scholarly journals Hypertriglyceridemia-induced acute pancreatitis with diabetic ketoacidosis: A rare presentation of type 1 diabetes mellitus

2017 ◽  
Vol 9 (04) ◽  
pp. 329-331 ◽  
Author(s):  
Prabhat Kumar ◽  
Abhishek Sakwariya ◽  
Amit Ranjan Sultania ◽  
Renu Dabas
Keyword(s):  
Diabetes Mellitus ◽  
Acute Pancreatitis ◽  
Type 1 Diabetes ◽  
Diabetic Ketoacidosis ◽  
Insulin Infusion ◽  
Rare Presentation ◽  
Chronic Hyperglycemia ◽  
Severe Hypertriglyceridemia ◽  
Peptide Level

AbstractDiabetic ketoacidosis (DKA) is a frequently encountered complication of diabetes mellitus. DKA is an insulin deficit state and results in moderate to severe hypertriglyceridemia (HTG). HTG is the third leading cause of acute pancreatitis (AP) and often goes unnoticed. The triad of DKA, HTG, and AP is rarely seen, and literature on the same is sparse. We report a case of AP which was due to DKA-induced secondary HTG in an adult with previously undiagnosed type 1 diabetes. His HbA1c was significantly raised, and C-peptide level was low, confirming chronic hyperglycemia. He was treated successfully with insulin infusion, intravenous crystalloid, and analgesics.

scholarly journals Severe dyslipidemia associated with diabetic ketoacidosis in newly diagnosed female of type 1 diabetes mellitus

2021 ◽  
Vol 2021 (10) ◽  
Author(s):  
Ahmad Chreitah ◽  
Kheria Hijazia ◽  
Leen Doya ◽  
Alaa Salloum
Keyword(s):  
Diabetes Mellitus ◽  
Acute Pancreatitis ◽  
Type 1 Diabetes ◽  
Type 1 Diabetes Mellitus ◽  
Diabetic Ketoacidosis ◽  
Rare Event ◽  
Newly Diagnosed ◽  
Severe Hypertriglyceridemia

ABSTRACT Diabetic ketoacidosis (DKA) is considered as a serious complication of type 1 diabetes mellitus in pediatrics. Severe dyslipidemia in DKA is a rare eventuality. We report on a 10-year-old female presented with severe DKA. The serum was lipemic with severe hypertriglyceridemia and hypercholesterolemia. Laboratory workup: the values of glycemia, sodium and HbA1c were misleading; a method of dilution was used to obtain the correct values. Triglyceride and cholesterol returned gradually to normal levels only with the management of DKA without any complication. Mild dyslipidemia is a common feature in DKA, but severe dyslipidemia is a very rare event whose pathophysiology is not completely elucidated. It needs close surveillance because it might be responsible for acute pancreatitis and lipidemia retinalis.

scholarly journals Severe Transient Hyperglycemia in a Prediabetic Patient during Mild Acute Pancreatitis

2015 ◽  
Vol 2015 ◽  
pp. 1-3 ◽  
Author(s):  
Aura Diana Reghina ◽  
Silvia Craciun ◽  
Simona Fica
Keyword(s):  
Diabetes Mellitus ◽  
Acute Pancreatitis ◽  
Insulin Treatment ◽  
Serum Lipase ◽  
Acute Hyperglycemia ◽  
Severe Hypertriglyceridemia ◽  
Peptide Level ◽  
Mild Acute Pancreatitis ◽  
Obese Male

A 30-year-old obese male patient had been diagnosed with diabetes mellitus due to acute hyperglycemia and ketonuria. He also presented with severe hypertriglyceridemia and high levels of serum lipase. He was initially misdiagnosed with type 1 diabetes and treated with insulin for one month. At two months from first presentation, pancreatic antibodies were negative, and the C-peptide level was normal. A1c level was 5.9% without insulin treatment. The association between diabetes mellitus and acute pancreatitis is well established. We reported a case of severe transient hyperglycemia during mild acute pancreatitis in a metabolically ill patient.

scholarly journals Diabetic Ketoacidosis Revealing a Severe Hypertriglyceridemia and Acute Pancreatitis in Type 1 Diabetes Mellitus

