Ranson score to stratify severity in Acute Pancreatitis remains valid - Old is gold

Impact of metabolic syndrome components on clinical outcomes in hypertriglyceridemia-induced acute pancreatitis

BACKGROUND

The incidence of hypertriglyceridemia (HTG)-induced acute pancreatitis (AP) is steadily increasing in China, becoming the second leading cause of AP. Clinical complications and outcomes associated with HTG-AP are generally more severe than those seen in AP caused by other etiologies. HTG-AP is closely linked to metabolic dysfunction and frequently coexists with metabolic syndrome or its components. However, the impact of metabolic syndrome components on HTG-AP clinical outcomes remains unclear.

AIM

To investigate the impact of metabolic syndrome component burden on clinical outcomes in HTG-AP.

METHODS

In this retrospective study of 255 patients diagnosed with HTG-AP at the First Affiliated Hospital of Guangxi Medical University, we collected data on patient demographics, clinical scores, complications, and clinical outcomes. Subsequently, we analyzed the influence of the presence and number of individual metabolic syndrome components, including obesity, hyperglycemia, hypertension, and low high-density lipoprotein cholesterol (HDL-C), on the aforementioned parameters in HTG-AP patients.

RESULTS

This study found that metabolic syndrome components were associated with an increased risk of various complications in HTG-AP, with low HDL-C being the most significant risk factor for clinical outcomes. The risk of complications increased with the number of metabolic syndrome components. Adjusted for age and sex, patients with high-component metabolic syndrome had significantly higher risks of renal failure [odds ratio (OR) = 3.02, 95%CI: 1.12-8.11)], SAP (OR = 5.05, 95%CI: 2.04-12.49), and intensive care unit admission (OR = 6.41, 95%CI: 2.42-16.97) compared to those without metabolic syndrome.

CONCLUSION

The coexistence of multiple metabolic syndrome components can synergistically worsen the clinical course of HTG-AP, making it crucial to monitor these components for effective disease management.

Machine learning predicts acute respiratory failure in pancreatitis patients: A retrospective study

PURPOSE

The purpose of the research is to design an algorithm to predict the occurrence of acute respiratory failure (ARF) in patients with acute pancreatitis (AP).

METHODS

We collected data on patients with AP in the Medical Information Mart for Intensive Care IV database. The enrolled observations were randomly divided into a 70 % training cohort and a 30 % validation cohort, and the observations in the training cohort were divided into ARF and non-ARF groups. Feature engineering was conducted using random forest (RF) and least absolute shrinkage and selection operator (LASSO) methods in the training cohort. The model building included logistic regression (LR), decision tree (DT), k-nearest neighbours (KNN), naive bayes (NB) and extreme gradient boosting (XGBoost). Parameters for model evaluation include receiver operating characteristic (ROC) curve, precision-recall curve (PRC), calibration curves, positive predictive value (PPV), negative predictive value (NPV), true positive rate (TPR), true negative rate (TNR), accuracy (ACC) and F1 score.

RESULTS

Among 4527 patients, 445 patients (9.8 %) experienced ARF. Ca, ALB, GLR, WBC, AG and BUN have been included in the prediction model as features for predicting ARF. The AUC of XGBoost were 0.86 (95 %CI 0.84-0.88) and 0.87 (95 %CI 0.84-0.90) in the training and validation cohorts. In the training cohort, XGBoost demonstrates a true positive rate (TPR) of 0.662, a true negative rate (TNR) of 0.884, a positive predictive value (PPV) of 0.380, a negative predictive value (NPV) of 0.960, an accuracy (ACC) of 0.862, and an F1 score of 0.483. In the validation cohort, XGBoost shows a TPR of 0.620, a TNR of 0.895, a PPV of 0.399, an NPV of 0.955, an ACC of 0.867, and an F1 score of 0.486.

CONCLUSION

The XGBOOST model demonstrates good discriminatory ability, which enables clinicians to ascertain the probability of developing ARF in AP patients.

Kynurenine Pathway Dysregulation and Pain Perception in Acute Pancreatitis: Has the Connection Unraveled?

AIM

Tryptophan (TRP), an essential amino acid, undergoes catabolism through various pathways. Notably, the kynurenine pathway (KP), constituting one of these pathways, exhibits a unidirectional impact on immune response and energy metabolism. Nonetheless, its influence on pain sensation is characterized by biphasic dynamics. This study aims to scrutinize the influence of the KP pathway on pain sensation, particularly within the context of pancreatic inflammation.

METHODS

Our prospective case-control study involved individuals diagnosed with acute pancreatitis and a control group matched for gender and age. The patient cohort was subsequently subdivided into severe and non-severe subgroups. To assess metabolites within KP, two blood samples were collected from the patient cohort, one at the time of diagnosis and another during the recovery phase. Furthermore, for pain quantification, daily pain scores utilizing the Visual Analog Scale (VAS) were extracted from the patients' medical records.

RESULTS

The study incorporated 30 patients along with an equivalent number of controls. A noticeable distinction was evident between the patient and control groups, characterized by an increase in kynurenine levels and a decrease in the tryptophan/kynurenine ratio. Throughout the process of disease recovery, a uniform decrease was observed in all KP metabolites, excluding 3-Hydroxykynurenine. Elevated levels of Kynurenic acid (KYNA) were correlated with increased pain scores. Critically, no apparent distinctions in KP metabolites were discerned concerning pain severity in patients with comorbidities characterized by neural involvement.

CONCLUSION

Based on our results, the kynurenine pathway (KP) is activated in instances of acute pancreatitis. Elevated levels of KYNA were found to be associated with heightened pain scores. The operative stages within the KP responsible for pain modulation are impaired in cases characterized by neuropathy-induced pain sensation.

