Serum calcium as an indicator of persistent organ failure in acute pancreatitis

Application Value of the Automated Machine Learning Model Based on Modified Computed Tomography Severity Index Combined With Serological Indicators in the Early Prediction of Severe Acute Pancreatitis

BACKGROUND AND AIMS

Machine learning (ML) algorithms are widely applied in building models of medicine due to their powerful studying and generalizing ability. To assess the value of the Modified Computed Tomography Severity Index (MCTSI) combined with serological indicators for early prediction of severe acute pancreatitis (SAP) by automated ML (AutoML).

PATIENTS AND METHODS

The clinical data, of the patients with acute pancreatitis (AP) hospitalized in Hospital 1 and hospital 2 from January 2017 to December 2021, were retrospectively analyzed. Serological indicators within 24 hours of admission were collected. MCTSI score was completed by noncontrast computed tomography within 24 hours of admission. Data from the hospital 1 were adopted for training, and data from the hospital 2 were adopted for external validation. The diagnosis of AP and SAP was based on the 2012 revised Atlanta classification of AP. Models were built using traditional logistic regression and AutoML analysis with 4 types of algorithms. The performance of models was evaluated by the receiver operating characteristic curve, the calibration curve, and the decision curve analysis based on logistic regression and decision curve analysis, feature importance, SHapley Additive exPlanation Plot, and Local Interpretable Model Agnostic Explanation based on AutoML.

RESULTS

A total of 499 patients were used to develop the models in the training data set. An independent data set of 201 patients was used to test the models. The model developed by the Deep Neural Net (DL) outperformed other models with an area under the receiver operating characteristic curve (areas under the curve) of 0.907 in the test set. Furthermore, among these AutoML models, the DL and gradient boosting machine models achieved the highest sensitivity values, both exceeding 0.800.

CONCLUSION

The AutoML model based on the MCTSI score combined with serological indicators has good predictive value for SAP in the early stage.

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.

Blood Urine Nitrogen Trajectories of Acute Pancreatitis Patients in Intensive Care Units

Objective

To identify subclasses of acute pancreatitis (AP) patients in the intensive care unit (ICU) by analyzing blood urea nitrogen (BUN) trajectories.

Methods

AP patients in West China Hospital System (development cohort) and three public databases in the United States (validation cohort) were included. Latent class trajectory modelling was used to identify subclasses based on BUN trajectories within the first 21 days after ICU admission. Clinical characteristics and outcomes were compared, and results were externally validated.

Results

The study comprised 2971 and 930 patients in the development and validation cohorts, respectively, with five subclasses: Class 1 ("Moderate-azotemia, slow decreasing"), Class 2 ("Non-azotemia"), Class 3 ("Severe-azotemia, slow decreasing"), Class 4 ("Moderate-azotemia, rapid increasing"), and Class 5 ('Moderate-azotemia, slow increasing) identified. Azotemia patients showed significantly higher 30-day mortality risk in development and validation cohorts. Specifically, Class 4 patients exhibited notably highest mortality risk in both the development cohort (HR 5.32, 95% CI 2.62-10.82) and validation cohort (HR 6.23, 95% CI 2.93-13.22). Regarding clinical characteristics, AP patients in Class 4 showed lower mean arterial pressure and a higher proportion of renal disease. We also created an online early classification model to further identify Class 4 patients among all patients with moderate azotemia at baseline.

Conclusion

This multinational study uncovers heterogeneity in BUN trajectories among AP patients. Patients with "Moderate-azotemia, rapid increasing" trajectory, had a higher mortality risk than patients with severe azotemia at baseline. This finding complements studies that solely rely on baseline BUN for risk stratification and enhanced our understanding of longitudinal progression of AP.

Development and Validation of a Nomogram for Predicting the Severity of the First Episode of Hyperlipidemic Acute Pancreatitis

Purpose

Early detection of hyperlipidemic acute pancreatitis (HLAP) with exacerbation tendency is crucial for clinical decision-making and improving prognosis. The aim of this study was to establish a reliable model for the early prediction of HLAP severity.

Patients and Methods

A total of 225 patients with first-episode HLAP who were admitted to Fujian Medical University Union Hospital from June 2012 to June 2023 were included. Patients were divided into mild acute pancreatitis (MAP) or moderate-severe acute pancreatitis and severe acute pancreatitis (MSAP+SAP) groups. Independent predictors for progression to MSAP or SAP were identified through univariate analysis and least absolute shrinkage and selection operator regression. A nomogram was established through multivariate logistic regression analysis to predict this progression. The calibration, receiver operating characteristic(ROC), and clinical decision curves were employed to evaluate the model's consistency, differentiation, and clinical applicability. Clinical data of 93 patients with first-episode HLAP who were admitted to the First Affiliated Hospital of Fujian Medical University from October 2015 to October 2022 were collected for external validation.

Results

White blood cell count, lactate dehydrogenase, albumin, serum creatinine, serum calcium, D-Dimer were identified as independent predictors for progression to MSAP or SAP in patients with HLAP and used to establish a predictive nomogram. The internally verified Harrell consistency index (C-index) was 0.908 (95% CI 0.867-0.948) and the externally verified C-index was 0.950 (95% CI 0.910-0.990). The calibration, ROC, and clinical decision curves showed this nomogram's good predictive ability.

Conclusion

We have established a nomogram that can help identify HLAP patients who are likely to develop MSAP or SAP at an early stage, with high discrimination and accuracy.

Computed Tomography Assessment of Severity of Acute Pancreatitis in Bangladeshi Children

Purpose

Acute pancreatitis (AP) is common among children in Bangladesh. Its management depends mainly on risk stratification. This study aimed to assess the severity of pediatric AP using computed tomography (CT).

Methods

This cross-sectional, descriptive study was conducted in pediatric patients with AP at the Department of Pediatric Gastroenterology and Nutrition, BSMMU, Dhaka, Bangladesh.

Results

Altogether, 25 patients with AP were included, of whom 18 (mean age, 10.27±4.0 years) were diagnosed with mild AP, and 7 (mean age, 10.54±4.0 years) with severe AP. Abdominal pain was present in all the patients, and vomiting was present in 88% of the patients. Etiology was not determined. No significant differences in serum lipase, serum amylase, BUN, and CRP levels were observed between the mild and severe AP groups. Total and platelet counts as well as hemoglobin, hematocrit, serum creatinine, random blood sugar, and serum alanine aminotransferase levels (p>0.05) were significantly higher in the mild AP group than in the severe AP group (p=0.001). The sensitivity, specificity, positive predictive value, and negative predictive value of CT severity index (CTSI) were 71.4%, 72.2%, 50%, and 86.7%, respectively. In addition, significant differences in pancreatic appearance and necrosis were observed between the two groups on CT.

