Hypoalbuminemia affects one third of acute pancreatitis patients and is independently associated with severity and mortality

Chronic liver disease is an important risk factor for worse outcomes in acute pancreatitis: a systematic review and meta-analysis

Chronic liver diseases (CLD) affect 1.5 billion patients worldwide, with dramatically increasing incidence in recent decades. It has been hypothesized that the chronic hyperinflammation associated with CLD may increase the risk of a more severe course of acute pancreatitis (AP). This study aims to investigate the underlying impact of CLD on the outcomes of AP. A systematic search was conducted in Embase, Medline, and Central databases until October 2022. Studies investigating patients with acute pancreatitis and CLD, were included in the meta-analysis. A total of 14,963 articles were screened, of which 36 were eligible to be included. CLD was a risk factor for increased mortality with an odds ratio (OR) of 2.53 (CI 1.30 to 4.93, p = 0.01). Furthermore, renal, cardiac, and respiratory failures were more common in the CLD group, with ORs of 1.92 (CI 1.3 to 2.83, p = 0.01), 2.11 (CI 0.93 to 4.77, p = 0.062) and 1.99 (CI 1.08 to 3.65, p = 0.033), respectively. Moreover, the likelihood of developing Systemic Inflammatory Response Syndrome (SIRS) was significantly higher, with an OR of 1.95 (CI 1.03 to 3.68, p = 0.042). CLD is an important risk factor for worse outcomes in AP pancreatitis, leading to higher mortality and increased rates of local and systemic complications.

Ehmt2 inactivation in pancreatic epithelial cells shapes the transcriptional landscape and inflammation response of the whole pancreas

Introduction: The Euchromatic Histone Methyl Transferase Protein 2 (EHMT2), also known as G9a, deposits transcriptionally repressive chromatin marks that play pivotal roles in the maturation and homeostasis of multiple organs. Recently, we have shown that Ehmt2 inactivation in the mouse pancreas alters growth and immune gene expression networks, antagonizing Kras-mediated pancreatic cancer initiation and promotion. Here, we elucidate the essential role of Ehmt2 in maintaining a transcriptional landscape that protects organs from inflammation. Methods: Comparative RNA-seq studies between normal postnatal and young adult pancreatic tissue from Ehmt2 conditional knockout animals (Ehmt2 fl/fl ) targeted to the exocrine pancreatic epithelial cells (Pdx1-Cre and P48 Cre/+ ), reveal alterations in gene expression networks in the whole organ related to injury-inflammation-repair, suggesting an increased predisposition to damage. Thus, we induced an inflammation repair response in the Ehmt2 fl/fl pancreas and used a data science-based approach to integrate RNA-seq-derived pathways and networks, deconvolution digital cytology, and spatial transcriptomics. We also analyzed the tissue response to damage at the morphological, biochemical, and molecular pathology levels. Results and discussion: The Ehmt2 fl/fl pancreas displays an enhanced injury-inflammation-repair response, offering insights into fundamental molecular and cellular mechanisms involved in this process. More importantly, these data show that conditional Ehmt2 inactivation in exocrine cells reprograms the local environment to recruit mesenchymal and immunological cells needed to mount an increased inflammatory response. Mechanistically, this response is an enhanced injury-inflammation-repair reaction with a small contribution of specific Ehmt2-regulated transcripts. Thus, this new knowledge extends the mechanisms underlying the role of the Ehmt2-mediated pathway in suppressing pancreatic cancer initiation and modulating inflammatory pancreatic diseases.

Penoscrotal Edema as a Rare Complication of Acute Pancreatitis: A Case Report

Background and Objectives: Scrotal swelling or hydrocele is a rare complication of acute pancreatitis described in the literature. We present a case of penoscrotal swelling caused by the first attack of acute interstitial edematous alcohol-induced pancreatitis in a young male patient. Case report: A 22-year-old man was admitted to the emergency unit due to diarrhea and vomiting since morning which was followed by severe abdominal pain. Urgent abdominal multislice CT scan showed steatosis, pancreatic swelling and acute peripancreatic fluid collection (interstitial edematous pancreatitis). Also, scan showed fluid between small bowel loops and along the anterior renal fascia, while there was minimal amount of fluid in the Douglas space. There was no sign of penoscrotal swelling. On the second day of admission, the patient developed left scrotal swelling and mild pain without erythema. On the fourth day, a control CT scan showed progression to moderately severe pancreatitis (CT severity index 4). Dilated scrotal veins of the pampiniform venous plexus with an increased caliber of the testicular veins were present on both sides, from the scrotum to the level of the inguinal canal. Penoscrotal swelling was significantly reduced on discharge. Conclusions: Penoscrotal swelling is a rare complication or manifestation of acute inflammation of the pancreas. It is important to identify scrotal swelling caused by pancreatitis because in severe cases it can be related to possible infertility in the future.

