What's New

Last Posted: Dec 17, 2020

• Performance and clinical utility of supervised machine-learning approaches in detecting familial hypercholesterolaemia in primary care.
  Akyea Ralph K et al. NPJ digital medicine 2020 Oct 3(1) 142
• Sex Differences in the Risk of Coronary Heart Disease Associated With Type 2 Diabetes: A Mendelian Randomization Analysis.
  Peters Tricia M et al. Diabetes care 2020 Dec
• Sex differences in cardiovascular morbidity associated with familial hypercholesterolaemia: A retrospective cohort study of the UK Simon Broome register linked to national hospital records.
  Iyen Barbara et al. Atherosclerosis 2020 Oct
• Color Data v2: a user-friendly, open-access database with hereditary cancer and hereditary cardiovascular conditions datasets.
  Berger Mark J et al. Database : the journal of biological databases and curation 2020 Jan 2020
• Inherited causes of clonal haematopoiesis in 97,691 whole genomes.
  Bick Alexander G et al. Nature 2020 Oct
• Predicting Postoperative Length of Stay for Isolated Coronary Artery Bypass Graft Patients Using Machine Learning.
  Alshakhs Fatima et al. International journal of general medicine 2020 13751-762
• Electronic health records to facilitate continuous detection of familial hypercholesterolemia.
  Pepplinkhuizen Shari et al. Atherosclerosis 2020 Aug 31083-87
• Consideration of clinical translation of cardiac AAV gene therapy.
  Yamada Kelly P et al. Cell & gene therapy insights 2020 Jun 6(5) 609-615
• An Implementation Science Framework to Develop a Clinical Decision Support Tool for Familial Hypercholesterolemia.
  Bangash Hana et al. Journal of personalized medicine 2020 Jul 10(3)
• Molecular screening of familial hypercholesterolemia in Icelanders.
  Kellogg Greg et al. Scandinavian journal of clinical and laboratory investigation 2020 Jul 1-7
• Dietary Recommendations for Familial Hypercholesterolaemia: an Evidence-Free Zone.
  Diamond David M et al. BMJ evidence-based medicine 2020 Jul
• Accurate Prediction of Coronary Heart Disease for Patients With Hypertension From Electronic Health Records With Big Data and Machine-Learning Methods: Model Development and Performance Evaluation.
  Du Zhenzhen et al. JMIR medical informatics 2020 Jul 8(7) e17257
• Applying Artificial Intelligence to Predict Self-Reported Poor Health Among Black and Hispanic Caregivers with Mild Cognitive Impairment.
  Yoon Sunmoo et al. Studies in health technology and informatics 2020 Jun 272433-436
• Family history of cardiovascular disease and risk of premature coronary heart disease: A matched case-control study.
  Chacko Manas et al. Wellcome open research 2020 570
• Health economic evaluation of screening and treating children with familial hypercholesterolemia early in life: Many happy returns on investment?
  Ademi Zanfina et al. Atherosclerosis 2020 May 3041-8