Conclusion

CT can be used to assess the severity of AP. In the present study, the CTSI effectively assessed the severity of AP in pediatric patients.

Prediction and evaluation of a nomogram model for recurrent acute pancreatitis

OBJECTIVE

The purpose of this study was to investigate the influencing factors for recurrent acute pancreatitis and construct the nomogram model to predict the risk of recurrent acute pancreatitis.

METHODS

Patients diagnosed with acute pancreatitis in the Affiliated Hospital of Southwest Medical University were enrolled. We collected these patients' basic information, laboratory data, imaging information. Using Logistic regression and least absolute shrinkage and selection operator regression to select risk factor for Cross-Validation Criterion. To create nomogram and validated by receiver operator characteristic curve, calibration curves and decision curve analysis.

RESULTS

A total of 533 patients with acute pancreatitis were included, including 99 recurrent acute pancreatitis patients. The average age of recurrent acute pancreatitis patients was 49.69 years old, and 67.7% of them were male. At the same time, in all recurrent acute pancreatitis patients, hypertriglyceridemic pancreatitis is the most important reason (54.5%). Regression analysis and least absolute shrinkage and selection operator regression showed that smoking history, acute necrotic collection, triglyceride, and alcohol etiology for acute pancreatitis were identified and entered into the nomogram. The area under the receiver operator characteristic curve of the training set was 0.747. The calibration curve showed the consistency between the nomogram model and the actual probability.

CONCLUSION

In conclusion, some high-risk factors like smoking history, acute necrotic collection, triglyceride, and alcohol etiology for acute pancreatitis may predict recurrent pancreatitis and their incorporation into a nomogram has high accuracy in predicting recurrence.

Identifying novel acute pancreatitis sub-phenotypes using total serum calcium trajectories

BACKGROUND

Acute pancreatitis (AP) has heterogeneous clinical features, and identifying clinically relevant sub-phenotypes is useful. We aimed to identify novel sub-phenotypes in hospitalized AP patients using longitudinal total serum calcium (TSC) trajectories.

METHODS

AP patients had at least two TSC measurements during the first 24 h of hospitalization in the US-based critical care database (Medical Information Mart for Intensive Care-III (MIMIC-III) and MIMIC-IV were included. Group-based trajectory modeling was used to identify calcium trajectory phenotypes, and patient characteristics and treatment outcomes were compared between the phenotypes.

RESULTS

A total of 4518 admissions were included in the analysis. Four TSC trajectory groups were identified: "Very low TSC, slow resolvers" (n = 65; 1.4% of the cohort); "Moderately low TSC" (n = 559; 12.4%); "Stable normal-calcium" (n = 3875; 85.8%); and "Fluctuating high TSC" (n = 19; 0.4%). The "Very low TSC, slow resolvers" had the lowest initial, maximum, minimum, and mean TSC, and highest SOFA score, creatinine and glucose level. In contrast, the "Stable normal-calcium" had the fewest ICU admission, antibiotic use, intubation and renal replace treatment. In adjusted analysis, significantly higher in-hospital mortality was noted among "Very low TSC, slow resolvers" (odds ratio [OR], 7.2; 95% CI, 3.7 to 14.0), "moderately low TSC" (OR, 5.0; 95% CI, 3.8 to 6.7), and "Fluctuating high TSC" (OR, 5.6; 95% CI, 1.5 to 20.6) compared with the "Stable normal-calcium" group.

CONCLUSIONS

We identified four novel sub-phenotypes of patients with AP, with significant variability in clinical outcomes. Not only the absolute TSC levels but also their trajectories were significantly associated with in-hospital mortality.

Decreased HDL-C Levels as a Predictor of Organ Failure in Acute Pancreatitis in the Emergency Department

High-density lipoprotein cholesterol (HDL-C) is reported as a biomarker of systemic inflammation and multi-organ failure (MOF), which has been rarely investigated in acute pancreatitis (AP), a frequent condition in the emergency department (ED). The objective was to study the predictive capacity of the decrease in HDL-C to the progression of MOF in AP in the ED; analyzing 114 patients with AP for one year in a longitudinal and prospective study, AP severity was obtained by the Atlanta classification, in relation to modified Marshall and Bedside Index for Severity in Acute Pancreatitis (BISAP) scores, and clinical and laboratory parameters in a 48 h hospital stay. The area under the receiver operating characteristic (ROC) curve was used to estimate the validity of the predictor and define optimal cut-off points. It was found that AP was classified as severe in 24.5%, mainly for biliary etiology (78.9%) and female sex (73.6%). As a biomarker, HDL-C decreased from 31.6 to 29.5 mg/dL in a 48 h stay (p < 0.001), correlating negatively with the increase in severity index > 2 and the modified Marshall (p < 0.032) and BISAP (p < 0.009) scores, finding an area under the ROC curve with a predictive capacity of 0.756 (95% CI, 0.614-0.898; p < 0.004) and a cut-off point of 28.5 mg/dL (sensitivity: 79%, specificity: 78%), demonstrating that the decrease in HDL-C levels serves as a useful indicator with a predictive capacity for MOF in mild to severe AP, during a 48 h hospital stay in the ED.

A novel clinical prediction model of severity based on red cell distribution width, neutrophil-lymphocyte ratio and intra-abdominal pressure in acute pancreatitis in pregnancy

BACKGROUND

Acute pancreatitis in pregnancy (APIP) with a high risk of death is extremely harmful to mother and fetus. There are few models specifically designed to assess the severity of APIP. Our study aimed to establish a clinical model for early prediction of severity of APIP.

METHODS

A retrospective study in a total of 188 patients with APIP was enrolled. The hematological indicators, IAP (intra-abdominal pressure) and clinical data were obtained for statistical analysis and prediction model construction.

RESULTS

According to univariate and multivariate logistic regression analysis, we found that red cell distribution width (RDW), neutrophil-lymphocyte ratio (NLR) and Intra-abdominal pressure (IAP) are prediction indexes of the severity in APIP (p-value < 0.05). Our novel clinical prediction model was created by based on the above three risk factors and showed superior predictive power in primary cohort (AUC = 0.895) and validation cohort (AUC = 0.863). A nomogram for severe acute pancreatitis in pregnancy (SAPIP) was created based on the three indicators. The nomogram was well-calibrated.

CONCLUSION

RDW, NLR and IAP were the independent risk factors of APIP. Our clinical prediction model of severity in APIP based on RDW, NLR and IAP with predictive evaluation is accurate and effective.

