Towards reducing the risk of new onset diabetes after pancreatitis

Jivanji, Chirag J.; Soo, Danielle; Petrov, Maxim S.

doi:10.23736/s1121-421x.16.02365-5

Cited by 7 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is far from being the case for DEP because it is typically diagnosed late and often misdiagnosed as type 2 diabetes (and sometimes as type 1 diabetes) (1). Given that DEP is characterised by a significantly poorer glycaemic control in the first few years after the diagnosis in comparison with type 2 diabetes and taking into account the well-known legacy effect of early glycaemic control on micro-and macrovascular complications and death, it is important to raise the awareness and early recognition of DEP (114). This underscores the need to offer appropriate management early in the course of DEP with a view to achieving nearnormal glycaemic profile soon after patients are diagnosed with diabetes and mitigating long-term risk for diabetic complications and mortality.…”

Section: Discussionmentioning

confidence: 99%

DIAGNOSIS OF ENDOCRINE DISEASE: Diagnosing and classifying diabetes in diseases of the exocrine pancreas

Petrov

Basina

2021

European Journal of Endocrinology

View full text Add to dashboard Cite

Diabetes in the setting of diseases of the exocrine pancreas has long existed as a known, but underdiagnosed or misdiagnosed, disorder. It currently finds itself in a state of taxonomic dereliction and requires a long overdue refurbishment. Correct conceptualisation is a key precondition for knowledge development in this disorder. This article lays out the epistemiological foundation for diabetes of the exocrine pancreas (DEP) and presents a synthesis of the current interdisciplinary discourse on diagnosing and classifying DEP. The diagnosis of DEP is generally based on the most up-to-date biochemical criteria endorsed by the American Diabetes Association and European Association for the Study of Diabetes. The presence of exocrine pancreatic dysfunction is not considered a mandatory diagnostic criterion for DEP but is rather a significant risk factor for developing DEP. DEP principally comprises post-pancreatitis diabetes mellitus, pancreatic cancer-related diabetes, and cystic fibrosis-related diabetes, which are mutually exclusive with autoimmune diabetes and type 2 diabetes. Other exclusions and stipulations apply. The DEP criteria will be instrumental in aiding optimal design and conduct of clinical studies, uniform collection of health utilisation data, meaningful comparison of scientific findings across countries, and clear communication among stakeholders (healthcare providers, patients, health regulatory authorities, pharmaceutical industry).

show abstract

Section: Discussionmentioning

confidence: 99%

DIAGNOSIS OF ENDOCRINE DISEASE: Diagnosing and classifying diabetes in diseases of the exocrine pancreas

Petrov

Basina

2021

European Journal of Endocrinology

View full text Add to dashboard Cite

show abstract

“…This type of diabetes is characterized by impaired endocrine and exocrine functions, including significant glycemic drift, frequent episodes of hypoglycemia (fragile diabetes) 10 , and impaired digestion and absorption of nutrients 12 , 13 . It seriously threatens human health and places a heavy burden on health care 14 , 15 .…”

Section: Introductionmentioning

confidence: 99%

Machine learning for post-acute pancreatitis diabetes mellitus prediction and personalized treatment recommendations

Zhang

Hou

et al. 2023

Sci Rep

View full text Add to dashboard Cite

Post-acute pancreatitis diabetes mellitus (PPDM-A) is the main component of pancreatic exocrine diabetes mellitus. Timely diagnosis of PPDM-A improves patient outcomes and the mitigation of burdens and costs. We aimed to determine risk factors prospectively and predictors of PPDM-A in China, focusing on giving personalized treatment recommendations. Here, we identify and evaluate the best set of predictors of PPDM-A prospectively using retrospective data from 820 patients with acute pancreatitis at four centers by machine learning approaches. We used the L1 regularized logistic regression model to diagnose early PPDM-A via nine clinical variables identified as the best predictors. The model performed well, obtaining the best AUC = 0.819 and F1 = 0.357 in the test set. We interpreted and personalized the model through nomograms and Shapley values. Our model can accurately predict the occurrence of PPDM-A based on just nine clinical pieces of information and allows for early intervention in potential PPDM-A patients through personalized analysis. Future retrospective and prospective studies with multicentre, large sample populations are needed to assess the actual clinical value of the model.

show abstract

Glucose Variability Measures as Predictors of Oral Feeding Intolerance in Acute Pancreatitis: A Prospective Pilot Study

et al. 2017

View full text Add to dashboard Cite

show abstract

Towards reducing the risk of new onset diabetes after pancreatitis

Cited by 7 publications

References 0 publications

DIAGNOSIS OF ENDOCRINE DISEASE: Diagnosing and classifying diabetes in diseases of the exocrine pancreas

DIAGNOSIS OF ENDOCRINE DISEASE: Diagnosing and classifying diabetes in diseases of the exocrine pancreas

Machine learning for post-acute pancreatitis diabetes mellitus prediction and personalized treatment recommendations

Glucose Variability Measures as Predictors of Oral Feeding Intolerance in Acute Pancreatitis: A Prospective Pilot Study

Contact Info

Product

Resources

About