Application of Machine Learning to Assess Interindividual Variability in Rapid-Acting Insulin Responses After Subcutaneous Injection in People With Type 1 Diabetes
Language English Country Canada Media print-electronic
Document type Journal Article
PubMed
35568422
DOI
10.1016/j.jcjd.2021.09.002
PII: S1499-2671(21)00246-X
Knihovny.cz E-resources
- Keywords
- apprentissage automatique, diabète de type 1, insulin pharmacokinetics, interpersonal variability, machine learning, pharmacocinétique de l’insuline, type 1 diabetes, variabilité interpersonnelle,
- MeSH
- Diabetes Mellitus, Type 1 * complications MeSH
- Fibrinogen therapeutic use MeSH
- Hypoglycemic Agents pharmacology therapeutic use MeSH
- Plasminogen Activator Inhibitor 1 therapeutic use MeSH
- Injections, Subcutaneous MeSH
- Insulin therapeutic use MeSH
- Insulin Resistance * MeSH
- Insulin, Short-Acting therapeutic use MeSH
- Blood Glucose analysis MeSH
- Humans MeSH
- Postprandial Period MeSH
- Machine Learning MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Fibrinogen MeSH
- Hypoglycemic Agents MeSH
- Plasminogen Activator Inhibitor 1 MeSH
- Insulin MeSH
- Insulin, Short-Acting MeSH
- Blood Glucose MeSH
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. METHODS: We re-analyzed baseline pretreatment meal-tolerance test data from 2 randomized controlled trials in which 32 patients consumed a mixed-macronutrient meal and self-administered a single dose of rapid-acting insulin individualized by carbohydrate counting. Postprandial serum insulin, tumour necrosis factor (TNF)-alpha, plasma fibrinogen, human tissue factor (HTF) activity and plasminogen activator inhibitor-1 (PAI-1) were measured. Two-step clustering categorized individuals based on shared clinical characteristics. For analyses, insulin pharmacokinetic summary statistics were normalized, allowing standardized intraindividual comparisons. RESULTS: Despite standardization of insulin dose, individuals exhibited marked interpersonal variability in peak insulin concentrations (48.63%), time to peak (64.95%) and insulin incremental area under the curve (60.34%). Two clusters were computed: cluster 1 (n=14), representing increased serum insulin concentrations; and cluster 2 (n=18), representing reduced serum insulin concentrations (cluster 1: 389.50±177.10 pmol/L/IU h-1; cluster 2: 164.29±41.91 pmol/L/IU h-1; p<0.001). Cluster 2 was characterized by increased levels of fibrinogen, PAI-1, TNF-alpha and HTF activity; higher glycated hemoglobin; increased body mass index; lower estimated glucose disposal rate (increased insulin resistance); older age; and longer diabetes duration (p<0.05 for all analyses). CONCLUSIONS: Reduced serum insulin concentrations are associated with insulin resistance and a prothrombotic milieu in individuals with T1D, and therefore may be a marker of adverse vascular outcome.
Department of Internal Medicine 2nd Faculty of Medicine Charles University Prague Czech Republic
Diabetes Research Centre Leicester General Hospital University of Leicester Leicester United Kingdom
Leeds Institute of Cardiovascular and Metabolic Medicine University of Leeds Leeds United Kingdom
School of Food Science and Nutrition University of Leeds Leeds United Kingdom
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