Changes in vitamin D and calcium-phosphorus metabolism in patients with severe acute pancreatitis

Objectives

The problem of predicting the course of acute pancreatitis and early diagnosis of its complications remains unresolved. This study aimed to determine changes in vitamin D and calcium-phosphorus metabolism in patients with severe acute pancreatitis.

Material and Methods

There were examined 72 people divided into two groups as healthy persons (comparison group) - males and females without pathology of the gastrointestinal tract and any other conditions or diseases that could affect the state of calcium-phosphorus metabolism (n= 36) and patients with acute pancreatitis (main group, n= 36). In addition, in order to determine the prognostic criteria for the severity of the disease, patients in the main group were divided into two subgroups. The first subgroup included patients with severe disease (n= 18), the second (n= 18) - with mild and moderate disease.

Results

Serum calcium value was lower in patients with severe acute pancreatitis comparison to healthy persons: 2.18 (2.12; 2.34) vs 2.36 (2.31; 2.43) mmol/L (p <0.0001), and the decrease of calcium levels was associated with an increase in the severity of acute pancreatitis. Therefore, hypocalcemia can be considered a reliable predictor of the severity of the disease. In patients with acute pancreatitis, the level of vitamin D was significantly low than in the healthy persons and was 13.8 (9.03; 21.34) and 28.4 (21.8; 32.3) ng/mL, respectively (p <0.0001).

Conclusion

For patients with acute pancreatitis, serum vitamin D levels≤ 13.28 ng/mL can be considered as a significant predictor of severe disease (sensitivity 83.3%, specificity 94.4%) regardless of calcium level.

The Potential Role of Model for End-Stage Liver Disease (MELD)-Sodium Score in Predicting the Severity of Acute Pancreatitis

Background and aim Acute pancreatitis is a common inflammation of the pancreas which can be severe and even potentially mortal. High rates of mortality showed the importance of immediate identification of patients at high risk and led the clinicians to refer to various scoring systems. Our aim was to investigate a clinical predictive model using the Model for End-Stage Liver Disease-Sodium (MELD-sodium) scoring system, adapting it to acute pancreatitis patients referring to the systemic inflammatory nature of the disease and potential multi-organ failures in severe form. Methods Our multicenter study was designed retrospectively. The medical records were reviewed for the period of two years. Demographics, biochemical results, MELD-sodium scores and mortality rates were analysed. Results MELD-sodium score was found to be statistically correlated with both mortality and the severity of pancreatitis (p<0.001) and significant difference between both mild and severe (p<0.001), moderate and severe groups (p<0.001). Mortality was found to be significantly higher in patients with MELD-Na score when the cut-off value was accepted as '≥11'. Conclusion We found that MELD-sodium score was significantly associated with both severity of disease and mortality rates and also significantly effective between both mild/severe and moderate/severe groups which may be a guide for future multi-center reviews with larger patient and control groups, which can define the potential role of this non-invasive and easy-to-use predictive model in acute pancreatitis patients.

Medical imaging for pancreatic diseases: Prediction of severe acute pancreatitis complicated with acute respiratory distress syndrome

In this editorial we comment on the article published in the recent issue of the World Journal of Gastroenterology [2022; 28 (19): 2123-2136]. We pay attention to how to construct a simpler and more reliable new clinical predictive model to early identify patients at high risk of acute respiratory distress syndrome (ARDS) associated with severe acute pancreatitis (SAP), and to early predict the severity of organ failure from chest computed tomography (CT) findings in SAP patients. As we all know, SAP has a sudden onset, is a rapidly changing condition, and can be complicated with ARDS and even multiple organ dysfunction syndrome, and its mortality rate has remained high. At present, there are many clinical scoring systems for AP, including the bedside index for severity in AP, acute physiology and chronic health evaluation II, systemic inflammatory response syndrome, Japanese severe score, quick sepsis-related organ failure assessment, etc. However, some of these scoring systems are complex and require multiple and difficult clinical parameters for risk stratification. Although the aforementioned biomarkers are readily available, their ability to predict ARDS varies. Accor-dingly, it is extremely necessary to establish a simple and valuable novel model to predict the development of ARDS in AP. In addition, the extra-pancreatic manifestations of AP patients often involve the chest, among which pleural effusion and pulmonary consolidation are the more common complications. Therefore, by measuring the semi-quantitative indexes of chest CT in AP patients, such as the amount of pleural effusion and the number of lobes involved as pulmonary consolidation, it has important reference value for the early diagnosis of SAP complicated with ARDS and is expected to provide a basis for the early treatment of ARDS.

A Rapid Prognostic Score Based on Bedside Arterial Blood Gas Analysis (ABG) Established for Predicting 60-Day Adverse Outcomes in Patients with Acute Pancreatitis in the Emergency Department

Objective

To establish a rapid and concise prognosis scoring system for pancreatitis in the emergency department based on bedside arterial blood gas analysis (ABG).

Methods

A single-center, retrospective cohort study was used to establish the new scoring system, and a validation group was used to verify it. The primary endpoint was 60-day death, and secondary endpoints were 28-day death, admission to the intensive care unit (AICU), requirement for mechanical ventilation (MV) and persistent organ failure (POF). Receiver operating characteristic (ROC) curves was drawn to validate the predictive value of the new scoring system. The performance of the new scoring system was compared with that of conventional predictive scoring.

Results

443 patients were in the derivation group and 217 patients in the validation group, of which 27 and 25 died during follow-up. A total of 443 patients in the derivation group, 27 of whom died during the follow-up period. Multivariate regression analysis showed that mental status, hematocrit (HCT), base excess (BE) and Serum ionic calcium (Ca²⁺) were independent risk factors for 60-day mortality of pancreatitis, and they were used to create a new scoring system (MHBC). In the derivation and validation, the ability of MHBC (AUC= 0.922, 0.773, respectively) to predict 60-day mortality from pancreatitis was no less than that of APACHE II (AUC= 0.838, 0.748, respectively) and BISAP (AUC= 0.791, 0.750, respectively), while, MHBC is more quickly and concisely than APACHE II and BISAP. Compared with MHBC less than or equal to 2, when MHBC is greater than 2, the 28-day mortality, 60-day mortality and the incidence of AICU, MV and POF increased significantly (P <0.001).

Conclusion

The MHBC can quickly and concisely evaluate the 60-day mortality, 28-day mortality, and the incidence of AICU, MV and POF of patients with acute pancreatitis in the emergency department.