Development and validation of a nomogram combining pain score with laboratory indicators for predicting persistent organ failure in acute pancreatitis: a retrospective cohort study

Background

Acute pancreatitis is an inflammatory disease that can lead to persistent organ failure (POF), which is associated with increased morbidity and mortality. Early prediction of POF in AP can significantly improve patient outcomes.

Objective

To develop and validate a nomogram that combines pain score with laboratory indicators for predicting POF in patients with AP.

Methods

A retrospective cohort study was conducted, including patients diagnosed with AP. Pain score and laboratory indicators were collected within the first 24 h of admission. A nomogram was developed using logistic regression models and validated in a separate cohort.

Results

There were 807 patients in the training cohort and 375 patients in the internal validation cohort.Multivariate logistic regression demonstrated that pain score, serum creatinine, hematocrit, serum calcium, and serum albumin were independent risk factors for the incidence of POF in patients with AP. The area under the curve of the nomogram constructed from the above factors were 0.924, respectively. The model demonstrated good calibration and discrimination in both the development and validation cohorts.

Conclusion

The nomogram had a good performance in predicting POF in patients with AP and can be used to guide clinical decision-making.

Analysis of Risk Factors for Severe Acute Pancreatitis in the Early Period (<24 h) After Admission

BACKGROUND

Severe acute pancreatitis (SAP) has high mortality. Early identification of high-risk factors that may progress to SAP and active intervention measures may improve the prognosis of SAP patients.

OBJECTIVE

Clinical data within 24 h after admission were retrospectively analyzed to provide an evidence for early screening of high-risk factors in patients with SAP.

METHODS

A review of clinical data of acute pancreatitis patients from January 1, 2018, to December 31, 2022, was conducted. We compared the clinical data of SAP and non-SAP patients, and a multivariable logistic regression model was used to identify the independent predictors of SAP. The receiver operating characteristic (ROC) curve of SAP was drawn for continuous numerical variables to calculate the optimal clinical cutoff value of each variable, and the predictive value of each variable was compared by the area under the ROC curve.

RESULTS

Based on the multivariate logistic regression analysis of Age (odds ratio (OR), 1.032;95% confident interval (CI),1.018-1.046, p < 0.001), body mass index (BMI) (OR, 1.181; 95% CI,1.083-1.288, p < 0.001), Non-HTGAP (nonhypertriglyceridemic acute pancreatitis) (OR, 2.098; 95% CI,1.276-3.45, p = 0.003), white blood cell count (WBC) (OR,1.072; 95% CI,1.034-1.111, p < 0.001), procalcitonin (PCT) (OR, 1.060; 95% CI, 1.027-1.095, p < 0.001), serum calcium (Ca) (OR,0.121; 95% CI, 0.050-0.292, p < 0.001), computed tomography severity index (CTSI) ≥4 (OR,12.942;95% CI,7.267-23.049, p < 0.001) were identified as independent risk factors for SAP. The area under the ROC curve (AUC) and optimal CUT-OFF values of continuous numerical variables for predicting SAP were Age (0.6079,51.5), BMI (0.6,23.25), WBC (0.6701,14.565), PCT (0.7086, 0.5175), Ca (0.7787,1.965), respectively.

CONCLUSION

Age, BMI, non-HTGAP, WBC, PCT, serum Ca and CTSI≥4 have good predictive value for SAP.

Establishment and Validation of an Early Predictive Model for Severe Acute Pancreatitis

Objective

The purpose of this study is to establishment and validation of an early predictive model for severe acute pancreatitis (SAP).

Methods

From January 2015 to August 2022, 2986 AP patients admitted to Changsha Central Hospital were enrolled in this study. They were randomly divided into a modeling group (n = 2112) and a validation group (n = 874). In the modeling group, identify risk factors through logistic regression models and draw column charts. Use internal validation method to verify the accuracy of column chart prediction. Apply calibration curves to evaluate the consistency between nomograms and ideal observations. Draw a DCA curve to evaluate the net benefits of the prediction model.

Results

Nine variables including respiratory rate, heart rate, WBC, PDW, PT, SCR, AMY, CK, and TG are the risk factors for SAP. The column chart risk prediction model which was constructed based on these 9 independent factors has high prediction accuracy (modeling group AUC = 0.788, validation group AUC = 7.789). The calibration curve analysis shows that the prediction probabilities of the modeling and validation groups are consistent with the observation probabilities. By drawing a DCA curve, it shows that the model has a wide threshold range (0.01-0.88).

Conclusion

The study developed an intuitive nomogram containing readily available laboratory parameters to predict the incidence rate of SAP.

Predicting the severity of acute pancreatitis: Current approaches and future directions

Acute pancreatitis (AP) is a sudden-onset inflammatory disease of the pancreas. The severity of AP is classified into mild, moderate, and severe categories based on the presence and persistence of organ failure. Severe acute pancreatitis (SAP) can be associated with significant morbidity and mortality. It requires early recognition for appropriate timely management. Prognostic scores for predicting SAP incorporating many clinical, laboratory, and radiological parameters have been developed in the past. However, all of these prognostic scores have low positive predictive value for SAP and some of these scores require >24 h for assessment. There is a need to develop biomarkers that can accurately identify patients at risk for SAP early in the course of the presentation. In this review, we aim to provide a summary of the most commonly utilized prognostic scores for AP and discuss future directions.

Predictive value of the Ranson and BISAP scoring systems for the severity and prognosis of acute pancreatitis: A systematic review and meta-analysis

BACKGROUND

To systematically assess and compare the predictive value of the Ranson and Bedside Index of Severity in Acute Pancreatitis (BISAP) scoring systems for the severity and prognosis of acute pancreatitis (AP).

