Dataset Information

Circulating cytokines in predicting development of severe acute pancreatitis.

ABSTRACT:

Introduction

Severe acute pancreatitis (AP) is associated with high morbidity and mortality. Early prediction of severe AP is needed to improve patient outcomes. The aim of the present study was to find novel cytokines or combinations of cytokines that can be used for the early identification of patients with AP at risk for severe disease.

Methods

We performed a prospective study of 163 nonconsecutive patients with AP, of whom 25 had severe AP according to the revised Atlanta criteria. Admission serum levels of 48 cytokines and growth factors were determined using Bio-Plex Pro Human Cytokine Assay 21-plex and 27-plex magnetic bead suspension panels. Admission plasma levels of C-reactive protein (CRP), creatinine and calcium were measured for comparison. In subgroup analyses, we assessed the cytokine profiles of patients with severe AP (n = 14) who did not have organ dysfunction (OD) upon admission (modified Marshall score <2).

Results

Of 14 cytokines elevated in the severe AP group, interleukin 6 (IL-6) and hepatocyte growth factor (HGF) levels were independent prognostic markers of severe AP. IL-6, HGF and a combination of them predicted severe AP with sensitivities of 56.0%, 60.0% and 72.0%, respectively, and specificities of 90.6%, 92.8% and 89.9%, respectively. The corresponding positive likelihood ratio (LR+) values were 5.9, 8.3 and 7.1, respectively. The predictive values of CRP, creatinine and calcium were comparable to those of the cytokines. In subgroup analyses of patients with severe AP and without OD upon admission, we found that IL-8, HGF and granulocyte colony-stimulating factor (G-CSF) levels predicted the development of severe AP, with G-CSF being the most accurate cytokine at a sensitivity of 35.7%, a specificity of 96.1% and a LR+ of 9.1.

Conclusions

IL-6 and HGF levels upon admission have prognostic value for severe AP which is similar to levels of CRP, creatinine and calcium. Although IL-6 and HGF, as either single or combined markers, were not perfect in identifying patients at risk for severe AP, the possibility that combining them with novel prognostic markers other than cytokines might improve prognostic accuracy needs to be studied. The accuracy of IL-8, HGF and G-CSF levels in predicting severe AP in patients without clinical signs of OD upon admission warrants larger studies.

SUBMITTER: Nieminen A

PROVIDER: S-EPMC4095695 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Circulating cytokines in predicting development of severe acute pancreatitis.

Nieminen Anne A Maksimow Mikael M Mentula Panu P Kyhälä Lea L Kylänpää Leena L Puolakkainen Pauli P Kemppainen Esko E Repo Heikki H Salmi Marko M

Critical care (London, England) 20140521 3

<h4>Introduction</h4>Severe acute pancreatitis (AP) is associated with high morbidity and mortality. Early prediction of severe AP is needed to improve patient outcomes. The aim of the present study was to find novel cytokines or combinations of cytokines that can be used for the early identification of patients with AP at risk for severe disease.<h4>Methods</h4>We performed a prospective study of 163 nonconsecutive patients with AP, of whom 25 had severe AP according to the revised Atlanta crit ...[more]

PMID: 24886762

Similar Datasets

Project description:Background and aimsThis study aimed to develop an interpretable random forest model for predicting severe acute pancreatitis (SAP).MethodsClinical and laboratory data of 648 patients with acute pancreatitis were retrospectively reviewed and randomly assigned to the training set and test set in a 3:1 ratio. Univariate analysis was used to select candidate predictors for the SAP. Random forest (RF) and logistic regression (LR) models were developed on the training sample. The prediction models were then applied to the test sample. The performance of the risk models was measured by calculating the area under the receiver operating characteristic (ROC) curves (AUC) and area under precision recall curve. We provide visualized interpretation by using local interpretable model-agnostic explanations (LIME).ResultsThe LR model was developed to predict SAP as the following function: -1.10-0.13×albumin (g/L) + 0.016 × serum creatinine (μmol/L) + 0.14 × glucose (mmol/L) + 1.63 × pleural effusion (0/1)(No/Yes). The coefficients of this formula were utilized to build a nomogram. The RF model consists of 16 variables identified by univariate analysis. It was developed and validated by a tenfold cross-validation on the training sample. Variables importance analysis suggested that blood urea nitrogen, serum creatinine, albumin, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, calcium, and glucose were the most important seven predictors of SAP. The AUCs of RF model in tenfold cross-validation of the training set and the test set was 0.89 and 0.96, respectively. Both the area under precision recall curve and the diagnostic accuracy of the RF model were higher than that of both the LR model and the BISAP score. LIME plots were used to explain individualized prediction of the RF model.ConclusionsAn interpretable RF model exhibited the highest discriminatory performance in predicting SAP. Interpretation with LIME plots could be useful for individualized prediction in a clinical setting. A nomogram consisting of albumin, serum creatinine, glucose, and pleural effusion was useful for prediction of SAP.

