Having children may add two years to your life: study

Tedros Adhanom Ghebreyesus, the World Health Organisation's (WHO) Director-General, said that a clinical trial of hydroxychloroquine (HCQ) on COVID-19 patients has come to "a temporary pause", while the safety data of the the anti-malaria drug was being reviewed.

According to the WHO chief, The Lancet medical journal on May 22 had published an observational study on HCQ and chloroquine and its effects on COVID-19 patients that have been hospitalized, reports Xinhua news agency.

The authors of the study reported that among patients receiving the drug, when used alone or with a macrolide, they estimated a higher mortality rate.

"The Executive Group of the Solidarity Trial, representing 10 of the participating countries, met on Saturday (May 23) and has agreed to review a comprehensive analysis and critical appraisal of all evidence available globally," Tedros said in a virtual press conference on Monday.

The review will consider data collected so far in the Solidarity Trial and in particular robust randomized available data, to adequately evaluate the potential benefits and harms from this drug, he said.

"The Executive Group has implemented a temporary pause of the HCQ arm within the Solidarity Trial while the safety data is reviewed by the Data Safety Monitoring Board. The other arms of the trial are continuing," Tedros added.

WHO initiated the Solidarity Trial, a plan to evaluate the safety and efficacy of four drugs and drug combinations against COVID-19 more than two months ago, which include HCQ.

According to the WHO, over 400 hospitals in 35 countries are actively recruiting patients and nearly 3,500 patients have been enrolled from 17 countries under the Solidarity Trial.

Tedros added that the safety concern over the drug related only to the use of HCQ and chloroquine in COVID-19, and "these drugs are accepted as generally safe for use in patients with autoimmune diseases or malaria".

"WHO will provide further updates as we know more," he added.

Clinician-scientists have found that Irish patients admitted to hospital with severe coronavirus (COVID-19) infection are experiencing abnormal blood clotting that contributes to death in some patients.

The research team from the Royal College of Surgeons in Ireland found that abnormal blood clotting occurs in Irish patients with severe COVID-19 infection, causing micro-clots within the lungs.

According to the study, they also found that Irish patients with higher levels of blood clotting activity had a significantly worse prognosis and were more likely to require ICU admission.

"Our novel findings demonstrate that COVID-19 is associated with a unique type of blood clotting disorder that is primarily focussed within the lungs and which undoubtedly contributes to the high levels of mortality being seen in patients with COVID-19," said Professor James O'Donnell from St James's Hospital in Ireland.

In addition to pneumonia affecting the small air sacs within the lungs, the research team has also hundreds of small blood clots throughout the lungs.

This scenario is not seen with other types of lung infection and explains why blood oxygen levels fall dramatically in severe COVID-19 infection, the study, published in the British Journal of Haematology said.

"Understanding how these micro-clots are being formed within the lung is critical so that we can develop more effective treatments for our patients, particularly those in high-risk groups," O'Donnell said.

"Further studies will be required to investigate whether different blood-thinning treatments may have a role in selected high-risk patients in order to reduce the risk of clot formation," Professor O'Donnell added.

According to the study, emerging evidence also shows that the abnormal blood-clotting problem in COVID-19 results in a significantly increased risk of heart attacks and strokes.

As of Friday morning, the cases increased to 20,612 cases in Ireland, with 1,232 deaths so far, according to the Johns Hopkins University.

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.