A nomogram for predicting the risk of mortality in patients with acute pancreatitis and Gram-negative bacilli infection

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

Objective

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

Methods

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

Results

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

Conclusion

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

Preliminary construction of a microecological evaluation model for uranium-contaminated soil

With the extensive development of nuclear energy, soil uranium contamination has become an increasingly prominent problem. The development of evaluation systems for various uranium contamination levels and soil microhabitats is critical. In this study, the effects of uranium contamination on the carbon source metabolic capacity and microbial community structure of soil microbial communities were investigated using Biolog microplate technology and high-throughput sequencing, and the responses of soil biochemical properties to uranium were also analyzed. Then, ten key biological indicators as reliable input variables, including arylsulfatase, biomass nitrogen, metabolic entropy, microbial entropy, Simpson, Shannon, McIntosh, Nocardioides, Lysobacter, and Mycoleptodisus, were screened by random forest (RF), Boruta, and grey relational analysis (GRA). The optimal uranium-contaminated soil microbiological evaluation model was obtained by comparing the performance of three evaluation methods: partial least squares regression (PLS), support vector regression (SVR), and improved particle algorithm (IPSO-SVR). Consequently, partial least squares regression (PLS) has a higher R2 (0.932) and a lower RMSE value (0.214) compared to the other. This research provides a new evaluation method to describe the relationship between soil ecological effects and biological indicators under nuclear contamination.

Nurse Supervised at Institutes versus Nurse Counseling Home-Based Resistance Exercise Training for Acute Pancreatitis

BACKGROUND

The physical and mental quality of life of patients with acute pancreatitis is poor. Professional nurses have the necessary knowledge, art, and skills to aid in resistance exercise training.

AIMS

To evaluate the effectiveness of 6 months of nurse-supervised resistance exercise training plus nutritional supplements and 6 months of nurse counseling home-based resistance exercise training plus nutritional supplements for patients with pancreatitis.

METHODS

Patients with acute pancreatitis (age ≥ 18 years) received nurse-supervised resistance exercise training at the institute (NEN cohort, n = 103), nurse counseling for home-based resistance exercise (HEN cohort, n = 123), or usual care (UCN cohort, n = 155) for 6 months. All patients received advice regarding nutritional especially protein supplements.

RESULTS

Before non-treatment intervention(s) (BL), quality of life score of patients was 53, mild-to-moderate self-reported pain episodes, or worse pain, and a total of 22% of patients were disabled. Patients in the NEN cohort had improved quality of life and decreased pain and disability after 6 months of non-treatment intervention(s) (EL) compared to their BL condition and those of the UCN and HEN cohorts at EL (p < 0.05 for all). A smaller number of patients were hospitalized and died in the NEN cohort than in the UCN and HEN cohorts (p ≤ 0.001 for both) during the follow-up period.

CONCLUSION

The quality of life, pain, and disability condition(s) of patients with acute pancreatitis should be improved. Nurse-supervised resistance exercise training at the institute associated with improvement in the quality of life and decrease of pain, disability, hospitalization, and death of patients with acute pancreatitis.

The Role of the Gut Microbiome in the Development of Acute Pancreatitis

With the explosion research on the gut microbiome in the recent years, much insight has been accumulated in comprehending the crosstalk between the gut microbiota community and host health. Acute pancreatitis (AP) is one of the gastrointestinal diseases associated with significant morbidity and subsequent mortality. Studies have elucidated that gut microbiota are engaged in the pathological process of AP. Herein, we summarize the major roles of the gut microbiome in the development of AP. We then portray the association between dysbiosis of the gut microbiota and the severity of AP. Finally, we illustrate the promises and challenges that arise when seeking to incorporate the microbiome in acute pancreatitis treatment.

A Practical Nomogram for Predicting the Bleeding Risk in Patients with a History of Myocardial Infarction Treating with Aspirin

BACKGROUND

Aspirin is a widely used antiplatelet medication to prevent blood clots, reducing the risk of cardiovascular event. Healthcare providers need to be mindful of the risk of aspirin-induced bleeding and carefully balancing its benefits against potential risks. The objective of this study was to create a practical nomogram for predicting bleeding risk in patients with a history of myocardial infarction treating with aspirin.

METHODS

A total of 2099 myocardial infarction patients with aspirin were enrolled. The patients were randomly divided into two groups, with a 7:3 ratio, for model development and internal validation. Boruta analysis was utilized to identify clinically significant features associated with bleeding. Logistic regression model based on independent bleeding risk factors was constructed and presented as a nomogram. Model performance was assessed from three aspects: identification, calibration, and clinical utility.

RESULTS

Boruta analysis identified eight clinical features from 25, and further multivariate logistic regression analysis selected four independent risk factors: hemoglobin, platelet count, previous bleeding, and sex. A visual nomogram was created based on these variables. The model achieved an area under the curve of 0.888 (95% CI: 0.845-0.931) in the training dataset and 0.888 (95% CI: 0.808-0.968) in the test dataset. Calibration curve analysis showed close approximation to the ideal curve. Decision curve analysis demonstrated favorable clinical net benefit for the model.