METHODS

PubMed, Embase, Cochrane Library, and Web of Science were systematically searched until February 15, 2023. Outcomes in this analysis included severity and prognosis [mortality, organ failure, pancreatic necrosis, and intensive care unit (ICU) admission]. The revised Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was used to evaluate the quality of diagnostic accuracy studies. The threshold effect was evaluated for each outcome. The sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristic (SROC) curve (AUC) as well as 95% confidence intervals (CI) were calculated. The DeLong test was used for AUC comparisons. For the outcome evaluated by over 9 studies, publication bias was assessed using the Deeks' funnel plot asymmetry test.

RESULTS

Totally 17 studies of 5476 AP patients were included. For severity, the pooled sensitivity of the Ranson and BISAP was 0.95 (95%CI: 0.87, 0.98) and 0.67 (95%CI: 0.27, 0.92); the pooled specificity of the Ranson and BISAP was 0.74 (0.52, 0.88) and 0.95 (95%CI: 0.85, 0.98); the pooled AUC of the Ranson and BISAP was 0.95 (95%CI: 0.93, 0.97) and 0.94 (95%CI: 0.92, 0.96) (P = 0.480). For mortality, the pooled sensitivity of the Ranson and BISAP was 0.89 (95%CI: 0.73, 0.96) and 0.77 (95%CI: 0.58, 0.89); the pooled specificity of the Ranson and BISAP was 0.79 (95%CI: 0.68, 0.87) and 0.90 (95%CI: 0.86, 0.93); the pooled AUC of the Ranson and BISAP was 0.91 (95%CI: 0.88, 0.93) and 0.92 (95%CI: 0.90, 0.94) (P = 0.480). For organ failure, the pooled sensitivity of the Ranson and BISAP was 0.84 (95%CI: 0.76, 0.90) and 0.78 (95%CI: 0.60, 0.90); the pooled specificity of the Ranson and BISAP was 0.84 (95%CI: 0.63, 0.94) and 0.90 (95%CI: 0.72, 0.97); the pooled AUC of the Ranson and BISAP was 0.86 (95%CI: 0.82, 0.88) and 0.90 (95%CI: 0.87, 0.93) (P = 0.110). For pancreatic necrosis, the pooled sensitivity of the Ranson and BISAP was 0.63 (95%CI: 0.35, 0.84) and 0.63 (95%CI: 0.23, 0.90); the pooled specificity of the Ranson and BISAP was 0.90 (95%CI: 0.77, 0.96) and 0.93 (95%CI: 0.89, 0.96); the pooled AUC of the Ranson and BISAP was 0.87 (95%CI: 0.84, 0.90) and 0.93 (95%CI: 0.91, 0.95) (P = 0.001). For ICU admission, the pooled sensitivity of the Ranson and BISAP was 0.86 (95%CI: 0.77, 0.92) and 0.63 (95%CI: 0.52, 0.73); the pooled specificity of the Ranson and BISAP was 0.58 (95%CI: 0.55, 0.61) and 0.84 (95%CI: 0.81, 0.86); the pooled AUC of the Ranson and BISAP was 0.92 (95%CI: 0.81, 1.00) and 0.86 (95%CI: 0.67, 1.00) (P = 0.592).

CONCLUSION

The Ranson score was an applicable tool for predicting severity and prognosis of AP patients with reliable diagnostic accuracy in resource and time-limited settings. Future large-scale studies are needed to verify the findings.

Nomogram for the prediction of infected pancreatic necrosis in moderately severe and severe acute pancreatitis

OBJECTIVES

As a serious complication of moderately severe acute pancreatitis (MSAP) and severe acute pancreatitis (SAP), infected pancreatic necrosis (IPN) can lead to a prolonged course of interventional therapy. Most predictive models designed to identify such patients are complex or lack validation. The aim of this study was to develop a predictive model for the early detection of IPN in MSAP and SAP.

METHODS

A total of 594 patients with MSAP or SAP were included in the study. To reduce dimensionality, least absolute shrinkage and selection operator regression analysis was used to screen potential predictive variables, a nomogram was then constructed using logistic regression analysis. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the discrimination, accuracy, and clinical efficacy of the model. External data were also obtained to further validate the constructed model.

RESULTS

There were 476, 118, and 82 patients in the training, internal validation, and external validation cohorts, respectively. Platelet count, hematocrit, albumin/globulin, severity of acute pancreatitis, and modified computed tomography severity index score were independent factors for predicting IPN in MSAP and SAP. The area under the ROC curves were 0.923, 0.940, and 0.817, respectively, in the three groups. There was a good consistency between the actual probabilities and the predicted probabilities. DCA revealed excellent clinical utility.

CONCLUSION

The constructed nomogram is a simple and feasible model that has good clinical predictive value and efficacy in clinical decision-making for IPN in MSAP and SAP.

Updated Review of Radiologic Imaging and Intervention for Acute Pancreatitis and Its Complications

This is a current update on radiologic imaging and intervention of acute pancreatitis and its complications. In this review, we define the various complications of acute pancreatitis, discuss the imaging findings, as well as the timing of when these complications occur. The various classification and scoring systems of acute pancreatitis are summarized. Advantages and disadvantages of the 3 primary radiologic imaging modalities are compared. We then discuss radiologic interventions for acute pancreatitis. These include diagnostic aspiration as well as percutaneous catheter drainage of fluid collections, abscesses, pseudocysts, and necrosis. Recommendations for when these interventions should be considered, as well as situations in which they are contraindicated are discussed. Fortunately, acute pancreatitis usually is mild; however, serious complications occur in 20%, and admission of patients to the intensive care unit (ICU) occurs in over 10%. In this paper, we will focus on the imaging and interventional radiologic aspects for the serious complications and patients admitted to the ICU.

