'Children under the age of 5 carry higher levels of Covid-19'

Researchers have found that patients with peripheral artery disease or stroke were less likely to receive recommended treatments to prevent heart attack than those with coronary artery disease. All three are types of atherosclerotic cardiovascular disease.

Depending on the location of the blockage, atherosclerosis increases the risk for three serious conditions: coronary artery disease, stroke and peripheral artery disease.

"Our study highlights the need for public health campaigns to direct equal attention to all three major forms of atherosclerotic cardiovascular disease," said senior study author Erin Michos from the Johns Hopkins University in the US.

"We need to generate awareness among both clinicians and patients that all of these diseases should be treated with aggressive secondary preventive medications, including aspirin and statins, regardless of whether people have heart disease or not," Michos added.

Since atherosclerosis can affect arteries in more than one part of the body, medical guidelines are to treat coronary artery disease, stroke and peripheral artery disease similarly with lifestyle changes and medication, including statins to lower cholesterol levels and aspirin to prevent blood clots.

Lifestyle changes include eating a healthy diet, being physically active, quitting smoking, controlling high cholesterol, controlling high blood pressure, treating high blood sugar and losing weight.

What was unclear was if people with stroke and peripheral artery disease received the same treatments prescribed for those with coronary artery disease.

This study compared more than 14,000 US adults enrolled in the 2006-2015 Medical Expenditure Panel Survey, a national survey of patient-reported health outcomes and conditions, and health care use and expenses.

Slightly more than half of the patients were men, the average age was 65, and all had either coronary artery disease, stroke or peripheral artery disease.

These individuals were the representative of nearly 16 million US adults living with one of the three forms of atherosclerotic cardiovascular disease.

Compared to participants with coronary artery disease, participants with peripheral artery disease were twice more likely to report no statin use and three times more likely to report no aspirin use.

Additionally, people with peripheral artery disease had the highest, annual, total out-of-pocket expenditures among the three atherosclerotic conditions.

The findings showed that participants with stroke were more than twice as likely to report no statin or aspirin use.

Moreover, those with stroke were more likely to report poor patient-provider communication, poor health care satisfaction and more emergency room visits.

"Our study highlights a missed opportunity for implementing life-saving preventive medications among these high-risk individuals," Michos said.

The study was presented in the virtual conference at the American Heart Association's Quality of Care & Outcomes Research Scientific Sessions 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.

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.