2019 ◽  
Vol 2019 ◽  
pp. 1-4
Author(s):  
Fatima Zahra Zaher ◽  
Imane Boubagura ◽  
Sana Rafi ◽  
Ghizlane Elmghari ◽  
Nawal Elansari
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Type 1 Diabetes Mellitus ◽  
Diabetic Ketoacidosis ◽  
Biological Evolution ◽  
Intravenous Insulin ◽  
Severe Hypertriglyceridemia ◽  
Metabolic Complication ◽  
Patients With Diabetes

Diabetic ketoacidosis (DKA) is a life-threatening acute metabolic complication occurring in patients with diabetes, especially in patients with type 1 diabetes (T1D), due to an insulin deficiency. Moderate hypertriglyceridemia is commonly observed in DKA but severe hypertriglyceridemia with a triglyceride level exceeding 10g/L is very rarely reported. We report a case of a 14-year-old boy who had type 1 diabetes for 4 years treated with insulin therapy, also having adrenal insufficiency treated with hydrocortisone who presented with ketoacidosis and excruciating abdominal pain. Investigations revealed hypertriglyceridemia at 64g/L, lipasemia at 1000 U/L, and stage E pancreatitis on abdominal CT. The patient was treated with intravenous insulin, rehydration, and fenofibrate with good clinical and biological evolution. Severe hypertriglyceridemia causing pancreatitis in type 1 diabetes mellitus is a rare but very serious complication of DKA in children.

scholarly journals A Comparison of Feature Selection and Forecasting Machine Learning Algorithms for Predicting Glycaemia in Type 1 Diabetes Mellitus

2021 ◽  
Vol 11 (4) ◽  
pp. 1742
Author(s):  
Ignacio Rodríguez-Rodríguez ◽  
José-Víctor Rodríguez ◽  
Wai Lok Woo ◽  
Bo Wei ◽  
Domingo-Javier Pardo-Quiles
Keyword(s):  
Diabetes Mellitus ◽  
Machine Learning ◽  
Type 1 Diabetes ◽  
Feature Selection ◽  
Blood Glucose ◽  
Type 1 Diabetes Mellitus ◽  
Support Vector ◽  
Chronic Hyperglycemia ◽  
Predictive Algorithms

Type 1 diabetes mellitus (DM1) is a metabolic disease derived from falls in pancreatic insulin production resulting in chronic hyperglycemia. DM1 subjects usually have to undertake a number of assessments of blood glucose levels every day, employing capillary glucometers for the monitoring of blood glucose dynamics. In recent years, advances in technology have allowed for the creation of revolutionary biosensors and continuous glucose monitoring (CGM) techniques. This has enabled the monitoring of a subject’s blood glucose level in real time. On the other hand, few attempts have been made to apply machine learning techniques to predicting glycaemia levels, but dealing with a database containing such a high level of variables is problematic. In this sense, to the best of the authors’ knowledge, the issues of proper feature selection (FS)—the stage before applying predictive algorithms—have not been subject to in-depth discussion and comparison in past research when it comes to forecasting glycaemia. Therefore, in order to assess how a proper FS stage could improve the accuracy of the glycaemia forecasted, this work has developed six FS techniques alongside four predictive algorithms, applying them to a full dataset of biomedical features related to glycaemia. These were harvested through a wide-ranging passive monitoring process involving 25 patients with DM1 in practical real-life scenarios. From the obtained results, we affirm that Random Forest (RF) as both predictive algorithm and FS strategy offers the best average performance (Root Median Square Error, RMSE = 18.54 mg/dL) throughout the 12 considered predictive horizons (up to 60 min in steps of 5 min), showing Support Vector Machines (SVM) to have the best accuracy as a forecasting algorithm when considering, in turn, the average of the six FS techniques applied (RMSE = 20.58 mg/dL).

MCP-1and IL-1β expression in the myocardia of two young patients with Type 1 diabetes mellitus and fatal diabetic ketoacidosis

2014 ◽  
Vol 96 (1) ◽  
pp. 71-79 ◽  
Author(s):  
Jianli Niu ◽  
M.G.F. Gilliland ◽  
Zhuqing Jin ◽  
Pappachan E. Kolattukudy ◽  
William H. Hoffman
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Type 1 Diabetes Mellitus ◽  
Diabetic Ketoacidosis ◽  
Young Patients
Sign in / Sign up

Export Citation Format

Share Document