Computational modelling of self-reported dietary carbohydrate intake on glucose concentrations in patients undergoing Roux-en-Y gastric bypass versus one-anastomosis gastric bypass.


Journal

Annals of medicine
ISSN: 1365-2060
Titre abrégé: Ann Med
Pays: England
ID NLM: 8906388

Informations de publication

Date de publication:
12 2021
Historique:
entrez: 29 10 2021
pubmed: 30 10 2021
medline: 21 12 2021
Statut: ppublish

Résumé

Our aim was to investigate in a real-life setting the use of machine learning for modelling the postprandial glucose concentrations in morbidly obese patients undergoing Roux-en-Y gastric bypass (RYGB) or one-anastomosis gastric bypass (OAGB). As part of the prospective randomized open-label trial (RYSA), data from obese (BMI ≥35 kg/m Altogether, 10 participants underwent RYGB and 7 participants OAGB surgeries. The glucose concentrations and carbohydrate intakes were reduced postoperatively in both groups. The relative time spent in hypoglycaemia increased regardless of the operation (RYGB, from 9.2 to 28.2%; OAGB, from 1.8 to 37.7%). Postoperatively, we observed an increase in the height of the fitted response curve and a reduction in its width, suggesting that the same amount of carbohydrates caused a larger increase in the postprandial glucose response and that the clearance of the meal-derived blood glucose was faster, with no clinically meaningful differences between the surgeries. A detailed analysis of the glycaemic responses using food diaries has previously been difficult because of the noisy meal data. The utilized machine learning model resolved this by modelling the uncertainty in meal times. Such an approach is likely also applicable in other applications involving dietary data. A marked reduction in overall glycaemia, increase in postprandial glucose response, and rapid glucose clearance from the circulation immediately after surgery are evident after both RYGB and OAGB. Whether nondiabetic individuals would benefit from monitoring the post-surgery hypoglycaemias and the potential to prevent them by dietary means should be investigated.KEY MESSAGESThe use of a novel machine learning model was applicable for combining patient-reported data and time-series data in this clinical study.Marked increase in postprandial glucose concentrations and rapid glucose clearance were observed after both Roux-en-Y gastric bypass and one-anastomosis gastric bypass surgeries.Whether nondiabetic individuals would benefit from monitoring the post-surgery hypoglycaemias and the potential to prevent them by dietary means should be investigated.

Identifiants

pubmed: 34714211
doi: 10.1080/07853890.2021.1964035
pmc: PMC8567939
doi:

Substances chimiques

Blood Glucose 0
Dietary Carbohydrates 0

Types de publication

Journal Article Randomized Controlled Trial Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1885-1895

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Auteurs

Reza A Ashrafi (RA)

Department of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Helsinki, Finland.

Aila J Ahola (AJ)

Faculty of Medicine, Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland.
Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.
Department of Nephrology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland.

Milla Rosengård-Bärlund (M)

Obesity Center, Endocrinology, Abdominal Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.

Tuure Saarinen (T)

Faculty of Medicine, Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland.
Department of Gastrointestinal Surgery, Abdominal Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.

Sini Heinonen (S)

Faculty of Medicine, Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland.

Anne Juuti (A)

Department of Gastrointestinal Surgery, Abdominal Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.

Pekka Marttinen (P)

Department of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Helsinki, Finland.

Kirsi H Pietiläinen (KH)

Faculty of Medicine, Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland.
Obesity Center, Endocrinology, Abdominal Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.

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