Development and validation of a nomogram for early assessment the severity of acute pancreatitis

BACKGROUND

Acute pancreatitis is an acute inflammatory disorder of the pancreas, and severe acute pancreatitis is associated with high mortality. Early assessment the severity of AP has an important significance for improving clinical outcomes. Our object aimed to develop a nomogram with high simplicity and rapidity for predicting the severity of acute pancreatitis.

METHODS

Patients admitted to the Hunan Provincial People's Hospital within 72 h from onset of AP from January 2010 and December 2020 were enrolled to establish a nomogram. Independent predictors were determined using univariate and multivariate analysis and then assembled to construct a predicting nomogram. The performance of proposed nomogram was evaluated by Brier score and Harrell's concordance index (C-index). Meanwhile, clinical data of AP patients from January 2021 to January 2022 were collected for external validation.

RESULTS

Album (OR 0.891, 95%CI 0.867-0.917), calcium (OR 0.151, 95%CI 0.084-0.273), neutrophil to lymphocyte ratio (OR 1.055, 95%CI 1.023-1.088) and systemic inflammatory response syndrome (OR 6.292, 95%CI 4.459-8.879) were identified as independent factors of SAP after univariate and multivariate analysis (p < .05). A predictive nomogram was accordingly established using these four independent variables. The internally verified C-index was 0.796 (95% CI 0.773-0.818), Brier score was 0.138. The externally verified C index was 0.820 (95% CI 0.754-0.887).

CONCLUSION

A nomogram for predicting the severity of AP was well developed, it may be of great significance for clinicians to quickly assess the progress of AP and choose more-targeted strategies.

Reduced blood circulating calcium level is an outstanding biomarker for preeclampsia among 48 types of human diseases

BACKGROUND

Calcium ion (Ca2+) is essential for human physiology by regulating various signal transduction pathways inside all cells and in the blood circulation.

AIM

We compared circulating Ca2+ levels in the healthy control against 48 different types of human diseases.

DESIGN

A total of 144 201 independent test results of Ca2+ levels from 48 clinically defined diseases and 141 679 independent test results of Ca2+ from healthy individuals who came to the hospital for annual physical examination were retrieved during the past 5 years.

METHODS

Ca2+ was determined by the standard 'Arsenazo III method' in the clinical laboratory of Affiliated Hospital of Qingdao University. We analyzed all data using RStudio V.1.3.1073 and python libraries 3.8.

RESULTS

All 48 types of diseases had decreased Ca2+ levels than the healthy control based on either mean or median values. Patients suffering from preeclampsia had the lowest Ca2+ levels among all 48 diseases. The perfect area under the curve, sensitivity, and specificity values of 1.0, 0.96 and 0.96 indicated that Ca2+ was an excellent biomarker for diagnosing preeclampsia. Extremely low Ca2+ was present in patients suffering kidney-related diseases. Since the correlation between each disease on the statistical features is proportional to their vector distance, the two-component analysis revealed that preeclampsia, sepsis and chronic obstructive pulmonary disease were closely related among 48 diseases.

CONCLUSIONS

All human diseases were associated with reduced circulating Ca2+ levels, where the decreased Ca2+ was a perfect biomarker for preeclampsia. Kidney-related conditions were related to over-down-regulation of Ca2+ levels. The resemblance of preeclampsia to sepsis and chronic obstructive pulmonary disease based on two-component analysis suggested that the three unrelated diseases might share a similar mechanism of the circulating Ca2+ regulation.

Automated Machine Learning for the Early Prediction of the Severity of Acute Pancreatitis in Hospitals

Background

Machine learning (ML) algorithms are widely applied in building models of medicine due to their powerful studying and generalizing ability. This study aims to explore different ML models for early identification of severe acute pancreatitis (SAP) among patients hospitalized for acute pancreatitis.

Methods

This retrospective study enrolled patients with acute pancreatitis (AP) from multiple centers. Data from the First Affiliated Hospital and Changshu No. 1 Hospital of Soochow University were adopted for training and internal validation, and data from the Second Affiliated Hospital of Soochow University were adopted for external validation from January 2017 to December 2021. The diagnosis of AP and SAP was based on the 2012 revised Atlanta classification of acute pancreatitis. Models were built using traditional logistic regression (LR) and automated machine learning (AutoML) analysis with five types of algorithms. The performance of models was evaluated by the receiver operating characteristic (ROC) curve, the calibration curve, and the decision curve analysis (DCA) based on LR and feature importance, SHapley Additive exPlanation (SHAP) Plot, and Local Interpretable Model Agnostic Explanation (LIME) based on AutoML.

Results

A total of 1,012 patients were included in this study to develop the AutoML models in the training/validation dataset. An independent dataset of 212 patients was used to test the models. The model developed by the gradient boost machine (GBM) outperformed other models with an area under the ROC curve (AUC) of 0.937 in the validation set and an AUC of 0.945 in the test set. Furthermore, the GBM model achieved the highest sensitivity value of 0.583 among these AutoML models. The model developed by eXtreme Gradient Boosting (XGBoost) achieved the highest specificity value of 0.980 and the highest accuracy of 0.958 in the test set.

Conclusions

The AutoML model based on the GBM algorithm for early prediction of SAP showed evident clinical practicability.

Dynamic nomogram for persistent organ failure in acute biliary pancreatitis: Development and validation in a retrospective study

BACKGROUND

Persistent organ failure (POF) increases the risk of death in patients with acute biliary pancreatitis (ABP). Currently, there is no early risk assessment tool for POF in patients with ABP.

AIMS

To establish and validate a dynamic nomogram for predicting the risk of POF in ABP.

METHODS

This was a retrospective study of 792 patients with ABP, with 595 cases in the development group and 197 cases in the validation group. Least absolute shrinkage and selection operator regression screened the predictors of POF, and logistic regression established the model (P < 0.05). A dynamic nomogram showed the model. We evaluated the model's discrimination, calibration, and clinical effectiveness; used the bootstrap method for internal validation; and conducted external validation in the validation group.

RESULTS

Neutrophils, haematocrit, serum calcium, and blood urea nitrogen were predictors of POF in ABP. In the development group and validation group, the areas under the receiver operating characteristic curves (AUROCs) were 0.875 and 0.854, respectively, and the Hosmer-Lemeshow test (P > 0.05) and calibration curve showed good consistency between the actual and prediction probability. Decision curve analysis showed that the dynamic nomogram has excellent clinical value.

CONCLUSION

This dynamic nomogram helps with the early identification and screening of high-risk patients with POF in ABP.

Calcium and pH value might predict persistent renal failure in acute pancreatitis in the early phase

OBJECTIVES

Persistent renal failure (PRF) increases morbidity and mortality in acute pancreatitis (AP). Traditional scoring systems achieve good diagnostic value of AP but not PRF alone. Our study aimed to determine PRF predictors in AP patients for early intervention in the disease development.

