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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.

Bergen, Mar 5: Divorce of parents may impact the academics of children negatively, suggests a new study.

According to the study, parental divorce is associated with a lower grade point average (GPA) among adolescents, with a stronger association seen in teens with more educated mothers.

The study was published in the journal PLOS ONE.

Children and adolescents with divorced or separated parents are known to do less well in school than adolescents with nondivorced parents and to be less well-adjusted, on average, across a spectrum of physical and mental health outcomes.

In the new study, researchers used data from the youth@hordaland study, a population-based survey of adolescents aged 16-19 conducted in the spring of 2012 in Hordaland County, Norway.

19,439 adolescents were invited to participate and 10,257 agreed; of those, 9,166 are included in the current study.

Overall, adolescents with divorced parents had a 0.3 point lower GPA (standard error 0.022, p<0.01) than their peers.

Controlling for parental education reduced the effect by 0.06 points to 0.240 (SE 0.021, p<0.01). This heterogeneity was predominantly driven by maternal education levels, the researchers found.

After controlling for paternal education and income measures, divorce was associated with a 0.120 point decrease in GPA among adolescents whose mothers had a secondary school education level; a 0.175 point decrease when mothers had a Bachelor's level education; and a 0.209 point decrease when mothers had a Master's or PhD level education (all estimates relative to adolescents with a mother who had a basic level of education, such as ISCED 0-2).

Due to the cross-sectional structure of the study, researchers could not investigate specific changes between pre- and post-divorce family life, and future studies are needed to investigate potential mechanisms (such as reduced parental monitoring or school-involvement) which might drive this finding.

Nonetheless, this study provides new evidence that the negative association between divorce and teens' GPA is especially strong in families with more educated mothers.

"Among Norwegian adolescents, parental divorce was hardly associated with GPA among youth whose parents have low educational qualifications. In contrast, among adolescents with educated or highly educated mothers, divorce was significantly associated with lower GPA," said the authors.

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.