Comparison of CGM-Derived Measures of Glycemic Variability Between Pancreatogenic Diabetes and Type 2 Diabetes Mellitus

Shivaprasad, C; Aiswarya, Yalamanchi; Shah, Kejal R.; Atluri, Sridevi; Anupam, Biswas; Barure, Ramdas; Gautham, Kolla; Premchander, Aarudhra

doi:10.1177/1932296819860133

Cited by 27 publications

(19 citation statements)

References 37 publications

(62 reference statements)

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“…To date, GV has mostly been investigated only as a risk factor for mortality in critically ill patients 21,22 . Further, high GV (assessed with the use of continuous glucose monitoring) has been shown to be significantly associated with the presence of diabetes in cross‐sectional studies in the setting of chronic pancreatitis 23,24 . However, changes in GV (and, by extension, possible usefulness of continuous glucose monitoring) in unselected AP patients is an unchartered territory.…”

Section: Discussionmentioning

confidence: 99%

Glucose variability during the early course of acute pancreatitis predicts two‐year probability of new‐onset diabetes: A prospective longitudinal cohort study

Bharmal

Cho

et al. 2022

UEG Journal

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Background Acute pancreatitis (AP) is the largest contributor to diabetes of the exocrine pancreas. However, there is no accurate predictor at the time of hospitalisation for AP to identify individuals at high risk for new‐onset diabetes. Objective To investigate the accuracy of indices of glucose variability (GV) during the early course of AP in predicting the glycated haemoglobin (HbA1c) trajectories during follow‐up. Methods This was a prospective longitudinal cohort study of patients without diabetes at the time of hospitalisation for AP. Fasting blood glucose was regularly measured over the first 72 h of hospital admission. The study endpoint was the HbA1c trajectories ‐ high‐increasing, moderate‐stable, normal‐stable ‐ over two years of follow‐up. Multinomial logistic regression analyses were conducted to investigate the associations between several common GV indices and the HbA1c trajectories, adjusting for covariates (age, sex, and body mass index). A sensitivity analysis constrained to patients with non‐necrotising AP was conducted. Results A total of 120 consecutive patients were studied. All patients in the high‐increasing HbA1c trajectory group had new‐onset diabetes at 18 and 24 months of follow‐up. Glycaemic lability index had the strongest significant direct association (adjusted odds ratio = 13.69; p = 0.040) with the high‐increasing HbA1c trajectory. High admission blood glucose, standard deviation of blood glucose, and average real variability significantly increased the patients' odds of taking the high‐increasing HbA1c trajectory by at least two‐times. Admission blood glucose, but not the other GV indices, had a significant direct association (adjusted odds ratio = 1.46; p = 0.034) with the moderate‐stable HbA1c trajectory. The above findings did not change materially in patients with non‐necrotising AP alone. Conclusions High GV during the early course of AP gives a prescient warning of worsening HbA1c pattern and new‐onset diabetes after hospital discharge. Determining GV during hospitalisation could be a relatively straightforward approach to early identification of individuals at high risk for new‐onset diabetes after AP.

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Section: Discussionmentioning

confidence: 99%

Glucose variability during the early course of acute pancreatitis predicts two‐year probability of new‐onset diabetes: A prospective longitudinal cohort study

Bharmal

Cho

et al. 2022

UEG Journal

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“…The present study represents an important expansion of our prior work on CGM-derived measures of glycemic variability in patients with T2D and FCPD. 23 In this study, we used CGM to assess hypoglycemic events and hypoglycemia-associated indices in patients with diabetes of the exocrine pancreas. We found that the majority of patients experienced hypoglycemic events with significant alterations in hypoglycemic indices.…”

Section: Discussionmentioning

confidence: 99%

Continuous Glucose Monitoring for the Detection of Hypoglycemia in Patients With Diabetes of the Exocrine Pancreas

