Post‐pancreatitis diabetes mellitus is common in chronic pancreatitis and is associated with adverse outcomes

Dugic, Ana; Hagström, Hannes; Dahlman, Ingrid; Rutkowski, Wiktor; Daou, Diana; Kulinski, Paula; Löhr, Matthias; Vujasinović, Miroslav

doi:10.1002/ueg2.12344

Cited by 16 publications

(8 citation statements)

References 65 publications

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“… 11 Moreover, compared to comorbidity in CP‐T2D, patients with diabetes related to CP present a more aggressive phenotype (microangiopathy and infection) and higher need for glucose‐lowering treatment, and even patients who experience their first attack of pancreatitis may require long‐term management after being discharged from the hospital. 12 , 13 Taken together, CP and T2D exhibit a strong correlation during the progression of the disease. However, the shared signatures and underlying pathogenesis of comorbidity are still not fully understood.…”

Section: Introductionmentioning

confidence: 90%

“…Another study showed that the combination of CP and T2D can lead to a mutually aggravating process involving insulin resistance, chronic low‐intensity inflammation, and dyslipidemia 11 . Moreover, compared to comorbidity in CP‐T2D, patients with diabetes related to CP present a more aggressive phenotype (microangiopathy and infection) and higher need for glucose‐lowering treatment, and even patients who experience their first attack of pancreatitis may require long‐term management after being discharged from the hospital 12,13 . Taken together, CP and T2D exhibit a strong correlation during the progression of the disease.…”

Section: Introductionmentioning

confidence: 99%

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Transcriptomic analysis reveals the crosstalk between type 2 diabetes and chronic pancreatitis

Chen,

Hao,

Cong

et al. 2024

Health Science Reports

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Background and AimsMounting evidence highlights a strong association between chronic pancreatitis (CP) and type 2 diabetes (T2D), although the exact mechanism of interaction remains unclear. This study aimed to investigate the crosstalk genes and pathogenesis between CP and T2D.MethodsTranscriptomic gene expression profiles of CP and T2D were extracted from Gene Expression Omnibus, respectively, and the common differentially expressed genes (DEGs) were subsequently identified. Further analysis, such as Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein–protein interaction, transcription factors (TFs), microRNA (miRNAs), and candidate chemicals identification, was performed to explore the possible common signatures between the two diseases.ResultsIn total, we acquired 281 common DEGs by interacting CP and T2D datasets, and identified 10 hub genes using CytoHubba. GO and KEGG analyses revealed that endoplasmic reticulum stress and mitochondrial dysfunction were closely related to these common DEGs. Among the shared genes, EEF2, DLD, RAB5A, and SLC30A9 showed promising diagnostic value for both diseases based on receiver operating characteristic curve and precision‐recall curves. Additionally, we identified 16 key TFs and 16 miRNAs that were strongly correlated with the hub genes, which may serve as new molecular targets for CP and T2D. Finally, candidate chemicals that might become potential drugs for treating CP and T2D were screened out.ConclusionThis study provides evidence that there are shared genes and pathological signatures between CP and T2D. The genes EEF2, DLD, RAB5A, and SLC30A9 have been identified as having the highest diagnostic efficiency and could be served as biomarkers for these diseases, providing new insights into precise diagnosis and treatment for CP and T2D.

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Section: Introductionmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Transcriptomic analysis reveals the crosstalk between type 2 diabetes and chronic pancreatitis

Chen,

Hao,

Cong

et al. 2024

Health Science Reports

View full text Add to dashboard Cite

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“…The inclusion and exclusion criteria for PPDM-A group were as follows: inclusion criteria: (I) patients were diagnosed with diabetes mellitus >90 days after the date of first pancreatitis diagnosis ( 24 , 25 , 28 ); (II) upper abdominal CECT examinations performed within 7 days of the onset of AP; and (III) inpatients. Exclusion criteria: (I) having any history of diabetes; (II) elevated blood glucose during hospitalization; (III) high blood glucose within 90 days after discharge; (IV) acute onset of chronic pancreatitis; (V) cancer or severe chronic wasting diseases; (VI) loss to follow-up; (VII) unsatisfactory images or incomplete medical records; and (VIII) less than 18 years of age.…”

