patient discharge policy. The discharge criteria is currently based on negative test results rather than infectiousness.

Singapore's strategy on managing COVID-19 patients is guided by the latest local and international clinical scientific evidence, and the Ministry of Health will evaluate if the latest evidence can be incorporated into its patient clinical management plan, according to a report by the Straits Times.

So far, 13,882, or about 45% of the total 31,068 Covid-19 patients in Singapore have been discharged from hospitals and community facilities. Singapore reported 642 new Covid-19 cases as of noon on Saturday.

The government has been actively screening pre-school staff as it prepares to reopen pre-schools from June 2. On Friday, two pre-school employees tested positive for the novel coronavirus, bringing the total number of confirmed cases among pre-school staff to seven, according to the Ministry of Health.

Toronto, Feb 4: People who text while walking face a higher risk of an accident than those listening to music or talking on the phone, a study has found.

The study, published in the journal Injury Prevention, found that smartphone texting is linked to compromised pedestrian safety, with higher rates of 'near misses', and failure to look left and right before crossing a road.

Researchers from the University of Calgary in Canada call for a more thorough approach to exploring the impact of distracted pedestrian behaviours on crash risk.

Worldwide, around 270,000 pedestrians die every year, accounting for around a fifth of all road traffic deaths, according to the researchers.

'Pedestrian distraction' has become a recognised safety issue as more and more people use their smartphones or hand held devices while walking on the pavement and crossing roads, they said.

The researchers looked for published evidence to gauge the potential impact on road safety of hand-held or hands-free device activities.

This included talking on the phone, text messaging, browsing and listening to music.

From among 33 relevant studies, they pooled the data from 14 -- involving 872 people -- and systematically reviewed the data from another eight.

The analysis showed that listening to music wasn't associated with any heightened risk of potentially harmful pedestrian behaviours.

Talking on the phone was associated with a small increase in the time taken to start crossing the road, and slightly more missed opportunities to cross the road safely.

The researchers found that text messaging emerged as the potentially most harmful behaviour.

It was associated with significantly lower rates of looking left and right before or while crossing the road, and with moderately increased rates of collisions, and close calls with other pedestrians or vehicles, they said.

Texting also affected the time taken to cross a road, and missed opportunities to cross safely, but to a lesser extent, according to the researchers.

The review of the eight observational studies revealed that the percentage of pedestrians who were distracted ranged from 12 to 45 per cent, they said.

It also found behaviours were influenced by several factors, including gender, time of day, solo or group crossing, and walking speed.

The researchers acknowledge "a variety of study quality issues" which limit the generalisability of the findings.

"Given the ubiquity of smartphones, social media, apps, digital video and streaming music, which has infiltrated most aspects of daily life, distracted walking and street cross will be a road safety issue for the foreseeable future," the researchers noted.

"And as signage and public awareness campaigns don't seem to alter pedestrian behaviour, establishing the relationship between distracted walking behaviour and crash risk is an essential research need," they said.

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.