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Machine learning-based marker for coronary artery disease: derivation and validation in two longitudinal cohorts

Electronic health record-based machine learning was used to generate an in-silico marker for coronary artery disease that can non-invasively quantify atherosclerosis and risk of death on a continuous spectrum, and identify underdiagnosed individuals.
United States United Kingdom Nat Genet Coll Cardiol Schjerning Olsen Goff Jr

Differential symptomology of possible and confirmed Ebola virus disease infection in the Democratic Republic of the Congo: a retrospective cohort study

Establishing the exact time an individual first had symptoms is essential to assessing their infection risk. An individuals exposure history remains of paramount importance, especially in the early phase. Ebola virus disease vaccination reduces symptom severity and should also be considered when assessing the likelihood of infection. These findings about symptomatology should be translated into practice during triage and should inform testing and quarantine procedures.
Democratic Republic Of The Congo Western Area Sierra Leone World Health Organization Bull World Health Organ Infect Dis

Incidence of death or disability at 6 months after extracorporeal membrane oxygenation in Australia: a prospective, multicentre, registry-embedded cohort study

In our study, only a third of patients were alive without moderate-to-severe disability at 6 months after initiation of ECMO. The finding that disability was common across all areas of functioning points to the need for long-term, multidisciplinary care and support for surviving patients who have had ECMO. Further studies are needed to understand the 180-day and longer-term prognosis of patients with different diagnoses receiving different modes of ECMO, which could have important implications f...
Anesth Analg Serpa Neto Rr Core Team Value Health Intj Qual Health Care International Liaison Committee On Resuscitation

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