Abstract
Our aim was to assess the potential of flash glucose monitoring (FGM) for diagnostic workup of suspected post-bariatric hypoglycaemia (PBH). Patients (N = 13) with suspected PBH underwent a food and symptoms diary (FSD) record along with FGM over 14 days. Targeted data analysis confirmed the occurrence of low glucose events in parallel to meal-triggered symptoms. Glycaemic variability, as assessed by Mean Absolute Glucose change (MAG change), was increased, while a higher risk of glycaemic excursions towards both hyper and hypoglycaemia (ADRRFGMGT) was observed in those with more frequent and severe hypoglycaemia. The herein described hypoglycaemia risk index (LBGIFGMGT) with a cut-off value of 4.6 showed to have 100% sensitivity and 100% specificity for PBH. This pilot proof-of-concept study highlighted that FSD coupled with FGM followed by targeted data analysis, provides relevant insights towards PBH diagnosis and grading in a user-friendly and easy to implement study protocol. Furthermore, LBGIFGMGT demonstrated to be an excellent index for PBH diagnosis. The unexpected improvement of glucose profile noticed along the monitoring time also unravels a possible application for PBH management.
Highlights
The only consensus is that hypoglycaemia as cause of patient symptoms must be confirmed in accordance to the Whipple triad[8] and other endocrine and non-endocrine causes for hypoglycaemia, including insulinoma and glucose lowering drugs, should be ruled out in patients with past-medical history of bariatric surgery before assuming the diagnosis of PBH
Since patients typically present with normal fasting glucose and postprandial hypoglycaemia that occurs most often 60 to 180 min after a m eal[8,14], the use of provocative tests with oral g lucose[7] or liquid[13] and even solid[19] mixed meals as tools to diagnose PBH has been proposed. These provocative tests represent an artificial scenario and a positive test with reactive hypoglycaemia is often observed in post-bariatric patients without further evidence of the condition, overestimating PBH diagnosis[8]
The original risk analysis function used to compute these indexes was adjusted to the specific characteristics of the FGM system used. This classic function (Eq (1)) was originally modelled using data from patients with diabetes assessed with glucose meters with detection ranges distinct from the currently used FGM s ystem[30,42]
Summary
Our aim was to assess the potential of flash glucose monitoring (FGM) for diagnostic workup of suspected post-bariatric hypoglycaemia (PBH). Our aim was to assess the potential for the use of flash glucose monitoring (FGM) with targeted data analysis in the clinical workup of patients with PBH, based on the outcomes of its implementation in a pilot proof-ofconcept study
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