Shivaprasad

Gautham

Shah

et al. 2020

J Diabetes Sci Technol

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Background: Detailed evaluations of hypoglycemia and associated indices based on continuous glucose monitoring (CGM) are limited in patients with diabetes of the exocrine pancreas. Our study sought to evaluate the frequency and pattern of hypoglycemic events and to investigate hypoglycemia-specific indices in this population. Methods: This was a cross-sectional study comprising 83 participants with diabetes of the exocrine pancreas. CGM and self-monitoring of blood glucose (SMBG) were performed on all participants for a minimum period of 72 hours. The frequency and pattern of hypoglycemic events, as well as hypoglycemia-related indices, were evaluated. Results: Hypoglycemia was detected in 90.4% of patients using CGM and 38.5% of patients using SMBG. Nocturnal hypoglycemic events were more frequent (1.9 episodes/patient) and prolonged (142 minutes) compared with day-time events (1.1 episodes/patient; 82.8 minutes, P < 0.05). The mean low blood glucose index was 2.1, and glycemic risk assessment diabetes equation hypoglycemia was 9.1%. The mean time spent below (TSB) <70 mg/dL was 9.2%, and TSB <54 mg/dL was 3.7%. The mean area under curve (AUC) <70 mg/dL was 1.7 ± 2.5 mg/dL/hour and AUC <54 mg/dL was 0.6 ± 1.3 mg/dL/hour. All of the CGM-derived hypoglycemic indices were significantly more deranged at night compared with during the day ( P < 0.05). Conclusion: Patients with diabetes of the exocrine pancreas have a high frequency of hypoglycemic episodes that are predominantly nocturnal. CGM is superior to SMBG in the detection of nocturnal and asymptomatic hypoglycemic episodes. CGM-derived hypoglycemic indices are beneficial in estimating the risk of hypoglycemia.

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“…CGM was carried out using the iPro®2 (Medtronic, MiniMed Northridge, CA, USA), which was placed on each participant's abdomen before lunch on the day before the test. The following CGM variables were calculated: daily mean blood glucose levels (24-hour MBG), 24-hour standard deviation of blood glucose (24-hour SDBG), and Mean Amplitude of Glucose Excursion (MAGE) [22]. MAGE is an index of glycemic variability calculated from the value larger than one standard deviation (SD) from the mean glycemic values ± SD.…”

Section: Continuous Glucose Monitoring (Cgm) Systemmentioning

confidence: 99%

“…MAGE is an index of glycemic variability calculated from the value larger than one standard deviation (SD) from the mean glycemic values ± SD. The other indexes of glycemic variability were calculated as follows; coefficient of variance (%CV) = SD/MBG×100, and J-index =0.001 ×(MBG+SD) 2 [22].…”

Section: Continuous Glucose Monitoring (Cgm) Systemmentioning

confidence: 99%

High β-Glucan Barley Improves Postprandial Hyperglycemia after Meal Loading in Patients with Type 2 Diabetes

Fuse¹,

Higa²,

Fujitani³

et al. 2021

austinjnutrmetab

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Objective: We investigated whether barley with a high β-glucan content (7.2 g per 100 g) improves postprandial plasma glucose levels and fluctuations using a meal tolerance test and Continuous Glucose Monitoring (CGM) in patients with type 2 diabetes. Methods: A meal tolerance test (500 kcal) was conducted using two types of test meals: one with white rice (WR diet) and one with white rice mixed 1:1 with high β-glucan-containing barley (BR diet). Both meals included the same side dish. Plasma glucose changes over 180 minutes were compared after ingestion of the test meals. In addition, participants wore a CGM device for the 2 study days, to measure the daily variations in glucose levels when the WR or BR diet as staple food was provided 3 times a day with the same side dish in both meals. Results: Twenty-nine patients with type 2 diabetes (age 52.5 ± 15.1 years, BMI 27.5 ± 4.7 kg/m2, HbA1c 8.1 ±1.8 %) were included in this study. The incremental area under the curve of plasma glucose levels after BR diet ingestion was significantly lower than that after WR diet ingestion (7934.0 ± 4151.2 vs 9434.0 ± 4701.2 mg·min/dL). CGM showed a 24-hour standard deviation of blood glucose after the BR diet was significantly lower than that after the WR diet. Conclusion: These results suggest that postprandial plasma glucose elevation and fluctuation in patients with type 2 diabetes are suppressed by adding high-β-glucan barley to white rice in meals.

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Comparison of CGM-Derived Measures of Glycemic Variability Between Pancreatogenic Diabetes and Type 2 Diabetes Mellitus

Cited by 27 publications

References 37 publications

Glucose variability during the early course of acute pancreatitis predicts two‐year probability of new‐onset diabetes: A prospective longitudinal cohort study

Glucose variability during the early course of acute pancreatitis predicts two‐year probability of new‐onset diabetes: A prospective longitudinal cohort study

Continuous Glucose Monitoring for the Detection of Hypoglycemia in Patients With Diabetes of the Exocrine Pancreas

High β-Glucan Barley Improves Postprandial Hyperglycemia after Meal Loading in Patients with Type 2 Diabetes

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