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.

Comments

Add new comment

  • Coastaldigest.com reserves the right to delete or block any comments.
  • Coastaldigset.com is not responsible for its readers’ comments.
  • Comments that are abusive, incendiary or irrelevant are strictly prohibited.
  • Please use a genuine email ID and provide your name to avoid reject.
Agencies
January 11,2020

Europe, Jan 11: Researchers have revealed the people who drink tea at least three times a week have healthy years of life and longer life expectancy.

The research was published in the European Journal of Preventive Cardiology, a journal of the European Society of Cardiology (ESC).

Dr Xinyan Wang, who is the author of the study, said: "Habitual tea consumption is associated with lower risks of cardiovascular disease and all-cause death. The favourable health effects are the most robust for green tea and for long-term habitual tea drinkers."
The analysis that was conducted included about 100,902 participants of the China-PAR project2 with no history of heart attack, stroke, or cancer.

Participants were classified into two groups: Habitual tea drinkers and never or non-habitual tea drinkers and followed-up for a median of 7.3 years.

The analyses estimated that 50-year-old habitual tea drinkers would develop coronary heart disease and stroke 1.41 years later and live 1.26 years longer than those who never or seldom drank tea. Compared with never or non-habitual tea drinkers, the habitual tea consumers had a 20 per cent lower risk of incident heart disease and stroke, 22 per cent lower risk of fatal heart disease and stroke, and 15 per cent decreased risk of all-cause death.

The potential influence of changes in tea drinking behaviour was suspected in a subset of 14,081 participants with assessments at two-time points. The average duration between the two surveys was 8.2 years, and the median follow-up after the second survey was 5.3 years.

Habitual tea drinkers who maintained their habit in both surveys had a 39 per cent lower risk of incident heart disease and stroke, 56 per cent lower risk of fatal heart disease and stroke, and 29 per cent decreased risk of all-cause death compared to consistent never or non-habitual tea drinkers.

Senior author Dr Dongfeng Gu said: "The protective effects of tea were most pronounced among the consistent habitual tea drinking group. Mechanism studies have suggested that the main bioactive compounds in tea, namely polyphenols, are not stored in the body long-term. Thus, frequent tea intake over an extended period may be necessary for the cardioprotective effect."

In a subanalysis by type of tea, drinking green tea was linked with approximately 25 per cent lower risks for incident heart disease and stroke, fatal heart disease and stroke, and all-cause death. However, no significant associations were observed for black tea.
Dr Gu noted that a preference for green tea is unique to East Asia.

Two factors may be at play. First, green tea is a rich source of polyphenols which protect against cardiovascular disease and its risk factors including high blood pressure and dyslipidaemia. Black tea is fully fermented and during this process, polyphenols are oxidised into pigments and may lose their antioxidant effects. Second, black tea is often served with milk, which previous research has shown may counteract the favourable health effects of tea on vascular function.

Gender-specific analyses showed that the protective effects of habitual tea consumption were pronounced and robust across different outcomes for men, but only modest for women. Dr Wang said: "One reason might be that 48 per cent of men were habitual tea consumers compared to just 20 per cent of women. Secondly, women had a much lower incidence of, and mortality from, heart disease and stroke. These differences made it more likely to find statistically significant results among men."

She said: "The China-PAR project is ongoing, and with more person-years of follow-up among women the associations may become more pronounced."

In conclusion, the authors have found that randomised trials are required to validate the results and to illustrate nutritional guidelines and advice for lifestyle.

Comments

Add new comment

  • Coastaldigest.com reserves the right to delete or block any comments.
  • Coastaldigset.com is not responsible for its readers’ comments.
  • Comments that are abusive, incendiary or irrelevant are strictly prohibited.
  • Please use a genuine email ID and provide your name to avoid reject.
News Network
February 4,2020

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.

Comments

Add new comment

  • Coastaldigest.com reserves the right to delete or block any comments.
  • Coastaldigset.com is not responsible for its readers’ comments.
  • Comments that are abusive, incendiary or irrelevant are strictly prohibited.
  • Please use a genuine email ID and provide your name to avoid reject.
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.

Comments

Add new comment

  • Coastaldigest.com reserves the right to delete or block any comments.
  • Coastaldigset.com is not responsible for its readers’ comments.
  • Comments that are abusive, incendiary or irrelevant are strictly prohibited.
  • Please use a genuine email ID and provide your name to avoid reject.