METHODS

In the prospective observational study, we consecutively recruited AP patients from October 2013 to October 2016. Complete clinical characteristics on admission were collected. The 2012 revision of the Atlanta classification diagnosed AP, and the Modified Marshall scoring system defined organ failures. We used univariate and multivariate analyses to select risk factors, and plotted survival curves of different groups and ROC curves of parameters to analyze PRF predictors in AP.

RESULTS

A total of 29 AP patients with PRF and 280 AP patients without PRF were included. Severity scoring and ICU admission rate were higher in the former group. The PRF group's mortality was 10-fold higher than without PRF (20.7% versus 2.1%, p < .001). Most relevant kidney metabolism indicators and excretion have significant differences (p < .05) between the two groups. Serum calcium (Ca) and pH value (pH) were independent risk factors of PRF (p < .05). ROC curve analysis indicated Ca and pH might predict PRF in AP with areas under the curves (AUCs) of 0.758 and 0.809.

CONCLUSIONS

AP patients with PRF had higher morbidity and mortality rate. Our study showed that Ca < 1.94 mmol/L and pH < 7.37 when patients on admission could be used to predict PRF in AP.

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.

Nomogram for Predicting Persistent Organ Failure With Acute Pancreatitis in Pregnancy

BACKGROUND

Acute pancreatitis in pregnancy (APIP) with persistent organ failure (POF) poses a high risk of death for mother and fetus. This study sought to create a nomogram model for early prediction of POF with APIP patients.

METHODS

We conducted a cross-sectional study on APIP patients with organ failure (OF) between January 2012 and March 2021. 131 patients were collected. Their clinical courses and pregnancy outcomes were obtained. Risk factors for POF were identified by univariate and multivariate logistic regression analysis. Prediction models with POF were built and nomogram was plotted. The performance of the nomogram was evaluated by using a bootstrapped-concordance index and calibration plots.

RESULTS

Hypertriglyceridemia was the most common etiology in this group of APIP patients, which accounted for 50% of transient organ failure (TOF) and 72.3% of POF. All in-hospital maternal death was in the POF group (P<0.05), which also had a significantly higher perinatal mortality rate than the TOF group (P<0.05). Univariate and multivariate logistic regression analysis determined that lactate dehydrogenase, triglycerides, serum creatinine, and procalcitonin were independent risk factors for predicting POF in APIP. A nomogram for POF was created by using the four indicators. The area under the curve was 0.875 (95%CI: 0.80-0.95). The nomogram had a bootstrapped-concordance index of 0.85 and was well-calibrated.

CONCLUSIONS

Hypertriglyceridemia was the leading cause of organ failure-related APIP. Lactate dehydrogenase, triglycerides, serum creatinine, and procalcitonin were the independent risk factors of POF in APIP. Our nomogram model showed an effective prediction of POF with the four indicators in APIP patients.

The Effect of Admission Serum Triglyceride Level on the Prediction of Severity of Acute Pancreatitis in Pregnancy

Purpose

Previous studies indicated that the serum triglyceride level in patients with acute pancreatitis positively correlated with the severity of the disease among the general population. Despite the physiological hypertriglyceridemia in pregnant women, there are no reports on the relationship between serum triglyceride level and the severity of acute pancreatitis in pregnant (APIP) women. This study explores the relationship between serum triglyceride levels and the severity of APIP.

Patients and Methods

Clinical information of APIP patients admitted to the Shengjing Affiliated Hospital of China Medical University was gathered from January 2012 to December 2020 to conduct retrospective research. The participating patients were divided into mild, moderately severe, and severe acute pancreatitis. The clinical outcomes of patients with different serum triglyceride levels (0–2.3 mmol/L, 2.23–5.65 mmol/L, 5.65–11.2 mmol/l, ≥11.2 mmol/L) were analyzed by performing ordinal logistic regression analysis. Receiver operating curve analysis was used to calculate the threshold value of serum triglyceride concentration that can effectively predict the occurrence of severe acute pancreatitis (SAP).

Results

Hypertriglyceridemic acute pancreatitis (HTG-AP) occurred in 47% of APIP patients within the group, with a high prevalence among the Han population. In the present study, the serum triglyceride concentration correlated positively with the severity of APIP (r=0.403, P < 0.05). The adjusted logistic model demonstrated that relative to nominal triglyceride levels, the OR value of SAP were 1.036 (95% CI: 0.401–2.677), 3.429 (95% CI: 1.269–9265), 8.329 (95% CI: 3.713–18.682) with triglyceride at the level of 2.23–5.65 mmol/L, 5.65–11.2 mmol/l and ≥11.2 mmol/L. In APIP patients, a triglyceride concentration of 10.7mmol/L or more upon admission was a predictive value for the occurrence of SAP, with a sensitivity of 0.72 and a specificity of 0.65, AUC: 0.708 (95% CI: 0.620–0.796).

Conclusion

As the serum triglyceride level upon admission increased, the frequency of local and systemic complications increased significantly.

Evaluation of the Prognostic Value of Red Cell Distribution Width to Total Serum Calcium Ratio in Patients with Acute Pancreatitis

Introduction

Acute pancreatitis (AP) is a sudden inflammatory process in the pancreas with variable involvement of nearby organs or other organ systems, and it is a common cause for hospitalization of gastrointestinal origin. Early prediction of the prognosis of patients with AP is important to help physicians triage the patients and decrease mortality. Red cell distribution width (RDW) and total serum calcium (TSC) have been reported to be useful predictors of the severity of AP, but if these parameters are associated with the prognosis of AP is unknown. The objective of the study was to evaluate whether RDW/TSC can be used to predict the prognosis of patients with AP at an early stage.

Methods

We retrospectively enrolled AP patients admitted to the emergency department of West China Hospital of Sichuan University from January 1, 2016, to June 30, 2016. According to the prognosis, AP patients were divided into ICU group and non-ICU group, surgery group and nonsurgery group, and hospital survival group and hospital death group. Demographic information and clinical and laboratory parameters of all enrolled patients after being admitted to ED were compared between the groups. The receiver operator characteristic (ROC) curves were used to evaluate the prognostic values of RDW, TSC, and RDW/TSC in patients with AP.

Results

A total of 666 AP patients were enrolled in this study, with an average age of 47.99 ± 14.11 years, including 633 patients who survived to discharge and 33 patients who died during hospitalization. The areas under the curve (AUC) of RDW and RDW/TSC predict that patients need to be admitted to ICU (0.773 vs. 0.824 vs. 0.723), patients need surgery treatment (0.744 vs. 0.768 vs. 0.690), and patients survived to hospital discharge (0.809 vs. 0.855 vs. 0.780) were greater than that of TSC, with RDW/TSC being the greatest.