High-density lipoprotein cholesterol level as an independent protective factor against aggravation of acute pancreatitis: a case-control study

Background and aims

At present, evidence on the association between high-density lipoprotein cholesterol (HDL-C) levels and aggravation of acute pancreatitis (AP) is limited. This study aimed to investigate the relationship between the lowest HDL-C level during intensive care units (ICU) stay and AP aggravation and to determine the optimum cutoff lowest HDL-C level.

Methods

Patients admitted to the ICU of the Shandong Provincial Hospital for AP from 2015 to 2021 were included. The lowest HDL-C level during ICU stay was set as the independent variable, and the progression or non-progression to severe AP (SAP) was set as the dependent variable. Univariate and multivariate analyses were performed to determine the relationship between the two variables, and receiver operating characteristic (ROC) curves were plotted to analyze the predictive ability of the lowest HDL-C level for progression to SAP.

Results

This study included 115 patients. The difference in the lowest HDL-C level between the SAP and moderately SAP groups was significant (P < 0.05). After adjusting for covariates, the lowest HDL-C level showed a negative correlation with the occurrence of SAP, with a relative risk of 0.897 (95% confidence interval: 0.827-0.973). The area under the ROC curve for prediction of AP aggravation by the lowest HDL-C level was 0.707, and the optimum cutoff lowest HDL-C level was 0.545 mmol/L.

Conclusion

No less than 0.545 mmol/L of the HDL-C level during ICU stay may be an independent protective factor for the aggravation of AP.

Unraveling the Metabolic Changes in Acute Pancreatitis: A Metabolomics-Based Approach for Etiological Differentiation and Acute Biomarker Discovery

Acute pancreatitis (AP) remains a challenging medical condition, where a deeper metabolic insight could pave the way for innovative treatments. This research harnessed serum metabolomics to discern potential diagnostic markers for AP and distinguish between its biliary (BAP) and alcohol-induced (AAP) forms. Leveraging high-performance liquid chromatography coupled with mass spectrometry, the metabolic signatures of 34 AP patients were contrasted against 26 healthy participants, and then between different etiologies of AP. The results identified metabolites primarily from glycerophospholipids, glycerolipids, fatty acyls, sterol lipids, and pteridines and derivative classes, with the Human Metabolome Database aiding in classification. Notably, these metabolites differentiated AP from healthy states with high AUROC values above 0.8. Another set of metabolites revealed differences between BAP and AAP, but these results were not as marked as the former. This lipidomic analysis provides an introduction to the metabolic landscape of acute pancreatitis, revealing changes in multiple lipid classes and metabolites and identifying these metabolites. Future research could add and discover new diagnostic biomarkers and therapeutic strategies enhancing the management of acute pancreatitis.

Low-grade inflammation for predicting severe acute pancreatitis in patients with hypertriglyceridemic acute pancreatitis

OBJECTIVES

We aimed to evaluate the association between low-grade inflammation (LGI) and the severity of hypertriglyceridemic acute pancreatitis (HTG-AP).

METHODS

We retrospectively reviewed 311 patients with HTG-AP who were admitted to the Department of Gastroenterology, Fujian Provincial Hospital between April 2012 and March 2021. Inpatient medical and radiological records were reviewed to collect the clinical manifestations, disease severity, and comorbidities. C-reactive protein (CRP) level, white blood cell (WBC) count, platelet (PLT) count, and neutrophil-to-lymphocyte ratio (NLR) were considered LGI components and were combined to calculate a standardized LGI score. The association between the LGI score and the severity of HTG-AP was analyzed using univariate and multivariate logistic regression analyses.

RESULTS

Of the 311 patients with HTG-AP, 47 (15.1%) had mild acute pancreatitis (MAP), 184 (59.2%) had moderately severe acute pancreatitis (MSAP), and 80 (25.7%) had severe acute pancreatitis (SAP), respectively. Patients with MSAP and SAP had a higher LGI score than those with MAP (1.50 vs -6.00, P < 0.001). Univariate logistic regression analysis revealed that patients with LGI scores in the fourth quartile were more likely to have MSAP and SAP (odds ratio [OR] 21.925, 95% confidence interval [CI] 5.014-95.867, P < 0.001). The multivariate logistic regression analysis confirmed that low calcium (OR 0.105, 95% CI 0.011-0.969, P = 0.047) and high LGI score (OR 1.253, 95% CI 1.066-1.473, P = 0.006) were associated with MSAP and SAP. When predicting the severity of acute pancreatitis, the LGI score had the highest area under the receiver operating characteristic (ROC) curve (0.7737) compared to its individual components.

CONCLUSION

An elevated LGI score was associated with a higher risk of SAP in patients with HTG-AP.

Establishment and Validation of a Nomogram Prediction Model for the Severe Acute Pancreatitis

Background

Severe acute pancreatitis (SAP) can progress to lung and kidney dysfunction, and blood clotting within 48 hours of its onset, and is associated with a high mortality rate. The aim of this study was to establish a reliable diagnostic prediction model for the early stage of severe pancreatitis.

Methods

The clinical data of patients diagnosed with acute pancreatitis from October 2017 to June 2022 at the Shangluo Central Hospital were collected. The risk factors were screened by least absolute shrinkage and selection operator (LASSO) regression analysis. A novel nomogram model was then established by multivariable logistic regression analysis.