Persistently High Procalcitonin and C-Reactive Protein Are Good Predictors of Infection in Acute Necrotizing Pancreatitis: A Systematic Review and Meta-Analysis

Infected necrotizing pancreatitis (INP) is associated with an increased risk of organ failure and mortality. Its early recognition and timely initiation of antibiotic therapy can save patients' lives. We systematically searched three databases on 27 October 2022. In the eligible studies, the presence of infection in necrotizing pancreatitis was confirmed via a reference test, which involved either the identification of gas within the necrotic collection through computed tomography imaging or the examination of collected samples, which yielded positive results in Gram staining or culture. Laboratory biomarkers compared between sterile necrotizing pancreatitis and INP were used as the index test, and our outcome measures included sensitivity, specificity, the receiver operating characteristic (ROC) curve and area under the ROC curve (AUC). Within the first 72 hours (h) after admission, the AUC of C-reactive protein (CRP) was 0.69 (confidence interval (CI): 0.62-0.76), for procalcitonin (PCT), it was 0.69 (CI: 0.60-0.78), and for white blood cell count, it was 0.61 (CI: 0.47-0.75). After the first 72 h, the pooled AUC of CRP showed an elevated level of 0.88 (CI: 0.75-1.00), and for PCT, it was 0.86 (CI: 0.60-1.11). The predictive value of CRP and PCT for infection is poor within 72 h after hospital admission but seems good after the first 72 h. Based on these results, infection is likely in case of persistently high CRP and PCT, and antibiotic initiation may be recommended.

Predictive power of HALP score in estimating short-term mortality in patients with acute pancreatitis

BACKGROUND

To examine the hemoglobin, albumin, lymphocyte, and platelet (HALP) scores' predictive power in predicting short-term mortality from acute pancreatitis (AP).

METHODS

The study was conducted at the emergency department (ED) of tertiary care hospital. The medical records of patients who admitted to the ED and were diagnosed with AP were reviewed retrospectively. İt was analyzed that the ability of the HALP score in predicting short-term mortality of these patients.

RESULTS

The study was achieved with a total of 634 patients. The mean age of these patients was 59.7±16.6 and 381 (60.1%) were female. While 42 (6.6%) of the total included patients were required to the intensive care unit, 58 (9.1%) died. To examine the HALP scores' predictive power in predicting short-term mortality, the Receiver Operating Characteristic (ROC) analysis was utilized. The value of the area under the curve was found as 0.891 (95% CI: 0.833-0.949). When the cut-off value of the HALP score in determining short-term mortality is >15, the Sensitivity of the score was found to be 82.8%, Specificity 86.8%, Positive Predictive Value 38.7%, and Negative Predictive Value 98.0%.

CONCLUSION

AP is a disease that requires early diagnosis and adequate treatment if not it can cause a high rate of mortality and morbidity. As a result of this study, it was concluded that the HALP score can be utilized during the prediction of short-term mortality for patients diagnosed with AP.

Ascites Volume Quantification via Abdominal CT: A Novel Approach to Predict Severity in Acute Pancreatitis

BACKGROUND Acute pancreatitis, a sudden inflammation of the pancreas, can result in severe complications. The presence and volume of ascites, an abnormal accumulation of fluid in the abdomen, has been linked to disease severity. Our study investigates ascites volume, quantified via abdominal CT scans, as a potential predictive tool for disease severity. MATERIAL AND METHODS In this retrospective analysis, patients diagnosed with acute pancreatitis were evaluated. Patients were categorized into groups with and without ascites, with comparisons made regarding clinical characteristics. We further compared the mean ascitic volume against various outcome parameters in patients with ascites. Ascites volume and other predictive systems were assessed through receiver operating characteristic (ROC) curves, with the area under the ROC curve (AUC) for different predictive systems being analyzed. RESULTS The ascites group had higher severity scores and related serological indexes (P<0.05 for all). Among patients with ascites, a significant correlation was observed between ascites volume and outcome parameters (P<0.05 for all). The area under the ROC curve for predicting severe acute pancreatitis was 0.896, with 93% sensitivity and 79% specificity. Ascites volume yielded the highest diagnostic odds ratio (53.1; 95% confidence interval: 13.2,199.6). CONCLUSIONS Early-stage acute pancreatitis patients with ascites are indicative of severe illness and poor prognosis. An increase in ascites volume correlates with adverse clinical outcomes, thus highlighting the significance of ascites volume as a prognostic marker. This underscores the importance of abdominal CT in measuring ascites volume to predict disease severity.

