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Enregistrement W2139336719 · doi:10.1038/oby.2011.182

Bypass of Metabolic Diseases With Surgery

2011· letter· en· W2139336719 sur OpenAlexaboutno aff
G. Lynis Dohm, Walter J. Pories

Notice bibliographique

RevueObesity · 2011
Typeletter
Langueen
DomaineMedicine
ThématiqueBariatric Surgery and Outcomes
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineGastric bypass surgeryInsulin resistanceDiabetes mellitusBypass surgeryInternal medicineWeight lossCoronary artery bypass surgerySurgeryObesityInsulinGastroenterologyGastric bypassArteryEndocrinology

Résumé

récupéré en direct d'OpenAlex

Many reports have now confirmed and expanded on our early observation that approximately 80% of severely obese patients experience remission of type 2 diabetes mellitus (T2DM) and significantly lower mortality rates after Roux-en-Y gastric bypass surgery (1,2). Three large epidemiological studies in Canada, Sweden, and Utah reported decreased mortality rates for obese patients who underwent gastric bypass surgery (3,45). In the Utah study, a 7.1-year follow-up of patients demonstrated that mortality in the surgery group decreased 56% for coronary artery disease, 92% for T2DM, and 60% for cancer, as compared with a matched control group that did not have surgery. In this issue of Obesity, Promintzer-Schifferl et al. report the results of a study in which they sought to elucidate the mechanism(s) that underlie the amazing beneficial effects of the gastric bypass surgery. They studied a group of severely obese patients before surgery and again 7 months after gastric bypass. Importantly, two control groups were used for comparison: a lean group and a group of individuals matched to the experimental postsurgery BMI. The tests performed were an oral glucose-tolerance test and a hyperinsulinemic-isoglycemic-clamp test. Improvements in peripheral insulin sensitivity were minor, whereas the hepatic insulin-resistance index was completely normalized. Interestingly, insulin secretion was elevated after surgery and was greater than in either of the control groups (6). Although changes in insulin secretion and insulin sensitivity after gastric bypass surgery are certainly interesting and important, it is difficult to directly connect these results to improvements in diseases as disparate as T2DM, hypertension, coronary artery disease, nonalcoholic steatohepatitis, and cancer. One straightforward explanation for such changes might be that the remission of these diseases, often lumped together as a “metabolic syndrome,” is due to the weight loss induced by bariatric surgery. This conclusion would be supported by data reported by Adams et al., who found that the beneficial changes in almost all quantitative variables correlated significantly with the decrease in BMI (7). The problem with the explanation that the remission of T2DM is a result of weight loss is that the remission of diabetes occurs rapidly – within days after surgery – before there is significant weight loss (8). In addition, the remission of diabetes after gastric bypass is greater than in restrictive procedures such as gastric band surgery (9) and occurs even when there is no weight loss, as in duodenojejunal bypasses performed on lean individuals (10). The weight-independent effects of gastric bypass surgery have led to the hypothesis that exclusion of food from the lower stomach and foregut has metabolic effects that may be related to gut-derived factors that cause or reverse insulin resistance and/or insulin secretion. A better argument might be that the metabolic changes that occur after gastric bypass surgery are due to a correction of the constant, chronic hyperinsulinemia of T2DM with the restoration of first-phase insulin secretion; i.e., the ability to respond to the intake of a meal is improved by a lower insulin baseline. This important correction is shown in the data of Promintzer-Schifferl et al., who found that fasting insulin decreased from 28 μU/ml before surgery to 10 μU/ml in the postsurgery stage. The postsurgery insulin values were very much like those of lean patients, which is consistent with our studies. The increase in insulin secretion after gastric bypass reported by Promintzer-Schifferl et al. is most likely attributable to a combination of the lower baseline insulin before the glucose load and a substantial stimulatory effect of the incretin GLP-1. Correction of hyperinsulinemia and resolution of insulin resistance, which has long presented an unresolved chicken-and-egg dilemma, now seems to point far more convincingly to abnormally high basal insulin levels as the initial, key defect. Hyperinsulinemia does cause insulin resistance, probably through serine phosphorylation of IRS-1, and lowering baseline insulin would clearly have a beneficial effect on the ability of liver and muscle to respond to a rise in insulin in response to glucose or a meal. Correction of hyperinsulinemia could thus be the mechanism for a reduction in the mortality due to diabetes, heart disease and cancer in gastric bypass patients. Given that insulin is a lipogenic hormone, high baseline insulin would likely be a factor in causing dyslipidemia. The correction of plasma lipids after surgery could be due to lower fasting insulin, and this may play a role in reduced atherosclerosis. Likewise, insulin is known to act as a growth factor, possibly through the IGF-1 receptor, and could thus play a role in the elevated cancer incidence observed with obesity. The dramatic beneficial effects of gastric bypass surgery on serious diseases highlight the need for further research into the mechanism(s) involved. The results of Promintzer-Schifferl et al. add to our knowledge base. However, it is our opinion that one avenue of future research should be a focus on the mechanism that regulates “baseline” insulin and how gastric bypass is able to correct hyperinsulinemia. G.L.D. and W.J.P. both receive monetary support from GlaxoSmithKline and J ohnson & Johnson.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,431
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,024
Tête enseignante GPT0,225
Écart entre enseignants0,202 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2011
Routes d'admission1
Résumé présentoui

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