Conclusions

RDW/TSC may be a new method to identify the AP patients who need to be transferred to the ICU, accompanying complications which need surgery treatment, or may be died in hospital at an early stage, and we should pay more attention to RDW/TSC in patients with AP, for they may have a worse prognosis.

Accuracy of conventional and novel scoring systems in predicting severity and outcomes of acute pancreatitis: a retrospective study

BACKGROUND

Recently, several novel scoring systems have been developed to evaluate the severity and outcomes of acute pancreatitis. This study aimed to compare the effectiveness of novel and conventional scoring systems in predicting the severity and outcomes of acute pancreatitis.

METHODS

Patients treated between January 2003 and August 2020 were reviewed. The Ranson score (RS), Glasgow score (GS), bedside index of severity in acute pancreatitis (BISAP), pancreatic activity scoring system (PASS), and Chinese simple scoring system (CSSS) were determined within 48 h after admission. Multivariate logistic regression was used for severity, mortality, and organ failure prediction. Optimum cutoffs were identified using receiver operating characteristic curve analysis.

RESULTS

A total of 1848 patients were included. The areas under the curve (AUCs) of RS, GS, BISAP, PASS, and CSSS for severity prediction were 0.861, 0.865, 0.829, 0.778, and 0.816, respectively. The corresponding AUCs for mortality prediction were 0.693, 0.736, 0.789, 0.858, and 0.759. The corresponding AUCs for acute respiratory distress syndrome prediction were 0.745, 0.784, 0.834, 0.936, and 0.820. Finally, the corresponding AUCs for acute renal failure prediction were 0.707, 0.734, 0.781, 0.868, and 0.816.

CONCLUSIONS

RS and GS predicted severity better than they predicted mortality and organ failure, while PASS predicted mortality and organ failure better. BISAP and CSSS performed equally well in severity and outcome predictions.

Metabolomic-based clinical studies and murine models for acute pancreatitis disease: A review

Acute pancreatitis (AP) is one of the most common gastroenterological disorders requiring hospitalization and is associated with substantial morbidity and mortality. Metabolomics nowadays not only help us to understand cellular metabolism to a degree that was not previously obtainable, but also to reveal the importance of the metabolites in physiological control, disease onset and development. An in-depth understanding of metabolic phenotyping would be therefore crucial for accurate diagnosis, prognosis and precise treatment of AP. In this review, we summarized and addressed the metabolomics design and workflow in AP studies, as well as the results and analysis of the in-depth of research. Based on the metabolic profiling work in both clinical populations and experimental AP models, we described the metabolites with potential utility as biomarkers and the correlation between the altered metabolites and AP status. Moreover, the disturbed metabolic pathways correlated with biological function were discussed in the end. A practical understanding of current and emerging metabolomic approaches applicable to AP and use of the metabolite information presented will aid in designing robust metabolomics and biological experiments that result in identification of unique biomarkers and mechanisms, and ultimately enhanced clinical decision-making.

Resveratrol supplementation and acute pancreatitis: A comprehensive review

Resveratrol, a natural polyphenolic ingredient extracted from herbs, suppresses oxidative stress and inflammation. We performed a comprehensive review to find any evidence about the effects of Resveratrol on acute pancreatitis (AP). Resveratrol has been found to directly impact cytokine generation. As these factors play a crucial role in the pathophysiology of AP, resveratrol might attenuate AP and its complications. Mechanistically, resveratrol exerts its pharmacological effects through anti-inflammatory and antioxidant mechanisms via interaction with different signaling molecules and transcription factors. Indeed, resveratrol might prove to be an effective therapeutic component for AP treatment in the future. In this review, we shed light on potential most recent pathways through which resveratrol might impact the management and control of AP.

Factors predicting the severity of acute pancreatitis in elderly patients

BACKGROUND

Moderately severe acute pancreatitis (MSAP) and severe acute pancreatitis (SAP) are associated with organ failure (OF), which can be lethal.

AIMS

This study determined the factors that predict the severity of AP at admission in elderly patients.

METHODS

In this retrospective study, the data from elderly patients (> 60 years of age) admitted within 72 h of onset of symptoms without OF were collected. These data at admission were analyzed and correlated with the severity of AP. To identify the factors associated with more serious AP (i.e. MSAP and SAP), patients were divided into mild acute pancreatitis (MAP) and MSAP + SAP groups.

RESULTS

A total of 198 patients [MAP group (n = 135) and MSAP + SAP group (n = 63)] were included. Biliary disease was the most common etiology. Respiratory failure was the most common OF. Logistic regression analyses indicated that idiopathic etiology (odds ratio [OR]: 3.029, 95% confidence interval [CI]: 1.017-9.022, p = 0.047), pre-existing pulmonary disease (OR: 7.104, CI 1.750-28.84, p = 0.006), increased hematocrit level (OR: 3.717, 95%CI 1.372-10.070, p = 0.010), serum calcium (OR: 0.023, 95%CI 0.001-0.371, p = 0.008), serum glucose (OR: 1.157, 95%CI 1.031-1.299, p = 0.013), arterial partial pressure of oxygen (PaO₂) (OR: 0.914, 95%CI 0.874-0.956, p < 0.001), and pleural effusion (OR: 4.979, 95%CI 1.863-13.303, p = 0.001) were independent predictors of more serious AP.

CONCLUSION

This study found that idiopathic etiology, pre-existing pulmonary diseases, increased hematocrit level or pleural effusion, higher serum glucose, and lower serum calcium or PaO₂ at the time of admission independently correlated with more serious AP in the elderly patients.

Assessment of the course of acute pancreatitis in the light of aetiology: a systematic review and meta-analysis

The main causes of acute pancreatitis (AP) are biliary disease, alcohol consumption, hypertriglyceridaemia (HTG) and endoscopic retrograde cholangiopancreatography (ERCP). The aim of this meta-analysis was to evaluate the effects of these aetiological factors on the severity and outcome of AP. Pubmed and Embase were searched between 01/01/2012 and 31/05/2020. Included articles involved adult alcoholic, biliary, HTG- or post-ERCP AP (PAP) patients. Primary outcome was severity, secondary outcomes were organ failures, intensive care unit admission, recurrence rate, pancreatic necrosis, mortality, length of hospital stay, pseudocyst, fluid collection and systematic inflammatory response syndrome. Data were analysed from 127 eligible studies. The risk for non-mild (moderately severe and severe) condition was the highest in HTG-induced AP (HTG-AP) followed by alcoholic AP (AAP), biliary AP (BAP) and PAP. Recurrence rate was significantly lower among BAP vs. HTG-AP or AAP patients (OR = 2.69 and 2.98, 95% CI 1.55–4.65 and 2.22–4.01, respectively). Mortality rate was significantly greater in HTG-AP vs. AAP or BAP (OR = 1.72 and 1.50, 95% CI 1.04–2.84 and 0.96–2.35, respectively), pancreatic necrosis occurred more frequently in AAP than BAP patients (OR = 1.58, 95% CI 1.08–2.30). Overall, there is a potential association between aetiology and the development and course of AP. HTG-AP is associated with the highest number of complications. Furthermore, AAP is likely to be more severe than BAP or PAP. Greater emphasis should be placed on determining aetiology on admission.