Results

The data of 436 patients with acute pancreatitis, 45 (10.3%) patients had progressed to SAP. Through univariate and LASSO regression analyses, the neutrophils (P <0.001), albumin (P < 0.001), blood glucose (P < 0.001), serum calcium (P < 0.001), serum creatinine (P < 0.001), blood urea nitrogen (P < 0.001) and procalcitonin (P = 0.005) were identified as independent predictive factors for SAP. The nomogram built on the basis of these factors predicted SAP with sensitivity of 0.733, specificity of 0.9, positive predictive value of 0.458 and negative predictive value of 0.967. Furthermore, the concordance index of the nomogram reached 0.889 (95% CI, 0.837-0.941), and the area under the curve (AUC) in receiver operating characteristic curve (ROC) analysis was significantly higher than that of the APACHEII and ABISAP scoring systems. The established model was validated by plotting the clinical decision curve analysis (DCA) and clinical impact curve (CIC).

Conclusion

We established a nomogram to predict the progression of early acute pancreatitis to SAP with high discrimination and accuracy.

A modified Ranson score to predict disease severity, organ failure, pancreatic necrosis, and pancreatic infection in patients with acute pancreatitis

Background

Although there are several scoring systems currently used to predict the severity of acute pancreatitis, each of them has limitations. Determine the accuracy of a modified Ranson score in predicting disease severity and prognosis in patients with acute pancreatitis (AP).

Methods

AP patients admitted or transferred to our institution were allocated to a modeling group (n = 304) or a validation group (n = 192). A modified Ranson score was determined by excluding the fluid sequestration parameter and including the modified computed tomography severity index (CTSI). The diagnostic performance of the modified Ranson score was compared with the Ranson score, modified CTSI, and bedside index of severity in acute pancreatitis (BISAP) score in predicting disease severity, organ failure, pancreatic necrosis and pancreatic infection.

Results

The modified Ranson score had significantly better accuracy that the Ranson score in predicting all four outcome measures in the modeling group and in the validation group (all p < 0.05). For the modeling group the modified Ranson score had the best accuracy for predicting disease severity and organ failure, and second-best accuracy for predicting pancreatic necrosis and pancreatic infection. For the verification group, it had the best accuracy for predicting organ failure, second-best accuracy for predicting disease severity and pancreatic necrosis, and third-best accuracy for predicting pancreatic infection.

Conclusion

The modified Ranson score provided better accuracy than the Ranson score in predicting disease severity, organ failure, pancreatic necrosis and pancreatic infection. Relative to the other scoring systems, the modified Ranson system was superior in predicting organ failure.

Occam’s razor or Hickam’s dictum-COVID-19 is not a textbook aetiology of acute pancreatitis: A modified Naranjo Score appraisal

BACKGROUND

Acute pancreatitis (AP) is a disease spectrum ranging from mild to severe disease. During the coronavirus disease 2019 (COVID-19) pandemic, numerous reports of AP have been published, with most authors concluding a causal relationship between COVID-19 and AP. Retrospective case reports or small case series are unable to accurately determine the cause-effect relationship between COVID-19 and AP.

AIM

To establish whether COVID-19 is a cause of AP using the modified Naranjo scoring system.

METHODS

A systematic review was conducted on PubMed, World of Science and Embase for articles reporting COVID-19 and AP from inception to August 2021. Exclusion criteria were cases of AP which were not reported to be due to COVID-19 infection, age < 18 years old, review articles and retrospective cohort studies. The original 10-item Naranjo scoring system (total score 13) was devised to approximate the likelihood of a clinical presentation to be secondary to an adverse drug reaction. We modified the original scoring system into a 8-item modified Naranjo scoring system (total score 9) to determine the cause-effect relationship between COVID-19 and AP. A cumulative score was decided for each case presented in the included articles. Interpretation of the modified Naranjo scoring system is as follows: ≤ 3: Doubtful, 4-6: Possible, ≥ 7: Probable cause.

RESULTS

The initial search resulted in 909 articles, with 740 articles after removal of duplicates. A total of 67 articles were included in the final analysis, with 76 patients which had AP reported to be due to COVID-19. The mean age was 47.8 (range 18-94) years. Majority of patients (73.3%) had ≤ 7 d between onset of COVID-19 infection and diagnosis of AP. There were only 45 (59.2%) patients who had adequate investigations to rule out common aetiologies (gallstones, choledocholithiasis, alcohol, hypertriglyceridemia, hypercalcemia and trauma) of AP. Immunoglobulin G4 testing was conducted in 9 (13.5%) patients to rule out autoimmune AP. Only 5 (6.6%) patients underwent endoscopic ultrasound and/or magnetic resonance cholangiopancreatogram to rule out occult microlithiasis, pancreatic malignancy and pancreas divisum. None of the patients had other recently diagnosed viral infections apart from COVID-19 infection, or underwent genetic testing to rule out hereditary AP. There were 32 (42.1%), 39 (51.3%) and 5 (6.6%) patients with doubtful, possible, and probable cause-effect relationship respectively between COVID-19 and AP.

CONCLUSION

Current evidence is weak to establish a strong link between COVID-19 and AP. Investigations should be performed to rule out other causes of AP before establishing COVID-19 as an aetiology.

Acute pancreatitis due to hypertriglyceridemia: Plasmapheresis versus medical treatment

OBJECTIVE

Hypertriglyceridemia (HTG) is the third-most common cause of acute pancreatitis. Plasmapheresis is an extracorporeal treatment method used for treatment. This study aimed to investigate the efficacy of medical treatment and plasmapheresis in patients with acute pancreatitis due to HTG.

