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Influence of glucometric 'dynamical' variables on duodenal-jejunal bypass liner (DJBL) anthropometric and metabolic outcomes
A. Colás, M. Varela, M. Mraz, D. Novak, D. Cuesta-Frau, L. Vigil, M. Benes, T. Pelikanova, M. Haluzik, V. Burda, B. Vargas
Language English Country Great Britain
Document type Journal Article, Research Support, Non-U.S. Gov't
Grant support
CZ.02.1.01/0.0/0.0/16_019/0000765
Research Center for Informatics - International
SGS19/171/OHK3/3T/13
Biomedical data acquisition, processing and visualization - International
MH CZ - DRO ("IKEM, IN 00023001") - International
RVO VFN64165 - International
PubMed
31916665
DOI
10.1002/dmrr.3287
Knihovny.cz E-resources
- MeSH
- Biomarkers analysis MeSH
- Diabetes Mellitus, Type 2 complications surgery MeSH
- Adult MeSH
- Duodenum surgery MeSH
- Glycated Hemoglobin analysis MeSH
- Weight Loss MeSH
- Jejunum surgery MeSH
- Blood Glucose analysis MeSH
- Middle Aged MeSH
- Humans MeSH
- Metabolic Syndrome etiology prevention & control MeSH
- Obesity, Morbid physiopathology surgery MeSH
- Follow-Up Studies MeSH
- Prognosis MeSH
- Aged MeSH
- Gastric Bypass methods MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
BACKGROUND: The endoscopically implanted duodenal-jejunal bypass liner (DJBL) is an attractive alternative to bariatric surgery for obese diabetic patients. This article aims to study dynamical aspects of the glycaemic profile that may influence DJBL effects. METHODS: Thirty patients underwent DJBL implantation and were followed for 10 months. Continuous glucose monitoring (CGM) was performed before implantation and at month 10. Dynamical variables from CGM were measured: coefficient of variation of glycaemia, mean amplitude of glycaemic excursions (MAGE), detrended fluctuation analysis (DFA), % of time with glycaemia under 6.1 mmol/L (TU6.1), area over 7.8 mmol/L (AO7.8) and time in range. We analysed the correlation between changes in both anthropometric (body mass index, BMI and waist circumference) and metabolic (fasting blood glucose, FBG and HbA1c) variables and dynamical CGM-derived metrics and searched for variables in the basal CGM that could predict successful outcomes. RESULTS: There was a poor correlation between anthropometric and metabolic outcomes. There was a strong correlation between anthropometric changes and changes in glycaemic tonic control (∆BMI-∆TU6.1: rho = - 0.67, P < .01) and between metabolic outcomes and glycaemic phasic control (∆FBG-∆AO7.8: r = .60, P < .01). Basal AO7.8 was a powerful predictor of successful metabolic outcome (0.85 in patients with AO7.8 above the median vs 0.31 in patients with AO7.8 below the median: Chi-squared = 5.67, P = .02). CONCLUSIONS: In our population, anthropometric outcomes of DJBL correlate with improvement in tonic control of glycaemia, while metabolic outcomes correlate preferentially with improvement in phasic control. Assessment of basal phasic control may help in candidate profiling for DJBL implantation.
Department of Cybernetics Czech Technical University Prague Prague Czech Republic
Department of Internal Medicine Hospital Universitario 12 de Octubre Madrid Spain
Department of Internal Medicine Hospital Universitario de Móstoles Madrid Spain
Technological Institute of Informatics Universitat Politècnica de València Alcoi Spain
References provided by Crossref.org
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- $a BACKGROUND: The endoscopically implanted duodenal-jejunal bypass liner (DJBL) is an attractive alternative to bariatric surgery for obese diabetic patients. This article aims to study dynamical aspects of the glycaemic profile that may influence DJBL effects. METHODS: Thirty patients underwent DJBL implantation and were followed for 10 months. Continuous glucose monitoring (CGM) was performed before implantation and at month 10. Dynamical variables from CGM were measured: coefficient of variation of glycaemia, mean amplitude of glycaemic excursions (MAGE), detrended fluctuation analysis (DFA), % of time with glycaemia under 6.1 mmol/L (TU6.1), area over 7.8 mmol/L (AO7.8) and time in range. We analysed the correlation between changes in both anthropometric (body mass index, BMI and waist circumference) and metabolic (fasting blood glucose, FBG and HbA1c) variables and dynamical CGM-derived metrics and searched for variables in the basal CGM that could predict successful outcomes. RESULTS: There was a poor correlation between anthropometric and metabolic outcomes. There was a strong correlation between anthropometric changes and changes in glycaemic tonic control (∆BMI-∆TU6.1: rho = - 0.67, P < .01) and between metabolic outcomes and glycaemic phasic control (∆FBG-∆AO7.8: r = .60, P < .01). Basal AO7.8 was a powerful predictor of successful metabolic outcome (0.85 in patients with AO7.8 above the median vs 0.31 in patients with AO7.8 below the median: Chi-squared = 5.67, P = .02). CONCLUSIONS: In our population, anthropometric outcomes of DJBL correlate with improvement in tonic control of glycaemia, while metabolic outcomes correlate preferentially with improvement in phasic control. Assessment of basal phasic control may help in candidate profiling for DJBL implantation.
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