Development and Validation of a Dynamic Nomogram for Predicting in-Hospital Mortality in Patients with Acute Pancreatitis: A Retrospective Cohort Study in the Intensive Care Unit

Purpose

The aim of this study is to develop and validate a predictive model for the prediction of in-hospital mortality in patients with acute pancreatitis (AP) based on the intensive care database.

Patients and Methods

We analyzed the data of patients with AP in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and Electronic Intensive Care Unit Collaborative Research Database (eICU-CRD). Then, patients from MIMIC-IV were divided into a development group and a validation group according to the ratio of 8:2, and eICU-CRD was assigned as an external validation group. Univariate logistic regression and least absolute shrinkage and selection operator regression were used for screening the best predictors, and multivariate logistic regression was used to establish a dynamic nomogram. We evaluated the discrimination, calibration, and clinical efficacy of the nomogram, and compared the performance of the nomogram with Acute Physiology and Chronic Health Evaluation II (APACHE-II) score and Bedside Index of Severity in AP (BISAP) score.

Results

A total of 1030 and 514 patients with AP in MIMIC-IV database and eICU-CRD were included in the study. After stepwise analysis, 8 out of a total of 37 variables were selected to construct the nomogram. The dynamic nomogram can be obtained by visiting https://model.sci-inn.com/KangZou/. The area under receiver operating characteristic curve (AUC) of the nomogram was 0.859, 0.871, and 0.847 in the development, internal, and external validation set respectively. The nomogram had a similar performance with APACHE-II (AUC = 0.841, p = 0.537) but performed better than BISAP (AUC = 0.690, p = 0.001) score in the validation group. Moreover, the calibration curve presented a satisfactory predictive accuracy, and the decision curve analysis suggested great clinical application value of the nomogram.

Conclusion

Based on the results of internal and external validation, the nomogram showed favorable discrimination, calibration, and clinical practicability in predicting the in-hospital mortality of patients with AP.

Albumin Corrected Anion Gap and the Risk of in-Hospital Mortality in Patients with Acute Pancreatitis: A Retrospective Cohort Study

Purpose

To explore the prognostic value of albumin corrected anion gap (ACAG) within 24 hours of admission to the intensive care unit (ICU) for acute pancreatitis (AP).

Patients and Methods

This was a retrospective cohort study. Adult AP patients admitted to ICU from June 2016 to December 2019 were included in the study, who were divided into three groups according to initial serum ACAG within 24 hours upon ICU admission: ACAG ≤ 14.87 mmol/L, 14.87 < ACAG ≤ 19.03 mmol/L, and ACAG > 19.03 mmol/L. The primary study outcome indicator was in-hospital mortality. Age, sex, Glasgow Coma Scale score, and Acute Physiology and Chronic Health Evaluation II (APACHE II) score were matched through propensity score matching (PSM) method to balance the baseline between the survivors and non-survivors. Multivariate Cox regression was used to determine the relationship between ACAG and in-hospital mortality.

Results

A total of 344 patients (of them 81 non-survivors) were analyzed in this study. Patients with higher ACAG intended to present significantly higher in-hospital mortality, APACHE II score, creatine, lower albumin, and bicarbonate. Multivariate Cox regression analysis after matching demonstrated that white blood cell count, platelet count, and higher ACAG were independently associated with higher in-hospital mortality (ACAG ≤ 14.87 as a reference, 14.87 < ACAG ≤ 19.03 mmol/L with HR of 2.34 and 95% CI of 1.15-4.76, ACAG >19.03 with HR of 3.46 and 95% CI of 1.75-6.84).

Conclusion

Higher ACAG was independently associated with higher in-hospital mortality in patients with AP after matching the baseline between the survivors and non-survivors.

