Lung ultrasonography as a direct measure of evolving respiratory dysfunction and disease severity in patients with acute pancreatitis

Significance of MCP-1 in predicting the short-term recurrence of primary intussusception in children: An observational study

To evaluate the relationship between the expression level of (MCP-1) in peripheral blood and the short-term recurrence of primary intussusception in children, a retrospective analysis of children with primary intussusception under ultrasound-guided hydrostatic reduction in our hospital from June 2019 to June 2021, a total of 412 cases, 37 cases of short-term recurrence. Enzyme-linked immunosorbent assay was used to detect the expression of MCP-1 in peripheral venous blood; receiver operating curve (ROC) was utilized to evaluate the diagnostic efficacy of MCP-1 in predicting short-term recurrence; logistic regression analysis of risk factors for recurrence. MCP-1 increased in the peripheral blood of children with short-term recurrence (P < .05). Logistic regression analysis found that increased MCP-1 was a risk factor for recurrence; ROC showed that 23.24 ng/mL was used as a cut-off value. The sensitivity of MCP-1 for predicting the recurrence of intussusception in children is 82.14%, and the specificity is 75.67%. In primary intussusception, the expression of MCP-1 in the peripheral blood of children with short-term recurrence is raised. Elevated expression of MCP-1 is a risk factor for predicting short-term intussusception recurrence and has certain clinical significance.

A prediction model for acute respiratory distress syndrome among patients with severe acute pancreatitis: a retrospective analysis

Background:

Acute respiratory distress syndrome (ARDS) is a severe complication among patients with severe acute pancreatitis (SAP), which may be associated with increased mortality in hospitalized patients. Thus, an effective model to predict ARDS in patients with SAP is urgently required.

Methods:

We retrospectively analyzed the data from the patients with SAP who recruited in Xiangya Hospital between April 2017 and May 2021. Patients meeting the Berlin definition of ARDS were categorized into the ARDS group. Logistic regression models and a nomogram were utilized in the study. Descriptive statistics, logistic regression models, and a nomogram were used in the current study.

Results:

Comorbidity of ARDS occurred in 109 (46.58%) of 234 patients with SAP. The SAP patients with ARDS group had a higher 60-day mortality rate, an increased demand for invasive mechanical ventilation, and a longer intensive care unit (ICU) stay than those without ARDS (p < .001 for all). Partial pressure of oxygen (PaO2): fraction of inspired oxygen (FiO2) < 200, platelets <125 × 109/L, lactate dehydrogenase >250 U/L, creatinine >111 mg/dL, and procalcitonin >0.5 ng/mL were independent risk variables for development of ARDS in SAP patients. The area under the curve for the model was 0.814, and the model fit was acceptable [p = .355 (Hosmer–Lemeshow)]. Incorporating these 5 factors, a nomogram was established with sufficient discriminatory power (C-index 0.814). Calibration curve indicated the proper discrimination and good calibration in the predicting nomogram model.

Conclusion:

The prediction nomogram for ARDS in patients with SAP can be applied using clinical common variables after the diagnosis of SAP. Future studies would be warranted to verify the potential clinical benefits of this model.

Use of Lung Ultrasound for Assessment of Lung Recruitment Maneuvers in Patients with ARDS

BACKGROUND: Positive pressure mechanical ventilation is a non-physiological intervention that saves lives but is not free of important side effects. It invariably results in different degrees of collapse of small airways. Recruitment maneuver (RM) aims to resolve lung collapse by a brief and controlled increment in airway pressure while positive end-expiratory pressure (PEEP) afterward keeps the lungs open. Therefore, ideally RM and PEEP selection must be individualized and this can only be done when guided by specific monitoring tools since lung’s opening and closing pressures vary among patients with different lung conditions. AIM: The aim of this study was to explore the clinical value of ultrasonic monitoring in the assessment of pulmonary recruitment and the best PEEP. PATIENTS AND METHODS: This study was conducted on 120 patients, 30 were excluded as in whom lung collapse cannot be confirmed then the rest were 90 patients from whom another 25 patients excluded as they were hemodynamically unstable the rest 65 patients were divided into two groups: Group A: Included 50 mechanically ventilated patients with ARDS, underwent lung recruitment using lung ultrasound and Group B: Included 15 mechanically ventilated patients with ARDS, underwent lung recruitment using oxygenation index. This prospective study was held at many critical care departments around Egypt. RESULTS: We noticed that lung recruitment in both groups significantly increased Pao2/Fio2 ratio immediately after recruitment compared with basal state and also significantly increase dynamic compliance compared with basal state. The increase in PF ratio immediately was significantly more in ultrasound group than in oxygenation group. Furthermore, we noticed that that P/F ratio 12 h after recruitment decreased compared with P/F ratio immediately after recruitment but significantly increased compared with basal state before recruitment and also we found that the increase in P/F ratio 12 h after recruitment was more significantly in lung ultrasound group than in oxygenation group. Furthermore, we noticed that lung recruitment (both lung ultrasound and oxygenation group) significantly increase RV function using TAPSE compared with basal state. Both opening pressure and optimal PEEP were significantly higher in lung ultrasound group than in oxygenation group. In our study, opening pressure was 37.28 ± 1.25 in lung ultrasound group and was 36.67±0.98 in oxygenation group and optimal PEEP was 14.64 ± 1.08 in lung ultrasound group and was 13.13 ± 0.74 in oxygenation group. CONCLUSION: Lung US is an effective mean of evaluating and guiding alveolar recruitment in ARDS. Compared with the maximal oxygenation–guided method, the protocol for reaeration in US-guided lung recruitment achieved a higher opening pressure, resulted in greater improvements in lung aeration, and substantially reduced lung heterogeneity in ARDS.

Saikosaponin A-Induced Gut Microbiota Changes Attenuate Severe Acute Pancreatitis through the Activation of Keap1/Nrf2-ARE Antioxidant Signaling

Objective

Severe acute pancreatitis (SAP) is a serious and life-threatening disease associated with multiple organ failure and a high mortality rate and is accompanied by distinct oxidative stress and inflammatory responses. Saikosaponin A has strong antioxidant properties and can affect the composition of gut microbiota. We sought to determine the effects of Saikosaponin A interventions on SAP by investigating the changes of gut microbiota and related antioxidant signaling.

Methods

A SAP model was established in Sprague-Dawley (SD) rats through the injection of sodium taurocholate into the biliopancreatic duct and confirmed by elevated levels of serum lipase and amylase. The model was fed a standard diet either with saline solution or with Saikosaponin A. Fecal microbiota transplantation (FMT) from Saikosaponin A-induced rats into the rat model was performed to test the effects of gut microbiota. The composition of gut microbiota was analyzed by using 16S rRNA gene sequencing. We measured apoptotic status, inflammatory biomarkers, and Keap1-Nrf2-ARE ((Kelch-like ECH-associated protein 1) nuclear factor erythroid 2-related factor 2-antioxidant response element) antioxidant signaling.

Results

Saikosaponin A intervention attenuated SAP lesions and reduced the levels of serum amylase and lipase, oxidative stress, and inflammatory responses by reducing pathological scores and affecting the serum level of oxidative and inflammatory factors. Meanwhile, the expression of Keap1-Nrf2-ARE was increased. Saikosaponin A intervention improved microbiota composition by increasing the relative abundance of Lactobacillus and Prevotella species. FMT resulted in similar results as those caused by the Saikosaponin A intervention, suggesting Saikosaponin A may exert its function via the improvement of gut microbiota composition.

Conclusions

Saikosaponin A-induced gut microbiota changes attenuate SAP progression in the rat model and may be a potential natural drug for adjuvant treatment of SAP. Further work is needed to clear up the points.

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.

Acute respiratory distress syndrome in acute pancreatitis

Development of organ failure is one of the major determinants of mortality in patients with acute pancreatitis (AP). Acute respiratory distress syndrome (ARDS) is an important cause of respiratory failure in AP and is associated with high mortality. Pathogenesis of ARDS in AP is incompletely understood. Release of various cytokines plays an important role in development of ARDS in AP. Increased gut permeability due to various toxins, inflammatory mediators, and pancreatic enzymes potentiates lung injury by gut-lymph-lung axis leading on to increased translocation of bacterial endotoxins. Various scoring systems, serum levels of various cytokines and lung ultrasound have been evaluated for prediction of development of ARDS in AP with varying results. Various drugs have shown encouraging results in prevention of ARDS in animal models but these encouraging results in animal models are yet to be confirmed in clinical studies. There is no specific effective treatment for ARDS. Treatment of sepsis and local complications of AP should be done according to the standard management strategies. Lung protective ventilatory strategies are of paramount importance to improve outcome of patients of AP with ARDS and therefore effective coordination between gastroenterologists and intensivists is needed for effective management of these patients.

Multifactorial Scores and Biomarkers of Prognosis of Acute Pancreatitis: Applications to Research and Practice

Acute pancreatitis (AP) is a severe inflammation of the pancreas presented with sudden onset and severe abdominal pain with a high morbidity and mortality rate, if accompanied by severe local and systemic complications. Numerous studies have been published about the pathogenesis of AP; however, the precise mechanism behind this pathology remains unclear. Extensive research conducted over the last decades has demonstrated that the first 24 h after symptom onset are critical for the identification of patients who are at risk of developing complications or death. The identification of these subgroups of patients is crucial in order to start an aggressive approach to prevent mortality. In this sense and to avoid unnecessary overtreatment, thereby reducing the financial implications, the proper identification of mild disease is also important and necessary. A large number of multifactorial scoring systems and biochemical markers are described to predict the severity. Despite recent progress in understanding the pathophysiology of AP, more research is needed to enable a faster and more accurate prediction of severe AP. This review provides an overview of the available multifactorial scoring systems and biochemical markers for predicting severe AP with a special focus on their advantages and limitations.

Prediction and evaluation of the severity of acute respiratory distress syndrome following severe acute pancreatitis using an artificial neural network algorithm model

BACKGROUND

To predict the risk and severity of acute respiratory distress syndrome (ARDS) following severe acute pancreatitis (SAP) by artificial neural networks (ANNs) model.