Project description:The incidence of hypertriglyceridemia induced acute pancreatitis (HTAP) continues to rise in China. It has systemic complications and high mortality, making the early assessment of the severity of this disease even more important. Circulating microRNAs (miRNAs) could be novel, non-invasive biomarkers for disease progression judgment. This study aimed to identify the potential role of serum miRNAs as novel biomarkers of HTAP progression. HTAP patients were divided into two groups: moderately severe (HTMSAP) and severe (HTSAP), healthy people were used as control group. The serum miRNA expression profiles of these three groups were determined by microarray and verified by qRT-PCR. The functions and pathways of the targeted genes of deregulated miRNAs were predicted, using bioinformatics analysis; miRNA-mRNA network was generated. Moreover, the correlation between miR-181a-5p and pancreatitis metabolism related substances were studied and the serum concentration of inflammatory cytokines and miRNAs at different time points during the MSAP and SAP were investigated, respectively. Finally, the receiver operating characteristic (ROC) curve of miRNAs was studied. Significant changes in the serum concentration of the following miRNAs of HTAP patients (P<0.05) were discovered: miR24-3p, 361-5p, 1246, and 222-3p (constantly upregulated), and 181a-5p (constantly downregulated) (P<0.05). Bioinformatics analysis predicted that 13 GOs and 36 pathways regulated by overlap miRNAs were involved in glucose, fat, calcium (Ca++), and insulin metabolism (P<0.001). miRNA-mRNA network revealed that the overlap miRNAs targeted genes participating in pancreas metabolism and miR-181a-5p, the only downregulated miRNA, had good negative correlation with triglyceride (TG), total cholesterol (TC), and fast blood glucose (FBG), but a positive correlation with Ca++. When compared with inflammatory cytokines, the changes of all five overlap miRNAs were more stable. It was found that when used for evaluating the progression of HTAP, miRNAs showed good AUC. These data suggested that serum miRNAs have the potential to be excellent HTAP biomarkers.

Project description:Ferroptosis is a newly recognized form of regulatory cell death characterized by severe lipid peroxidation triggered by iron overload and the production of reactive oxygen species (ROS). However, the role of ferroptosis in severe acute pancreatitis(SAP) has not been fully elucidated. We established four severe acute pancreatitis models of rats including the sham control group, the SAP group, the Fer -1-treated SAP (SAP + Fer-1) group, the 3-MA-treated SAP (SAP + 3-MA) group. The SAP group was induced by retrograde injection of sodium taurocholate into the pancreatic duct. The other two groups were intraperitoneally injected with ferroptosis inhibitor (Fer-1) and autophagy inhibitor (3-MA), respectively. The model of severe acute pancreatitis with amylase crest-related inflammatory factors was successfully established. Then we detected ferroptosis (GPX4, SLC7A1 etc.) and autophagy-related factors (LC3II, p62 ect.) to further clarify the relationship between ferroptosis and autophagy. Our study found that ferroptosis occurs during the development of SAP, such as iron and lipid peroxidation in pancreatic tissues, decreased levels of reduced glutathione peroxidase 4 (GPX 4) and glutathione (GSH), and increased malondialdehyde(MDA) and significant mitochondrial damage. In addition, ferroptosis related proteins such as GPX4, solute carrier family 7 member 11(SLC7A11) and ferritin heavy chain 1(FTH1) were significantly decreased. Next, the pathogenesis of ferroptosis in SAP was studied. First, treatment with the ferroptosis inhibitor ferrostatin-1(Fer-1) significantly alleviated ferroptosis in SAP. Interestingly, autophagy occurs during the pathogenesis of SAP, and autophagy promotes the occurrence of ferroptosis in SAP. Moreover, 3-methyladenine (3-MA) inhibition of autophagy can significantly reduce iron overload and ferroptosis in SAP. Our results suggest that ferroptosis is a novel pathogenesis of SAP and is dependent on autophagy. This study provides a new theoretical basis for the study of SAP.

Dataset Information

Circulating cytokines in predicting development of severe acute pancreatitis.

Introduction

Methods

Results

Conclusions

Publications

Circulating cytokines in predicting development of severe acute pancreatitis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets