Plasmatic Oxidative and Metabonomic Profile of Patients with Different Degrees of Biliary Acute Pancreatitis Severity

Clinical value of the Systemic Inflammatory Response Index for predicting acute pancreatitis severity in Vietnamese setting

Background and Aim

Accurate prediction of severe acute pancreatitis (SAP) is crucial for timely intervention. This study focuses on the Systemic Inflammatory Response Index (SIRI) to assess its clinical value in predicting the severity of AP in the Vietnamese context.

Methods

A cross-sectional prospective study was conducted with acute pancreatitis patients at a national hospital in Ho Chi Minh City. The patients were classified into nonsevere and severe groups, and the clinical characteristics were analyzed. The predictive abilities of SIRI, calculated using neutrophil × monocyte/lymphocyte, was assessed for predictive abilities. Multivariate regression and receiver operating characteristics (ROC) curves evaluated the prognostic factors and predictive accuracy.

Results

Among 207 patients, 78.7% had nonsevere AP, and 21.3% had SAP. The severe group exhibited a significantly higher median SIRI (12.0) than the nonsevere group (4.9) (P < 0.001). Multivariate regression identified SIRI (odds ratio [OR] = 1.623) as an independent predictor of SAP. The ROC curve determined a SIRI cutoff of 7.82 with an area under the curve (AUC) of 0.737. Combining the SIRI and Bedside Index for Severity in Acute Pancreatitis (BISAP) score improved the predictive ability (AUC = 0.820) with increased sensitivity (90.91%) (P < 0.001).

Conclusion

SIRI, particularly when combined with the BISAP score, shows significant potential to predict SAP severity in the Vietnamese clinical setting, providing valuable information for effective patient management.

Hemorheological and Microcirculatory Relations of Acute Pancreatitis

Acute pancreatitis still means a serious challenge in clinical practice. Its pathomechanism is complex and has yet to be fully elucidated. Rheological properties of blood play an important role in tissue perfusion and show non-specific changes in acute pancreatitis. An increase in blood and plasma viscosity, impairment of red blood cell deformability, and enhanced red blood cell aggregation caused by metabolic, inflammatory, free radical-related changes and mechanical stress contribute to the deterioration of the blood flow in the large vessels and also in the microcirculation. Revealing the significance of these changes in acute pancreatitis may better explain the pathogenesis and optimize the therapy. In this review, we give an overview of the role of impaired microcirculation by changes in hemorheological properties in acute pancreatitis.

Prolonged activated partial thromboplastin time predicts poor short-term prognosis in patients with acute pancreatitis: A retrospective cohort study

It is unclear whether activated partial thromboplastin time (APTT) is predictive of survival in patients with acute pancreatitis (AP). Our study aimed to investigate the relationship between APTT and short-term prognosis in AP. From the Medical Information Mart for Intensive Care (MIMIC)-IV database, a total of 844 patients with AP were randomly divided into the training cohort (n = 591) and the validation cohort (n = 253) at a ratio of 7:3. Based on their APTT values, the patients were divided into the normal and high groups. The primary outcome of this study was 30- and 60-day survival. Kaplan-Meier survival analysis and Cox regression models were used to analyze associations between groups and outcomes. The training and validation cohort matched well on all parameters (p > 0.05). In terms of 30- and 60-day survival, Kaplan-Meier survival curves from both training and validation cohorts demonstrated a lower survival probability for patients in the high APTT group than the normal group (log-rank p < 0.05). In the training cohort, patients in the high APTT group had a statistically significantly higher risk of death than those in the normal group after controlling for possible confounders in Cox regression (p < 0.05). For the high APTT group, the hazard ratios (95% confidence interval [CI]) were 1.63 (95% CI 1.10, 2.61, p = 0.035) and 1.49 (95% CI 1.01, 2.38, p = 0.041), respectively. APTT performed as well as BISAP, Ranson, and APACHE II models in predicting 30- and 60-day survival in patients with AP. The results above have been verified in the validation cohort. Prolonged APTT in patients with AP may increase the risk of short-term death.

Systemic Inflammation Response Index and Systemic Immune Inflammation Index Are Associated with Clinical Outcomes in Patients with Acute Pancreatitis?

OBJECTIVES

The inflammatory response is critically important in acute pancreatitis (AP). Systemic immune-inflammation (SII) index and systemic inflammation response index (SIRI), which are novel inflammatory markers, have been linked to determining outcomes in various diseases. The goal of the current study was to examine the relation of the SII index and SIRI with disease severity and acute kidney injury (AKI) in subjects with AP.

