Preoperative estimated glomerular filtration rate to predict cardiac events in major noncardiac surgery: a secondary analysis of two large international studies.

Background: Optimised use of kidney function information might improve cardiac risk prediction in noncardiac surgery.

Methods: In 35,815 patients from the VISION cohort study and 9219 patients from the POISE-2 trial who were ≥45 yr old and underwent nonurgent inpatient noncardiac surgery, we examined (by age and sex) the association between continuous nonlinear preoperative estimated glomerular filtration rate (eGFR) and the composite of myocardial injury after noncardiac surgery, nonfatal cardiac arrest, or death owing to a cardiac cause within 30 days after surgery. We estimated contributions of predictive information, C-statistic, and net benefit from eGFR and other common patient and surgical characteristics to large multivariable models.

Atrial fibrillation status and associations with adverse clinical outcomes in patients hospitalised with COVID-19: a large unselected statewide population-linkage study.

Background: Atrial fibrillation (AF) is common in COVID-19 patients. The impact of AF on major-adverse-cardiovascular-events (MACE defined as all-cause mortality, myocardial infarction, ischemic stroke, cardiac failure or coronary revascularisation), recurrent AF admission and venous thromboembolism in hospitalised COVID-19 patients is unclear.

Methods: Patients admitted with COVID-19 (1-January-2020 to 30-September-2021) were identified from the New South Wales Admitted-Patient-Data-Collection database, stratified by AF status (no-AF vs prior-AF or new-AF during index COVID-19 admission) and followed-up until 31-Mar-2022.

End-tidal CO and ventilation: Novel markers for assessing performance levels in elite long-distance runners.

Well-trained individuals, compared to less well-trained individuals, exhibit a lower minute ventilation (V̇) and higher end-tidal partial pressure of CO (PCO) at a given work rate. This study investigated whether such breathing adaptations seen in well-trained individuals also applied to elite long-distance runners. Forty-one long-distance runners were categorized into high (Long-High, consisting of Tokyo-Hakone College Ekiden [relay marathon] runners and Olympic athletes, n = 23), or low performance-level group (Long-Low, n = 18) according to their race times.

Vision transformer-equipped Convolutional Neural Networks for automated Alzheimer's disease diagnosis using 3D MRI scans.

Alzheimer's disease (AD) is a neurodegenerative ailment that is becoming increasingly common, making it a major worldwide health concern. Effective care depends on an early and correct diagnosis, but traditional diagnostic techniques are frequently constrained by subjectivity and expensive costs. This study proposes a novel Vision Transformer-equipped Convolutional Neural Networks (VECNN) that uses three-dimensional magnetic resonance imaging to improve diagnosis accuracy.