Application of Machine Learning to Assess Interindividual Variability in Rapid-Acting Insulin Responses After Subcutaneous Injection in People With Type 1 Diabetes.

Journal: Canadian journal of diabetes
PMID: 35568422

Abstract

OBJECTIVES: Circulating insulin concentrations mediate vascular-inflammatory and prothrombotic factors. However, it is unknown whether interindividual differences in circulating insulin levels are associated with different inflammatory and prothrombotic profiles in type 1 diabetes (T1D). We applied an unsupervised machine-learning approach to determine whether interindividual differences in rapid-acting insulin levels associate with parameters of vascular health in patients with T1D.

Authors

  • Eleanor M Coales
    School of Food Science and Nutrition, University of Leeds, Leeds, United Kingdom.
  • Ramzi A Ajjan
    Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom.
  • Sam M Pearson
    Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom.
  • Lauren L O'Mahoney
    Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, United Kingdom.
  • Noppadol Kietsiriroje
    Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom.
  • Jan Brož
    Department of Internal Medicine, Second Faculty of Medicine, Charles University, Prague, Czech Republic.
  • Mel Holmes
    School of Food Science and Nutrition, University of Leeds, Leeds, United Kingdom.
  • Matthew D Campbell
    Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom; School of Nursing and Health Sciences, University of Sunderland, Sunderland, United Kingdom. Electronic address: matthew.campbell@sunderland.ac.uk.

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