Gym mistakes to avoid

Washington, Feb 12: People who are optimistic may contribute to the health of their partners, staving off the risk factors leading to Alzheimer's disease, dementia and cognitive decline as they grow old together, according to a study.

The research, published in the Journal of Personality, followed nearly 4,500 heterosexual couples from the US Health and Retirement Study for up to eight years.

The researchers found a potential link between being married to an optimistic person and preventing the onset of cognitive decline, due to a healthier environment at home.

"We spend a lot of time with our partners.They might encourage us to exercise, eat healthier or remind us to take our medicine," said William Chopik, an assistant professor at the Michigan State University in the US.

"When your partner is optimistic and healthy, it can translate to similar outcomes in your own life. You actually do experience a rosier future by living longer and staving off cognitive illnesses," Chopik said.

An optimistic partner may encourage eating healthy foods, or working out together to develop healthier lifestyles, the researchers said.

For example, if a person quits smoking or starts exercising, their partner is close to following suit, they said.

"We found that when you look at the risk factors for what predicts things like Alzheimer's disease or dementia, a lot of them are things like living a healthy lifestyle," Chopik said.

"Maintaining a healthy weight and physical activity are large predictors.There are some physiological markers as well. It looks like people who are married to optimists tend to score better on all of those metrics," he said.

The researchers said there is a sense where optimists lead by example, and their partners follow their lead.

They also suggest that when couples recall shared experiences together, richer details from the memories emerge.

Chopik noted while there is a heritable component to optimism, there is some evidence to suggest that it's a trainable quality.

"There are studies that show people have the power to change their personalities, as long as they engage in things that make them change," Chopik said.

"Part of it is wanting to change. There are also intervention programs that suggest you can build up optimism," he added.

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.