International consensus on the diagnosis and management of dumping syndrome.
Emidio ScarpelliniJoris ArtsGeorge KaramanolisAnna LaureniusWalter SiquiniHidekazu SuzukiAndrew UklejaAndre Van BeekTim VanuytselSerhat BorEugene P CeppaCarlo Di LorenzoMarloes EmousHeinz HammerPer HellströmMartine LavilleLars LundellAd MascleePatrick RitzJan TackPublished in: Nature reviews. Endocrinology (2020)
Dumping syndrome is a common but underdiagnosed complication of gastric and oesophageal surgery. We initiated a Delphi consensus process with international multidisciplinary experts. We defined the scope, proposed statements and searched electronic databases to survey the literature. Eighteen experts participated in the literature summary and voting process evaluating 62 statements. We evaluated the quality of evidence using grading of recommendations assessment, development and evaluation (GRADE) criteria. Consensus (defined as >80% agreement) was reached for 33 of 62 statements, including the definition and symptom profile of dumping syndrome and its effect on quality of life. The panel agreed on the pathophysiological relevance of rapid passage of nutrients to the small bowel, on the role of decreased gastric volume capacity and release of glucagon-like peptide 1. Symptom recognition is crucial, and the modified oral glucose tolerance test, but not gastric emptying testing, is useful for diagnosis. An increase in haematocrit >3% or in pulse rate >10 bpm 30 min after the start of the glucose intake are diagnostic of early dumping syndrome, and a nadir hypoglycaemia level <50 mg/dl is diagnostic of late dumping syndrome. Dietary adjustment is the agreed first treatment step; acarbose is effective for late dumping syndrome symptoms and somatostatin analogues are preferred for patients who do not respond to diet adjustments and acarbose.
Keyphrases
- case report
- systematic review
- minimally invasive
- clinical practice
- small bowel
- physical activity
- skeletal muscle
- adipose tissue
- cross sectional
- body mass index
- coronary artery disease
- atrial fibrillation
- machine learning
- heavy metals
- artificial intelligence
- big data
- sleep quality
- smoking cessation
- acute coronary syndrome