METHODS

This was a retrospective cross-sectional study. The patients were divided into two groups according to the treatment they received as those who received only medical treatment and those who performed plasmapheresis with medical treatment. According to the treatment received by the patients; clinical, demographic, and laboratory data, Ranson scores, and bedside index of severity in acute pancreatitis (BISAP) scores, decrease in triglyceride levels in 24 h, length of hospital stay, and outcomes were recorded.

RESULTS

Forty-seven patients were included in the study. The level of triglyceride decreases at the 24^th h was 59.7% ±17.3% in those who received medical treatment and was 70.4% ±15.1% in those who received plasmapheresis (P = 0.032). Receiver operating characteristic curve analysis was performed to predict the need for plasmapheresis treatment, area under the curve (AUC) value of the triglyceride level was the highest (AUC: 0.822, 95% confidence interval: [0.703-0.940]; P < 0.001), the sensitivity and specificity were 83.3% and 72.4%, respectively, and the cut-off value of triglyceride was accepted as 3079.5 mg/dL.

CONCLUSION

Plasma triglyceride levels and BISAP score on admission may help physicians to predict the need for plasmapheresis. Plasmapheresis helps to rapidly reduce triglyceride levels in patients with HTG-associated acute pancreatitis.

Acute Pancreatitis Severity Prediction: It Is Time to Use Artificial Intelligence

The clinical course of acute pancreatitis (AP) can be variable depending on the severity of the disease, and it is crucial to predict the probability of organ failure to initiate early adequate treatment and management. Therefore, possible high-risk patients should be admitted to a high-dependence unit. For risk assessment, we have three options: (1) There are univariate biochemical markers for predicting severe AP. One of their main characteristics is that the absence or excess of these factors affects the outcome of AP in a dose-dependent manner. Unfortunately, all of these parameters have low accuracy; therefore, they cannot be used in clinical settings. (2) Score systems have been developed to prognosticate severity by using 4-25 factors. They usually require multiple parameters that are not measured on a daily basis, and they often require more than 24 h for completion, resulting in the loss of valuable time. However, these scores can foresee specific organ failure or severity, but they only use dichotomous parameters, resulting in information loss. Therefore, their use in clinical settings is limited. (3) Artificial intelligence can detect the complex nonlinear relationships between multiple biochemical parameters and disease outcomes. We have recently developed the very first easy-to-use tool, EASY-APP, which uses multiple continuous variables that are available at the time of admission. The web-based application does not require all of the parameters for prediction, allowing early and easy use on admission. In the future, prognostic scores should be developed with the help of artificial intelligence to avoid information loss and to provide a more individualized risk assessment.

Diagnosis, severity stratification and management of adult acute pancreatitis-current evidence and controversies

Acute pancreatitis (AP) is a disease spectrum ranging from mild to severe with an unpredictable natural course. Majority of cases (80%) are mild and self-limiting. However, severe AP (SAP) has a mortality risk of up to 30%. Establishing aetiology and risk stratification are essential pillars of clinical care. Idiopathic AP is a diagnosis of exclusion which should only be used after extended investigations fail to identify a cause. Tenets of management of mild AP include pain control and management of aetiology to prevent recurrence. In SAP, patients should be resuscitated with goal-directed fluid therapy using crystalloids and admitted to critical care unit. Routine prophylactic antibiotics have limited clinical benefit and should not be given in SAP. Patients able to tolerate oral intake should be given early enteral nutrition rather than nil by mouth or parenteral nutrition. If unable to tolerate per-orally, nasogastric feeding may be attempted and routine post-pyloric feeding has limited evidence of clinical benefit. Endoscopic retrograde cholangiopancreatogram should be selectively performed in patients with biliary obstruction or suspicion of acute cholangitis. Delayed step-up strategy including percutaneous retroperitoneal drainage, endoscopic debridement, or minimal-access necrosectomy are sufficient in most SAP patients. Patients should be monitored for diabetes mellitus and pseudocyst.

Value of Dual-Energy CT Perfusion Analysis in Patients with Acute Pancreatitis: Correlation and Discriminative Diagnostic Accuracy with Varying Disease Severity

Background: This study investigates the correlation and discriminative diagnostic accuracy of dual-energy CT (DECT)-derived imaging biomarkers in patients with acute pancreatitis of varying severity. Methods: In this retrospective study, we included 51 patients with acute pancreatitis who had undergone portal-venous phase DECT of the abdomen. Three blinded readers independently performed region-of-interest measurements on DECT images in the inflammatory pancreatic parenchyma. The correlation between modified CT severity index (CTSI) and quantitative imaging parameters was investigated using Pearson correlation coefficient. We performed receiver operator curve (ROC) analysis to assess diagnostic accuracy of the quantitative image parameters for the differentiation between mild/moderate versus severe acute pancreatitis. The optimal discriminative cut-off value to diagnose severe acute pancreatitis was determined using the Youden index. Results: Moderate correlations were found between CTSI scores and iodine density (Pearson’s correlation coefficient r = −0.65; p < 0.001), as well as attenuation (r = −0.55; p < 0.001) and normalized iodine uptake (r = −0.50; p < 0.001). ROC curve analysis revealed highest ability to differentiate mild/moderate from severe acute pancreatitis for iodine density (AUC = 0.86, 95% confidence interval 0.75 to 0.97). An optimal iodine density threshold of ≤1.63 mg/mL was found to indicate severe acute pancreatitis with a sensitivity of 81.3% and specificity of 77.1%. Conclusion: DECT-derived iodine density correlates with acute pancreatitis severity and may facilitate prediction of severe acute pancreatitis.