METHODS

ANNs model was constructed by clinical data of 217 SAP patients. The model was first trained on 152 randomly chosen patients, validated and tested on the 33 patients and 32 patients respectively. Statistical analysis was used to assess the value of it.

RESULTS

The training, validation, and test set were not significantly different for 13 variables. After training, ANNs retained excellent pattern recognition ability. When ANNs model was applied to the test set, it revealed a sensitivity of 87.5%, and an accuracy of 84.43%. Significant differences were found between ANNs model and logistic regression model. When ANNs model is used to identify ARDS, the area under ROC was 0.859 + 0.048. Meanwhile, pancreatic necrosis rate, lactic dehydrogenase and oxyhemoglobin saturation were the most important independent variables. Compared with the Berlin definition, the ANN model shows a good accuracy of 73.1% for total severity of ARDS.

CONCLUSION

ANNs model is a valuable tool in dealing with risk prediction of ARDS following SAP. In addition, it can extract informative risk factors of ARDS via the ANNs model.

Artificial neural network algorithm model as powerful tool to predict acute lung injury following to severe acute pancreatitis

OBJECTIVE

The aim of this study is to predict the risk of severe acute pancreatitis (SAP) associated with acute lung injury (ALI) by artificial neural networks (ANNs) model.

METHODS

The ANNs and logistic regression model were constructed using clinical and laboratory data of 217 SAP patients. The models were first trained on 152 randomly chosen patients, validated and tested on the 33 patients and 32 patients respectively. Statistical indices were used to evaluate the value of the forecast in two models.

RESULTS

The training set, validation set and test set were not significantly different for any of the 13 variables. After training, the back propagation network retained excellent pattern recognition ability. When the ANNs model was applied to the test set, it revealed a sensitivity of 87.5%, specificity of 83.3%. The accuracy was 84.43%. Significant differences could be found between ANNs model and logistic regression model in these parameter. When ANNs model was used to identify ALI, the area under receiver operating characteristic curve was 0.859 ± 0.048, which demonstrated the better overall properties than logistic regression modeling (AUC = 0.701 + 0.041) (95% CI: 0.664-0.857). Meanwhile, pancreatic necrosis rate, lactic dehydrogenase and oxyhemoglobin saturation were the important factors among all thirteen independent variable for ALI.

CONCLUSION

The ANNs model was a valuable tool in dealing with the clinical risk prediction problem of ALI following to SAP. In addition, our approach can extract informative risk factors of ALI via the ANNs model.

Thoracic complications of pancreatitis

Acute pancreatitis in its severe form may lead to systemic inflammatory response syndrome and multisystem organ dysfunction. Acute lung injury is an important cause of mortality in the setting of severe acute pancreatitis. Besides lung involvement, acute and chronic pancreatitis may also lead to the involvement of other thoracic compartments, including mediastinum, pleura, and vascular structures. These manifestations are an important cause of morbidity and may pose diagnostic and therapeutic challenges. These manifestations have not been discussed in detail in the available literature. In this review, we discuss the thoracic complications of pancreatitis, including lung, pleural, mediastinal, and vascular manifestations.

Ultrasonic monitoring in the assessment of pulmonary recruitment and the best positive end-expiratory pressure

The aim of this study was to explore the clinical value of ultrasonic monitoring in the assessment of pulmonary recruitment and the best positive end-expiratory pressure (PEEP).Between January 2015 and June 2017, 40 patients with acute respiratory distress syndrome in our hospital were randomly divided into 2 groups: ultrasound group (ULS group; n = 20) and oxygenation group (OXY group; n = 20). The PEEP incremental method was used to perform recruitment maneuvers. Ultrasound scoring and the oxygenation method were used to evaluate the pulmonary recruitment endpoint. The best PEEP was chosen by ultrasound scoring and the oxygenation method after achieving the pulmonary recruitment endpoint and sustaining it for 15 minutes.The oxygenation index, PEEP, peak airway pressure (Ppeak), mean airway pressure (Pmean), and dynamic compliance (Cdyn) in the OXY group were significantly lower than those in the ULS group (P < .05) at the pulmonary recruitment endpoint; however, there was no statistical significance in the mean arterial blood pressure (MAP) or heart rate (HR) (P > .05). The best PEEPs in the OXY and ULS groups were 13.1 ± 3.1 and 15.7 ± 4.2 cmH2O, respectively, with a significant difference between the 2 groups (t = 2.227, P = .016). Compared with the basal state, the Cdyn, oxygenation index, Pmean, and Ppeak in both groups significantly increased after pulmonary recruitment (P < .05). Furthermore, the Cdyn and oxygenation index in the ULS group were significantly higher than those in the OXY group after pulmonary recruitment (P < .05). The HR in both groups significantly increased, and the MAP significantly decreased. Two hours after recruitment, the HR and MAP returned to near basal levels without a significant difference between the 2 groups (P > .05).Lung ultrasound can be used to detect the endpoint of lung recruitment and the best PEEP, with good effects on lung compliance and oxygenation improvement.