Serum calcium as a biomarker of clinical severity and prognosis in patients with coronavirus disease 2019

The aim of this study was to investigate the correlations between serum calcium and clinical outcomes in patients with coronavirus disease 2019 (COVID-19). In this retrospective study, serum calcium levels, hormone levels and clinical laboratory parameters on admission were recorded. The clinical outcome variables were also recorded. From February 10 to February 28, 2020, 241 patients were enrolled. Of these patients, 180 (74.7%) had hypocalcemia on admission. The median serum calcium levels were 2.12 (IQR, 2.04-2.20) mmol/L, median parathyroid hormone (PTH) levels were 55.27 (IQR, 42.73-73.15) pg/mL, and median 25-hydroxy-vitamin D (VD) levels were 10.20 (IQR, 8.20-12.65) ng/mL. The serum calcium levels were significantly positively correlated with VD levels (P =0.004) but negatively correlated with PTH levels (P =0.048). Patients with lower serum calcium levels (especially ≤2.0 mmol/L) had worse clinical parameters, higher incidences of organ injury and septic shock, and higher 28-day mortality. The areas under the receiver operating characteristic curves of multiple organ dysfunction syndrome, septic shock, and 28-day mortality were 0.923 (P <0.001), 0.905 (P =0.001), and 0.929 (P <0.001), respectively. In conclusion, serum calcium was associated with the clinical severity and prognosis of patients with COVID-19. Hypocalcemia may be associated with imbalanced VD and PTH levels.

A new scoring system can be applied to predict the organ failure related events in acute pancreatitis accurately and rapidly

AIM

To establish a new scoring system to predict the organ failure (OF)-related events in acute pancreatitis (AP) with high accuracy and rapidity.

BACKGROUND

AP is a complicated immunological response that leads to multiple organ failure，but no single scoring system has so far effectively predicted the severity of OF-related events in AP.

METHODS

The research utilized a retrospective study including 1076 AP patients to establish the new scoring system and a prospective study of another 138 patients to verify it. All the laboratory parameters were measured at admission (within 72 h of disease onset). Dunnett'T3 test, univariate and multivariate ordinal logistic regressions were performed. ROC curves were drawn to calculate the cut-off value of the chosen factors and to validate the predictive value of the system.

RESULTS

Lactate dehydrogenase (LDH), creatinine (Cr), albumin (ALB) and calcium (Ca²⁺) made up the new system. The Area Under the Curve (AUC) of the system for OF was 0.904, and for persistent organ failure (POF) was 0.893 while that for death cases was 0.969. As a result, patients who scored 'zero' seemed to recover soon, who received a score '1-4' might have transient organ failure (TOF) but not POF. When the score was over 5, it was probable that patients would suffer POF, and even die if it exceeded 9. The test of the new scoring system proved it conducted well.

CONCLUSION

The new scoring system can accurately and promptly predict the OF-related events in AP.

The effect of hypothalamic peptides, neurohormone C and proline-rich peptide-1on the Ca2+-handling system in heartin pathophysiological conditions

Atthe Institute of Biochemistry named after H. Buniatyan we discovered and studied hypothalamic peptides with coronary dilatory and antioxidant activities:neurohormone C (NC) and proline-rich peptide-1 (PRP-1). Both NC and PRP-1 exhibit cardioprotective effects, in part by restoring the calcium affinity for calcium-binding membrane proteins in cardiomyocytes. This affinity is diminished in the sarcoplasmic reticulum and mitochondriawith myocardial damage, heart failure, pancreatic necrosis and crush syndrome caused by isoproterenol. The peptides can also destroy the four detected toxic peptides and myocardial depressant factor, and protect against ischemia-reperfusion injury. Further studies of these peptides may be promising for the treatment of patients at high risk of cardiovascular disease, regardless of pathology.

Prognostic value of red blood cell distribution width for severe acute pancreatitis

BACKGROUND

Severe acute pancreatitis (SAP) is a common condition in the intensive care unit (ICU) and has a high mortality. Early evaluation of the severity and prognosis is very important for SAP therapy. Recently, red blood cell distribution (RDW) was associated with mortality of sepsis patients and could be used as a predictor of prognosis. Similarly, RDW may be associated with the prognosis of SAP patients and be used as a prognostic indicator for SAP patients.

AIM

To investigate the prognostic value of RDW for SAP patients.

METHODS

We retrospectively enrolled SAP patients admitted to the ICU of the First Affiliated Hospital of China Medical University from June 2015 to June 2017. According to the prognosis at 90 d, SAP patients were divided into a survival group and a non-survival group. RDW was extracted from a routine blood test. Demographic parameters and RDW were recorded and compared between the two groups. The receiver operator characteristic (ROC) curve was constructed and Cox regression analysis was performed to investigate the prognostic value of RDW for SAP patients.

RESULTS

In this retrospective cohort study, 42 SAP patients were enrolled, of whom 22 survived (survival group) and 20 died (non-survival group). The baseline parameters were comparable between the two groups. The coefficient of variation of RDW (RDW-CV), standard deviation of RDW (RDW-SD), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and Sequential Organ Failure Assessment (SOFA) score were significantly higher in the non-survival group than in the survival group (P < 0.05). The RDW-CV and RDW-SD were significantly correlated with the APACHE II score and SOFA score, respectively. The areas under the ROC curves (AUCs) of RDW-CV and RDW-SD were all greater than those of the APACHE II score and SOFA score, among which, the AUC of RDW-SD was the greatest. The results demonstrated that RDW had better prognostic value for predicting the mortality of SAP patients. When the RDW-SD was greater than 45.5, the sensitivity for predicting prognosis was 77.8% and the specificity was 70.8%. Both RDW-CV and RDW-SD could be used as independent risk factors to predict the mortality of SAP patients in multivariate logistic regression analysis and univariate Cox proportional hazards regression analysis, similar to the APACHE II and SOFA scores.