Aging is Associated with Prolonged Hospitalisation Stay in Pyogenic Liver Abscess-A 1:1 Propensity Score Matched Study in Elderly Versus Non-Elderly Patients

BACKGROUND

Mortality of pyogenic liver abscess (PLA) is high ranging 10%-40%. Old age predicts outcomes in many diseases but there is paucity of data on PLA outcomes. We aim to compare the morbidity and mortality between elderly and non-elderly in PLA.

METHODS

This is a retrospective study from 2007-2011 comparing elderly (≥ 65 years old) and non-elderly (< 65 years old) with PLA. A 1:1 propensity score matching (PSM) was performed. Baseline clinical profile and outcomes were compared.

RESULTS

There were 213 patients (elderly patients = 90 [42.3%], non-elderly patients = 123 [57.7%]). Overall median age is 62 (interquartile range [IQR] = 53-74) years old. PSM resulted in 102 patients (51 per arm). Length of hospitalisation stay (LOS) was significantly longer in elderly patients in both unmatched (16 [IQR = 10-24.5] versus 11 [IQR = 8-19] days; P < 0.001) and matched cohorts (17 [IQR = 13-27] versus 11 [IQR = 7-19] days; P = 0.001). In-hospital mortality was significantly higher in elderly patients in the unmatched cohort (elderly patients = 21.1%, non-elderly patients = 7.3%; P = 0.003) but was insignificant following PSM (elderly patients = 15.7%, non-elderly patients = 9.8%; P = 0.219). Duration of antibiotic therapy and need for percutaneous drainage (PD) were comparable before and after PSM.

CONCLUSION

Age ≥ 65 years old is associated with longer LOS. In-hospital mortality though higher in elderly patients, was not statistically significant.

Akut Pankreas İltihabı Süresince Metillenmiş Arginin Rezidüleri ve İlişkili Amino Asitlerdeki Değişimler

Aim: The extent of the spread of inflammation determines the severity of acute pancreatitis (AP). Methylated arginine residues (MAR), a type of inflammatory mediator, reduce nitric oxide levels and cause vasoconstriction-induced endothelial damage. This study aimed to investigate MAR and related amino acids during acute pancreatic inflammation. Material and Method: This prospective, quasi-experimental study was conducted with patients diagnosed with AP and an age-matched control group. The patient samples were taken during the diagnosis and recovery time, whereas during the study for the control group. Mainly, Asymmetric dimethylarginine (ADMA), Arginine (ARG), Citrulline (CIT), and related chemicals were studied via a mass spectrometer. Results: A total of 30 patients with AP (mean age=53.3±17.8) and 30 controls (mean age=53.4±18.0) were included in the study. All patients were identified as non-severe (n=8) and severe (n=22). A decrease was detected in the patients' ADMA levels compared to the control group (p=0.01). MAR did not differ concerning disease severity (p > 0.05). However, MAR levels decreased higher in patients with diabetes or chronic kidney disease (CKD). Between the two samplings, the ARG level and ARG to ADMA ratio increased, while the MAR and CIT to ARG ratio decreased. Conclusion: Our results showed that MAR levels decreased with AP recovery. The start of a decrease in the high-level blood MAR may indicate the healing of pancreatic inflammation. AP inflammation may be more destructive in patients with diabetes or CKD.

65 yaş üstü hastalarda puanlama sistemlerinin şiddetli akut pankreatiti ve mortaliteyi erken öngörme açısından değerlendirilmesi

Purpose: The aim of this study is to investigate the power of disease severity scores to predict the development of Severe Acute Pancreatitis (SAP) and mortality in the early period over 65 years old diagnosed with acute pancreatitis in the emergency department. Materials and Methods: We calculated RANSON (on admission) and Computed Tomography Severity Index (CTSI) in addition to Bedside Index for Severity in Acute Pancreatitis (BISAP) score on admission to the emergency department. Results: One hundred and sixty patients (46.9% over 80 years of age) were included in the study. We observed statistically higher length of hospitalization, longer duration of stay in the intensive care unit, SAP and higher mortality in patients over 80 years of age. When we examined the ROC curve, we determined that the AUC values of the BISAP score were highest in both SAP and mortality estimation (AUC: 0.911, 95% CI 0.861-0.962; AUC: 0.918, 95% CI 0.864-0.9722, respectively). Binary logistic analysis indicated a 4.7-fold increased risk for SAP and a 12.3-fold increased mortality for each unit increase in BISAP score value. Conclusion: BISAP may be a good predictor for SAP and mortality estimation on admission to the emergency department in patients over 65 years of age with acute pancreatitis.

Neutrophil-Lymphocyte Ratio in Patients with Hypertriglyceridemic Pancreatitis Predicts Persistent Organ Failure

Background

The neutrophil–lymphocyte ratio (NLR) has been proposed as a surrogate marker of inflammation with prognostic value in various diseases. Our objective was to investigate the predictive value of the NLR as an indicator of persistent organ failure (POF) in patients with hypertriglyceridemic pancreatitis (HTGP).

Methods

We retrospectively reviewed the data from patients with HTGP between 2016 and 2019. The NLR was obtained at admission. The diagnostic performance of the NLR for POF was evaluated by the area under the receiver operator characteristics curve (AUROC). Multivariate logistic regression determined whether elevated NLR was independently associated with POF.

Results

Of the 446 patients enrolled, 89 (20.0%) developed POF. Patients with POF showed a significantly higher NLR than those without POF (P < 0.001). A positive trend for the association across increasing NLR quartiles and the incidence of POF was observed (P_trend < 0.001). The AUROC of NLR to predict POF was 0.673 (95% confidence interval, 0.627-0.716). With a cut-off of NLR > 6.56, the sensitivity and specificity were 73.0% and 55.7%, respectively. Multivariate analysis suggested that high NLR (>6.56) was independently associated with POF (odds ratio, 2.580; 95% confidence interval, 1.439-4.626; P = 0.001). Patients with a high NLR (>6.56) had a worse overall clinical course in HTGP.