Albumin infusion may decrease the mortality of hypoalbuminemia patients with severe acute pancreatitis: a retrospective cohort study

BACKGROUND

At present, the relationship between severe acute pancreatitis (SAP) and albumin infusion is not clear. We aimed to identify the impact of serum albumin on the prognosis of SAP and the association between albumin infusions and mortality for hypoalbuminemia patients.

METHODS

This was a retrospective cohort study that analyzed 1000 patients with SAP who were admitted to the First Affiliated Hospital of Nanchang University between January 2010 and December 2021 using data from a prospectively maintained database. Multivariate logistic regression analysis was conducted to reveal the relationship between serum albumin within 1 week after admission and poor prognosis of SAP. Propensity score matching (PSM) analysis was adopted to evaluate the effect of albumin infusion for hypoalbuminemia patients with SAP.

RESULTS

The prevalence of hypoalbuminemia (≤ 30 g/L) was 56.9% within 1 week after admission. Multivariate logistic regression identified that age (OR: 1.02; 95% CI: 1.00-1.04; P = 0.012), serum urea (OR: 1.08; 95% CI: 1.04-1.12; P < 0.001), serum calcium (OR: 0.27; 95% CI: 0.14-0.50; P < 0.001), lowest albumin level within 1 week after admission (OR: 0.93; 95% CI: 0.89-0.97; P = 0.002), and APACHE II score ≥ 15 (OR: 1.73; 95% CI: 1.19-2.51; P = 0.004) were independently associated with mortality. The PSM analysis demonstrated that mortality (OR: 0.52, 95% CI: 0.29-0.92, P = 0.023) was less common in albumin-infused than non-albumin-infused hypoalbuminemia patients. In subgroup analyses, doses > 100 g within 1 week after admission for hypoalbuminemia patients with albumin infusions was associated with lower mortality than doses ≤ 100 g (OR: 0.51, 95% CI: 0.28-0.90, P = 0.020).

CONCLUSIONS

Hypoalbuminemia in early-stage SAP is significantly related to poor prognosis. However, albumin infusions could significantly decrease mortality in hypoalbuminemia patients with SAP. Additionally, infusing sufficient albumin within a week after admission may decrease mortality in hypoalbuminemia patients.

To Establish an Early Prediction Model for Acute Respiratory Distress Syndrome in Severe Acute Pancreatitis Using Machine Learning Algorithm

OBJECTIVE

To develop binary and quaternary classification prediction models in patients with severe acute pancreatitis (SAP) using machine learning methods, so that doctors can evaluate the risk of patients with acute respiratory distress syndrome (ARDS) and severe ARDS at an early stage.

METHODS

A retrospective study was conducted on SAP patients hospitalized in our hospital from August 2017 to August 2022. Logical Regression (LR), Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), and eXtreme Gradient Boosting (XGB) were used to build the binary classification prediction model of ARDS. Shapley Additive explanations (SHAP) values were used to interpret the machine learning model, and the model was optimized according to the interpretability results of SHAP values. Combined with the optimized characteristic variables, four-class classification models, including RF, SVM, DT, XGB, and Artificial Neural Network (ANN), were constructed to predict mild, moderate, and severe ARDS, and the prediction effects of each model were compared.

RESULTS

The XGB model showed the best effect (AUC = 0.84) in the prediction of binary classification (ARDS or non-ARDS). According to SHAP values, the prediction model of ARDS severity was constructed with four characteristic variables (PaO₂/FiO₂, APACHE II, SOFA, AMY). Among them, the overall prediction accuracy of ANN is 86%, which is the best.

CONCLUSIONS

Machine learning has a good effect in predicting the occurrence and severity of ARDS in SAP patients. It can also provide a valuable tool for doctors to make clinical decisions.

