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New study links poor sleep quality to atrial fibrillation

A recent study has found that poor sleep quality is an independent risk factor for atrial fibrillation (AF), which can lead to symptoms like heart palpitations and shortness of breath. The researchers also discovered that disruptions in sleep patterns, such as reduced REM sleep, predict a higher risk of AF.

SourceElsevier·JournalHeart Rhythm·DateJun 26, 2018

Bisexual men have higher risk for heart disease

A new study published in LGBT Health found that bisexual men have a higher risk for heart disease compared to heterosexual men, with increased rates of mental distress, obesity, and elevated blood pressure. Researchers highlight the importance of tailored screening and prevention strategies to reduce heart disease risk in bisexual men.

SourceNew York University·JournalLGBT Health·DateJun 21, 2018

Optimal sleep linked to lower risks for dementia and early death

A study of Japanese adults aged 60 found that short and long daily sleep durations were risk factors for dementia and premature death. Participants with optimal sleep duration (5-6.9 hours) had a lower risk of dementia and death compared to those with shorter or longer sleep durations.

SourceWiley·JournalJournal of the American Geriatrics Society·DateJun 6, 2018

Education linked to higher risk of short-sightedness

A study published in The BMJ found that spending more years in full-time education is associated with a greater risk of developing myopia. Every additional year of education was linked to more myopia, with university graduates being at least 1 dioptre more myopic than those who left school earlier.

SourceBMJ Group·JournalThe BMJ·DateJun 6, 2018

The Lancet: A warning and an opportunity: The WHO Independent High-Level Commission on non-communicable diseases

The WHO Independent High-Level Commission on NCDs reports that the Sustainable Development Goal for reducing premature deaths from NCDs by a third by 2030 will not be met at current rates. The commission proposes six recommendations to address this issue, including increased political leadership, prioritization, and improved financing.

SourceThe Lancet·JournalThe Lancet·DateJun 1, 2018

Study gauges impact of dengue virus on Ethiopia

A recent study published in PLOS Neglected Tropical Diseases found that nearly a third of febrile patients in Northwest Ethiopia tested positive for dengue virus. The study identified key risk factors, including residence, occupation, and lack of mosquito net use, which can contribute to DENV infection.

SourcePLOS·JournalPLOS Neglected Tropical Diseases·DateMay 31, 2018

Big data reveals new Alzheimer's risk genes

A large-scale study has identified three new genes linked to the risk of Alzheimer's disease, shedding light on the mechanisms underlying the condition. The findings, published in Translational Psychiatry, are based on genetic data from over 300,000 people and could pave the way for new approaches to treating the disease.

SourceUniversity of Edinburgh·JournalTranslational Psychiatry·DateMay 17, 2018

SCAI updates consensus on length of stay for percutaneous coronary intervention

The Society for Cardiovascular Angiography and Interventions has updated its consensus guidelines to allow for flexibility in length of stay after percutaneous coronary intervention (PCI), prioritizing patient-centered care. The new guidelines assess readiness for discharge along three lines: procedural, patient, and programmatic factors.

SourceSociety for Cardiovascular Angiography and Interventions·JournalCatheterization and Cardiovascular Interventions·DateApr 25, 2018

New 'brain health index' can predict how well patients will do after stroke

A new computer programme assesses whole brain deterioration and predicts cognitive function after stroke up to ten times more accurately than current methods. The 'brain health index' can quantify visible brain injury from cerebral small vessel disease and brain atrophy, giving early warning of risk of future cognitive decline.

SourceSAGE·JournalInternational Journal of Stroke·DateApr 19, 2018

Using AI to detect heart disease

A new method developed by researchers at USC Viterbi School of Engineering uses machine learning to measure key risk factor for cardiovascular diseases and arterial stiffness using just a smartphone. The method was validated with existing tonometry data and showed high correlation with actual tonometry measurements.

SourceUniversity of Southern California·JournalScientific Reports·DateApr 16, 2018