METHODS

A total of 332 subjects with AP were analyzed retrospectively. SII index was calculated using the formula; platelet (P)×neutrophil (N)/lymphocyte (L), while SIRI was calculated as N × monocyte (M)/L count. Multivariate regression (MR) was done to determine the independent risk factors for AKI and severe AP (SAP).

RESULTS

Statistical analyses showed that both median SII index and median SIRI increased gradually with higher AP severity (p < 0.001). Both SII index and SIRI were higher in subjects with AKI compared to controls (p < 0.001). Using MR analysis, the SII index was found to independently predict both SAP (OR = 1.004, 95% CI: 1.001-1.008, p = 0.018) and AKI (OR = 1.005, 95% CI: 1.003-1.008, p < 0.001). ROC analysis showed that the SII index could accurately differentiate SAP (AUC = 0.809, p < 0.001) and AKI (AUC = 0.820, p = 0.001) in patients with acute pancreatitis. ROC analysis also showed that SIRI could also accurately differentiate SAP (0.782, p < 0.001) and AKI (AUC = 0.776, p = 0.001).

CONCLUSIONS

SIRI and the SII indexes can be used as potential biomarkers in predicting both disease severity and AKI development in subjects with AP.

Antioxidants, Oxidative Stress, and Non-Communicable Diseases

Non-communicable diseases have become the leading cause of death, morbidity, and loss of healthy years worldwide, according to the World Health Organization [...]

Predicting the Need for Therapeutic Intervention and Mortality in Acute Pancreatitis: A Two-Center International Study Using Machine Learning

Background: Current approaches to predicting intervention needs and mortality have reached 65–85% accuracy, which falls below clinical decision-making requirements in patients with acute pancreatitis (AP). We aimed to accurately predict therapeutic intervention needs and mortality on admission, in AP patients, using machine learning (ML). Methods: Data were obtained from three databases of patients admitted with AP: one retrospective (Chengdu) and two prospective (Liverpool and Chengdu) databases. Intervention and mortality differences, as well as potential predictors, were investigated. Univariate analysis was conducted, followed by a random forest ML algorithm used in multivariate analysis, to identify predictors. The ML performance matrix was applied to evaluate the model’s performance. Results: Three datasets of 2846 patients included 25 potential clinical predictors in the univariate analysis. The top ten identified predictors were obtained by ML models, for predicting interventions and mortality, from the training dataset. The prediction of interventions includes death in non-intervention patients, validated with high accuracy (96%/98%), the area under the receiver-operating-characteristic curve (0.90/0.98), and positive likelihood ratios (22.3/69.8), respectively. The post-test probabilities in the test set were 55.4% and 71.6%, respectively, which were considerably superior to existing prognostic scores. The ML model, for predicting mortality in intervention patients, performed better or equally with prognostic scores. Conclusions: ML, using admission clinical predictors, can accurately predict therapeutic interventions and mortality in patients with AP.

Predictive value of arterial blood lactic acid concentration on the risk of all-cause death within 28 days of admission in patients with severe acute pancreatitis

ObjectiveTo evaluate the ability of arterial blood lactic acid concentration to predict death within 28 days of admission of patients with severe acute pancreatitis (SAP) in the intensive care unit (ICU).MethodsClinical data of 523 SAP patients in the MIMIC-IV database were retrospectively analyzed. Patients were divided into those who survived (n=461) and those who died (n=62) within 28 days of admission. The association between lactic acid concentration and all-cause death in SAP patients was determined by Cox regression analysis, Kaplan-Meier survival analysis and subgroup analysis. The ability of lactic acid concentration to predict the risk of all-cause death in SAP patients was determined by time-dependent receiver operating curve (ROC) analysis.ResultsArterial blood lactic acid concentration was significantly higher in the 62 patients who died within 28 days than in the 461 patients who survived (P <0.05). Adjusted multivariate Cox regression analysis showed that lactic acid concentration was a significant independent predictor on all-cause mortality within 28 days of admission for SAP (hazard ratio=1.22, 95% confidence interval 1.09-1.36, P <0.001), as did time-dependent ROC analysis (area under the ROC curve=0.741). Kaplan-Meier analysis showed that the rate of all-cause mortality within 28 days of admission was significantly higher in patients with high than low lactic acid concentration (P <0.0001). Subgroup analysis showed that there was no significant interaction between lactic acid concentration and other factors with all-cause death within 28 days of admission (all P >0.05).ConclusionArterial blood lactic acid concentration is an important independent predictor of all-cause mortality within 28 days of admission of SAP patients in the ICU.