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Influence of Duodenal–Jejunal Implantation on Glucose Dynamics: A Pilot Study Using Different Nonlinear Methods

Author

Listed:
  • David Cuesta-Frau
  • Daniel Novák
  • Vacláv Burda
  • Daniel Abasolo
  • Tricia Adjei
  • Manuel Varela
  • Borja Vargas
  • Milos Mraz
  • Petra Kavalkova
  • Marek Benes
  • Martin Haluzik

Abstract

Diabetes is a disease of great and rising prevalence, with the obesity epidemic being a significant contributing risk factor. Duodenal–jejunal bypass liner (DJBL) is a reversible implant that mimics the effects of more aggressive surgical procedures, such as gastric bypass, to induce weight loss. We hypothesized that DJBL also influences the glucose dynamics in type II diabetes, based on the induced changes already demonstrated in other physiological characteristics and parameters. In order to assess the validity of this assumption, we conducted a quantitative analysis based on several nonlinear algorithms (Lempel–Ziv Complexity, Sample Entropy, Permutation Entropy, and modified Permutation Entropy), well suited to the characterization of biomedical time series. We applied them to glucose records drawn from two extreme cases available of DJBL implantation: before and after 10 months. The results confirmed the hypothesis and an accuracy of 86.4% was achieved with modified Permutation Entropy. Other metrics also yielded significant classification accuracy results, all above 70%, provided a suitable parameter configuration was chosen. With the Leave–One–Out method, the results were very similar, between 72% and 82% classification accuracy. There was also a decrease in entropy of glycaemia records during the time interval studied. These findings provide a solid foundation to assess how glucose metabolism may be influenced by DJBL implantation and opens a new line of research in this field.

Suggested Citation

  • David Cuesta-Frau & Daniel Novák & Vacláv Burda & Daniel Abasolo & Tricia Adjei & Manuel Varela & Borja Vargas & Milos Mraz & Petra Kavalkova & Marek Benes & Martin Haluzik, 2019. "Influence of Duodenal–Jejunal Implantation on Glucose Dynamics: A Pilot Study Using Different Nonlinear Methods," Complexity, Hindawi, vol. 2019, pages 1-10, February.
    • Handle: RePEc:hin:complx:6070518
    DOI: 10.1155/2019/6070518
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    References listed on IDEAS

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    1. Katya L Masconi & Tandi E Matsha & Rajiv T Erasmus & Andre P Kengne, 2015. "Effects of Different Missing Data Imputation Techniques on the Performance of Undiagnosed Diabetes Risk Prediction Models in a Mixed-Ancestry Population of South Africa," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-12, September.
    2. Till Seuring & Olga Archangelidi & Marc Suhrcke, 2015. "The Economic Costs of Type 2 Diabetes: A Global Systematic Review," PharmacoEconomics, Springer, vol. 33(8), pages 811-831, August.
    3. Restrepo, Juan F. & Schlotthauer, Gastón & Torres, María E., 2014. "Maximum approximate entropy and r threshold: A new approach for regularity changes detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 409(C), pages 97-109.
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