Conclusion

Elevated NLR was significantly associated with an increased risk of developing POF and could be an early independent predictor of POF in patients with HTGP.

Systemic Immune-Inflammation Index (SII) Can Be an Early Indicator for Predicting the Severity of Acute Pancreatitis: A Retrospective Study

Objective

Systemic immune-inflammation index (SII) is a new systemic inflammatory prognostic indicator associated with outcomes in patients with different tumors. Studies have shown an association between SII and many chronic/acute inflammatory diseases. This study aimed at exploring whether SII can be used as an effective parameter for predicting the severity of acute pancreatitis (AP).

Methods

A total of 101 acute pancreatitis patients were enrolled in this study (mild acute pancreatitis (MAP): n = 73 and severe acute pancreatitis (SAP): n = 28). Patient demographics and SII were analyzed using the chi-square test, Student’s t-test, and Mann–Whitney U-test. A receiver operating characteristic curve was generated to test the potential of using neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and SII to predict AP’s severity. Logistic regression analysis was performed to determine major risk factors.

Results

Patients with SII value ≥2207.53 had a higher probability of having SAP (sensitivity = 92.9%, specificity = 87.7%, and AUC = 0.920), and SII was a significantly better predictive value than PLR and NLR. Logistic regression analysis results showed SII could differentiate MAP from SAP as a major risk factor.

Conclusion

This study has shown that SII is a potential indicator for predicting the severity of acute pancreatitis. The findings suggested that SII is more sensitive and specific than NLR and PLR in predicting the severity of acute pancreatitis.

Role of Extrapancreatic Necrosis Volume in Assessing the Severity and Predicting the Outcomes of Severe Acute Pancreatitis

Objective

To observe the relationship between the extrapancreatic necrosis volume and outcomes in patients with severe acute pancreatitis (SAP).

Methods

We retrospectively analyzed 125 patients with SAP admitted to Severe Acute Pancreatitis Treatment Center of Guizhou Province from August 2013 to August 2018. All patients had extrapancreatic necrosis. The general clinical data of patients, C-reactive protein (CRP) value within 72 hours of onset, Ranson score, organ failure within 3 days after onset, complications, outcomes, CT severity index (CTSI), extrapancreatic necrosis volume and other information were collected. The correlation between extrapancreatic necrosis volume and hospitalization time, ICU stay, hospitalization cost, and CRP value was analyzed. The incidence of complications was obtained from the electronic medical record system.

Results

The mean extrapancreatic necrosis volume was 680 ± 473 mL. The median length of hospital stay was 18.2 (3–76) days, and the ICU stay was 13.5 (3–66) days. The extrapancreatic necrosis volume was positively correlated with hospitalization time, ICU stay time, cost of hospitalization and CRP (P < 0.05). The extrapancreatic necrosis volume in organ failure group was significantly higher than that in non-organ failure group (P < 0.05). The extrapancreatic necrosis volume in patients with death was also higher than that in survival (P < 0.05). With the increase of extrapancreatic necrosis volume, the incidence of complications increased significantly. On the basis of extrapancreatic necrosis volume, the ROC curves yielded an AUC of 0.92 (95% CI: 0.83, 0.99) in predicting the mortality, which was higher than Ranson score (0.90, 95% CI 0.82–0.96) and CTSI (0.85, 0 95% CI 0.77–0.91).

Conclusion

With the increase of extrapancreatic necrosis volume, the incidence of complications increased significantly. The extrapancreatic necrosis volume has the potential to be used as a valuable tool to predict the poor outcome of acute pancreatitis.

Prognostic Value of Glucose-to-Lymphocyte Ratio in Critically Ill Patients with Acute Pancreatitis

Background

Glucose metabolism and systemic inflammation have been associated with prognosis in acute pancreatitis (AP) patients. However, the possible value as a prognostic marker of the glucose-to-lymphocyte ratio (GLR) has not been evaluated in critically ill patients with AP.

Methods

This study included 1,133 critically ill patients with AP from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database, who were randomly divided into the training cohort (n=806) and the validation cohort (n=327) at a ratio of 7:3. X-tile software was used to determine the optimal cut-off values for GLR. Area under the curve (AUC) analysis was performed to compare the performance between GLR and other blood-based inflammatory biomarkers. Univariate and multivariate Cox regression analyses were applied to select prognostic factors associated with in-hospital mortality. A nomogram model was developed based on the identified prognostic factors and the validation cohort was used to further validate the nomogram.

Results

The optimal cut-off value for GLR was 0.9. The ROC analyses showed that the discrimination abilities of GLR were better than other blood-based inflammatory biomarkers. Multivariate Cox regression analysis demonstrated that age, platelet, albumin, bilirubin, Sequential Organ Failure Assessment (SOFA) score, and GLR are independent predictors of poor overall survival in the training cohort and were incorporated into the nomogram for in-hospital mortality as independent factors. The nomogram exhibited better discrimination with C-indexes in the training cohort and the validation cohort of 0.886 (95% CI=0.849–0.922) and 0.841 (95% CI=0.767–0.915), respectively. The calibration plot revealed an adequate fit of the nomogram for predicting the risk of in-hospital mortality in both sets.

Conclusion

As an easily available biomarker, GLR can independently predict the in-hospital mortality of critically ill patients with AP. The nomogram combining GLR with other significant features exerted favorable predictive performance for in-hospital mortality.