Marital stress can make people more vulnerable to depression

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.

Washington D.C., Jan 3: A new study has found out that diet significantly affects the mental health and well being of an individual.

The study was published in the journal European Neuropsychopharmacology.

"We have found that there is increasing evidence of a link between a poor diet and the worsening of mood disorders, including anxiety and depression. However, many common beliefs about the health effects of certain foods are not supported by solid evidence," said the lead researcher, Professor Suzanne Dickson.

According to the researchers, the link between diet and mental health can be firmly established in certain cases like that of the ability of a ketogenic diet being helpful for children with epilepsy and the impact of vitamin B12 deficiency on poor memory, depression and fatigue.

"With individual conditions, we often found very mixed evidence. With ADHD for example, we can see an increase in the quantity of refined sugar in the diet seems to increase ADHD and hyperactivity, whereas eating more fresh fruit and vegetables seems to protect against these conditions," said Dickson

But there are comparatively few studies, and many of them don't last long enough to show long-term effects," added Dickson.

The study further concludes that some food items can be associated with treatment and the betterment of certain mental health conditions.

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.