No evidence for the benefit of PPIs in the treatment of acute pancreatitis: a systematic review and meta-analysis

Although current guidelines do not recommend the use of proton pump inhibitors (PPIs) in the standard of care of acute pancreatitis (AP), they are often prescribed in clinical practice, mainly for ulcer stress prophylaxis. In this systematic review and meta-analysis we evaluated the association between the use of PPIs in the management of AP and various clinical outcomes. We conducted the systematic research in six databases without restrictions on January 24th, 2022. We investigated adult patient with AP, who were treated with PPI compared to conventional therapy. The pooled odds ratios, mean differences, and corresponding 95% confidence intervals were calculated with random effect model. We included six RCTs and three cohort studies, consisting of 28,834 patients. We found a significant decrease in the rate of pancreatic pseudocyst formation in patients who received PPI treatment. PPI use was associated with a higher risk of GI bleeding, however this finding could be due to the patients' comorbid conditions. We found no significant difference in the rates of 7-day mortality, length of hospital stay, and acute respiratory distress syndrome between the groups. The available data on this topic are limited; therefore, further well designed RCTs are needed to evaluate the potential benefits and adverse effects of PPIs in AP.

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.

Predicting persistent organ failure on admission in patients with acute pancreatitis: development and validation of a mobile nomogram

BACKGROUND

Early prediction of persistent organ failure (POF) is important for triage and timely treatment of patients with acute pancreatitis (AP).

METHODS

All AP patients were consecutively admitted within 48 h of symptom onset. A nomogram was developed to predict POF on admission using data from a retrospective training cohort, validated by two prospective cohorts. The clinical utility of the nomogram was defined by concordance index (C-index), decision curve analysis (DCA), and clinical impact curve (CIC), while the performance by post-test probability.

RESULTS

There were 816, 398, and 880 patients in the training, internal and external validation cohorts, respectively. Six independent predictors determined by logistic regression analysis were age, respiratory rate, albumin, lactate dehydrogenase, oxygen support, and pleural effusion and were included in the nomogram (web-based calculator: https://shina.shinyapps.io/DynNomapp/). This nomogram had reasonable predictive ability (C-indexes 0.88/0.91/0.81 for each cohort) and promising clinical utility (DCA and CIC). The nomogram had a positive likelihood ratio and post-test probability of developing POF in the training, internal and external validation cohorts of 4.26/31.7%, 7.89/39.1%, and 2.75/41%, respectively, superior or equal to other prognostic scores.

CONCLUSIONS

This nomogram can predict POF of AP patients and should be considered for clinical practice and trial allocation.

Identification and validation of an autophagy-related gene signature for predicting prognosis in patients with esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is the main subtype of esophageal cancer. Since autophagy-related genes (ARGs) play a key role in the pathogenesis of many tumors, including ESCC, the purpose of this study is to establish an autophagy-related prognostic risk signature based on ARGs expression profile, and to provide a new method for improving prediction of clinical outcomes. We obtained the expression profiles of ESCC from public data (GSE53625) and extracted the portion of ARGs. Differential expression analysis and enrichment analysis were performed to confirm abnormal autophagy-related biological functions. Univariate and multivariate Cox regression analyses were performed on RNA microarray data (GSE53625) to construct a prognostic risk signature associated with autophagy. The performance of the model was evaluated by receiver operating characteristic (ROC) analysis, survival analysis and Brier score. The model was subjected to bootstrap internal validation. The potential molecular mechanism of gene signature was explored by gene set enrichment analysis (GSEA). Spearman correlation coefficient examined the correlation between risk score and immune status and ferroptosis. The expression levels of genes and proteins were validated by qRT-PCR and immunohistochemistry in ESCC cell lines and ESCC tissues. We constructed and validated an autophagy-related prognostic risk signature in 179 patients with ESCC. The long-term survival of patients in high-risk group was lower than that in low-risk group (log-rank, P value < 0.001). ROC analysis and Brier score confirmed the reliability of the signature. GSEA results showed significant enrichment of cancer- and autophagy-related signaling pathways in the high-risk ESCC patients and immunoregulatory signaling pathways in the low-risk ESCC patients. Correlation analysis showed that the risk signature can effectively predict the effect of immunotherapy. About 33.97% (71/209) ferroptosis-related genes were significantly correlated with risk scores. Finally, the results of qRT-PCR and immunohistochemistry experiments were consistent with bioinformatics analysis. In brief, we constructed a novel autophagy-related gene signature (VIM, UFM1, TSC2, SRC, MEFV, CTTN, CFTR and CDKN1A), which could improve the prediction of clinical outcomes in patients with ESCC.

Usefulness of Random Forest Algorithm in Predicting Severe Acute Pancreatitis

BACKGROUND AND AIMS

This study aimed to develop an interpretable random forest model for predicting severe acute pancreatitis (SAP).

METHODS

Clinical 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).

RESULTS

The 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.

CONCLUSIONS

An 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.