CONCLUSION

The RDW is greater in the non-surviving SAP patients than in the surviving patients. RDW is significantly correlated with the APACHE II and SOFA scores. RDW has better prognostic value for SAP patients than the APACHE II and SOFA scores and could easily be used by clinicians for the treatment of SAP patients.

Early predictors of hyperlipidemic acute pancreatitis

The present study aimed to investigate early risk factors for hyperlipidemic acute pancreatitis (HLAP) in order to open up novel routes for its prevention and treatment. Demographics, laboratory data obtained within 48 h, enhanced computed tomography (CT) imaging data and the modified CT severity index (MCTSI) for 111 patients with HLAP who were assessed at Ordos Central Hospital (Ordos, China) between January 2015 and October 2017 were retrospectively analyzed. Of these, 17 patients progressed to infectious pancreatic necrosis (IPN) and 14 patients progressed to organ failure (OF), the occurrence of which were the study outcomes. The patients were divided into pairs groups: IPN and non-IPN, as well as OF and non-OF, and differences between the groups were determined regarding various clinicopathological parameters. Furthermore, univariate and multivariate regression analyses were performed to identify parameters associated with the risk of progression to IPN or OP. On univariate analysis, the following parameters were deemed as being significantly associated with the risk of IPN: Serum calcium ions, C-reactive protein (CRP), extent of necrosis, procalcitonin (PTC) and the MCTSI. Furthermore, calcium ions, red cell distribution width (RDW), extent of necrosis and the MCTSI were significantly associated with the risk of OF on univariate analysis. Multivariate logistic regression analysis for these parameters then indicated that CRP (P=0.014), RDW (P=0.025) and the extent of necrosis (P=0.022) were significant and independent predictors of progression; thus, these are early risk factors for patients with HLAP. Receiver operating characteristic curves were generated to evaluate the predictive value of these factors, and the area under the curve for the three parameters was 0.863 [95% confidence interval (CI), 0.646-0.886], 0.727 (95% CI, 0.651-0.803) and 0.833 (95% CI, 0.739-0.936), respectively. Therefore, CRP, RDW and the extent of necrosis are early predictive indexes for the risk of progression in HLAP.

A preliminary investigation of metal element profiles in the serum of patients with bloodstream infections using inductively-coupled plasma mass spectrometry (ICP-MS)

BACKGROUND

We determined metal element profiles (MEPs) by inductively-coupled plasma mass spectrometry (ICP-MS) in the serum of patients with blood stream infection (BSI) and find out very important (VIP) metal elements in specific infections.

METHODS

Sixty-eight metal elements were identified in both serum and the bacteria isolated from 14 BSI patients with Staphylococcus infection, 39 with Enterobacteriaceae infection, 5 with Enterococcus infection and 58 healthy subjects without infection by ICP-MS methods. Statistical analysis, Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) were performed to process data among different groups, select differential metal elements and operate correlation analysis.

RESULTS

The MEPs in the serum of BSI patients with 4 types of bacteria (Staphylococcus aureus, Escherichia coli, Enterococcus faecium, and Klebsiella pneumonia), and the corresponding MEPs of the bacteria were established. VIP metal elements were screened out in different BSI patients. Correlation analysis showed that there were some correlations between serum concentrations of metal elements and bacterial infection.

CONCLUSION

We found differential metal elements in the serum of BSI patients compared with controls, thus providing a basis for the diagnosis, prevention and treatment of BSI from the perspective of metallomics.

Is ischemia-modified albumin a reliable tool for the assessment of acute pancreatitis?

PURPOSE

Oxidative stress has been implicated in several disorders, including acute pancreatitis (AP). Ischemia-modified albumin (IMA), which reflects the ability to bind cobalt, has been found to be elevated in conditions of oxidative stress and tissue hypoxia. This study examined IMA and adjusted IMA levels in patients with AP, and examined the associations of IMA and adjusted IMA levels to the severity of AP.

PATIENTS AND METHODS

A total of 42 consecutive patients with AP and 43 age- and sex-matched control subjects were enrolled. Serum samples were obtained from patients with AP on admission as well as 48-72 hours after hospitalization, and from the controls, at the time of enrollment. Adjusted IMA was calculated by multiplying the IMA value of each patient with the ratio of the patient's albumin value and the median albumin value of the study population. The severity of AP was assessed according to the modified Atlanta classification, and the patients were divided into 2 groups: mild AP and severe AP.

RESULTS

The serum IMA and adjusted IMA values of patients with AP on admission and those of the controls did not differ (p=0.86 and p=0.99, respectively). The second measurements of IMA and adjusted IMA in the AP group were higher than the first measurements of both the AP group and controls (for all, p<0.01). Among the IMA measurements, only adjusted IMA on admission had the ability to predict the severity of AP. Severe AP was correlated with albumin, and the area under the curve of adjusted IMA values on admission was 0.746 for differentiating patients with severe AP from mild AP with statistical significance (p=0.005).

CONCLUSION

It was shown that IMA and adjusted IMA levels rise with the progression of AP. Lower levels of adjusted IMA predict the severity of AP. Further studies with serial measurements of IMA are warranted to explore the indicative role of IMA in the course of AP.

Decreased high density lipoprotein cholesterol is an independent predictor for persistent organ failure, pancreatic necrosis and mortality in acute pancreatitis

High density lipoprotein cholesterol (HDL-C) has been reported as a significant indicator of systemic inflammation. The association underlying HDL-C and persistent organ failure (POF), pancreatic necrosis (PNec) and mortality in acute pancreatitis (AP) has not been evaluated. From 2007 to 2016, consecutive AP patients with admission lipid profiles assessment were included in this study. The association of HDL-C value and other lipids with outcomes was explored with Cox proportional regression models, which were adjusted for confounding factors. 1131 consecutive AP patients were clinically eligible. Overall, 17.9% of the patients developed with POF, 27.1% experienced PNec, and 6.7% died during hospitalization. Lower HDL-C median (<1.06 mmol/L) was identified as an independent prognostic factor of the outcomes. Moreover, there was a positive trend for the association across increasing HDL-C quartiles and POF, PNec and mortality after multivariable analysis (p values were <0.001, <0.001 and 0.043, respectively). The AUC of HDL-C for the outcomes were comparable to that of Ranson score for diagnosing POF (0.778 vs. 0.678; P < 0.001), PNec (0.734 vs. 0.701; P = 0.143) and mortality (0.768 vs. 0.745; P = 0.516). Decreased HDL-C value is an independent risk factor for the incidence of POF, PNec and in-hospital mortality in AP.