Section: Methodsmentioning

confidence: 99%

A radiomics model of contrast-enhanced computed tomography for predicting post-acute pancreatitis diabetes mellitus

Hu,

Yang,

Zeng

et al. 2024

Quant Imaging Med Surg

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Background Diabetes mellitus can occur after acute pancreatitis (AP), but the accurate quantitative methods to predict post-acute pancreatitis diabetes mellitus (PPDM-A) are lacking. This retrospective study aimed to establish a radiomics model based on contrast-enhanced computed tomography (CECT) for predicting PPDM-A. Methods A total of 374 patients with first-episode AP were retrospectively enrolled from two tertiary referral centers. There were 224 patients in the training cohort, 56 in the internal validation cohort, and 94 in the external validation cohort, and there were 86, 22, and 27 patients with PPDM-A in these cohorts, respectively. The clinical characteristics were collected from the hospital information system. A total of 2,398 radiomics features, including shape-based features, first-order histogram features, high order textural features, and transformed features, were extracted from the arterial- and venous-phase CECT images. Intraclass correlation coefficients were used to assess the intraobserver reliability and interobserver agreement. Random forest-based recursive feature elimination, collinearity analysis, and least absolute shrinkage and selection operator (LASSO) were used for selecting the final features. Three classification methods [eXtreme Gradient Boosting (XGBoost), Adaptive Boosting, and Decision Tree] were used to build three models and performances of the three models were compared. Each of the three classification methods were used to establish the clinical model, radiomics model, and combined model for predicting PPDM-A, resulting in a total of nine classifiers. The predictive performances of the models were evaluated by the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1-score. Results Eleven radiomics features were selected after a reproducibility test and dimensionality reduction. Among the three classification methods, the XGBoost classifier showed better and more consistent performances. The AUC of the XGBoost’s radiomics model to predict PPDM-A in the training, internal, and external cohorts was good (0.964, 0.901, and 0.857, respectively). The AUC of the XGBoost’s combined model to predict PPDM-A in the training, internal, and external cohorts was good (0.980, 0.901, and 0.882, respectively). The AUC of the XGBoost’s clinical model to predict PPDM-A in the training, internal, and external cohorts did not perform well (0.685, 0.733, and 0.619, respectively). In the external validation cohort, the AUC of the XGBoost’s radiomics model was significantly higher than that of the clinical model (0.857 vs. 0.619, P<0.001), but there was no significant difference between the combined and radiomics models (0.882 vs. 0.857, P=0.317). Conclusions The radiomics model based on CECT performs well and can be used as an earl...

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Comments on Post-pancreatitis diabetes mellitus is common in chronic pancreatitis and is associated with adverse outcomesDear Editors, We read with great interest the recently published study on postpancreatitis diabetes mellitus (PPDM) in chronic pancreatitis and its association with adverse outcomes. 1 The authors concluded that patients with PPDM have a higher frequency of clinical complications and are more commonly prescribed insulin and metformin. The study is valuable; however, we identified some points that require further clarification.

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confidence: 99%

Comments on Post‐pancreatitis diabetes mellitus is common in chronic pancreatitis and is associated with adverse outcomes

2023

UEG Journal

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R Comments on Post-pancreatitis diabetes mellitus is common in chronic pancreatitis and is associated with adverse outcomesDear Editors, We read with great interest the recently published study on postpancreatitis diabetes mellitus (PPDM) in chronic pancreatitis and its association with adverse outcomes. 1 The authors concluded that patients with PPDM have a higher frequency of clinical complications and are more commonly prescribed insulin and metformin. The study is valuable; however, we identified some points that require further clarification.

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Post‐pancreatitis diabetes mellitus is common in chronic pancreatitis and is associated with adverse outcomes

Cited by 16 publications

References 65 publications

Transcriptomic analysis reveals the crosstalk between type 2 diabetes and chronic pancreatitis

Transcriptomic analysis reveals the crosstalk between type 2 diabetes and chronic pancreatitis

A radiomics model of contrast-enhanced computed tomography for predicting post-acute pancreatitis diabetes mellitus

Comments on Post‐pancreatitis diabetes mellitus is common in chronic pancreatitis and is associated with adverse outcomes

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