CONCLUSIONS

Our study focused on creating and validating a model to evaluate bleeding risk in patients with a history of myocardial infarction treated with aspirin, which demonstrated outstanding performance in discrimination, calibration, and net clinical benefit.

Acute Pancreatitis-Drivers of Hospitalisation Cost-A Seven-Year Retrospective Study from a Large Tertiary Center

(1) Introduction: Acute pancreatitis (AP) remains a global burden of cost for healthcare services. We found a high degree of heterogeneity in cost-related reports and a scarcity of data regarding the cost of AP episodes in European and Asian populations. We aimed to estimate the median daily cost of hospitalisation (DCH) of AP in our population. Our secondary aims included estimating the total cost of hospitalisation (TCH) and the total cost of AP in Romania, as well as assessing the correlation between median DCH and ward, age, sex, length of stay (LoS), intensive care unit (ICU), outcome, severity, morphology, and aetiology of AP. (2) Material and methods: This retrospective cohort study included 1473 cases recruited from the electronic health records of the University Emergency Hospital of Bucharest. Statistical tests used included Kolmogorov-Smirnov, Kruskal-Wallis with post-hoc Dunn-Bonferroni, and Pearson correlation two-tailed. (3) Results: We found a median DCH of AP of USD 203.8 and a median TCH of USD 1360.5. The total yearly cost of AP in Romania was estimated at around USD 19 million. The majority of males with AP (61.8%) were mostly discharged as healed/ameliorated (83.8%); a majority had local complications (55.4%), which were mostly alcohol-related (35.1%). Regarding the aetiology, biliary-related AP was a cost driver, with significant statistical differences observed in all studied groups (p < 0.01). Morphology assessment revealed that acute necrotic collections were associated with high cost and meaningful disparities among the groups (p < 0.01). Cost was also associated with severity, with significant deviations among all groups (p < 0.01). Outcome-at-discharge as deceased correlated with higher costs, with substantial differences within groups (p < 0.01). The need for an intensive care unit was also a large driver of cost (p < 0.01). Females were prone to more expensive costs (p < 0.01). Surgical cases necessitated more financial resources (p < 0.01). (4) Conclusions: To the best of our knowledge, this is the first study on the cost of AP in Romania. Our findings showed that the drivers of increased AP costs might be older age, ICU, intra-hospital mortality, severe AP, local complications such as acute necrotic collections, biliary aetiology, and female sex. We found large heterogeneity and scarcity regarding cost-related data in the literature.

Clinical Characteristics, Drug Resistance, and Risk Factors for Death of Klebsiella pneumoniae Infection in Patients with Acute Pancreatitis: A Single-Center Retrospective Study from China

Objective

Infection is a common complication of acute pancreatitis (AP). Klebsiella pneumoniae (KP) is one of the most common pathogens associated with nosocomial infections. Our study focuses on investigating the clinical characteristics and risk factors for death of Klebsiella pneumoniae infections in AP patients, further to quantify the prognosis of the patients, and provide evidence for guiding antibiotic use and improving prognosis.

Methods

The data of epidemiology, clinical manifestations and drug resistance rate with K. pneumoniae infections in AP patients from January 1, 2012 to August 30, 2022 were retrospectively collected. Logistic regression model and Cox regression model were, respectively, used to determine the risk factors for carbapenem-resistant Klebsiella pneumoniae (CRKP) acquisition and death. The nomogram prediction model was built by RMS software package to predict the 90-day survival rate.

Results

One hundred and twenty-six AP patients combined with K. pneumoniae infections, with a mortality rate of 34.9%. The most common infection sites were pancreas and peri-pancreas (54.8%), followed by lung (20.6%) and blood stream (18.3%). The resistance rate of K. pneumoniae to commonly used antibiotics in clinical practice was high, especially CRKP, which was only sensitive to sulfamethoxazole-trimethoprim (SMZ-TMP) and tigecycline (TGC) (resistance rates were 37.57% and 17.57%, respectively). Independent risk factors for CPKP acquisition were male (OR = 1.655, 95% CI 0.642-4.265, P = 0.017) and PICC/CVC implantation (OR = 3.157, 95% CI 1.223-8.147, P = 0.021). Independent risk factors for mortality included carbapenem resistance (HR = 2.556, 95% CI 1.011-6.462, P = 0.047), hemorrhage (HR = 2.392, 95% CI 1.104-5.182, P = 0.027), septic shock (HR = 3.022, 95% CI 1.312-6.959, P = 0.009), age >60 years (HR = 2.977, 95% CI 1.303-6.799, P = 0.01), creatinine >177μmol/L (HR = 2.815, 95% CI 1.075-7.369, P = 0.035).

Conclusion

K. pneumoniae infection has become a serious threat for AP patients, which recommends us more attention and active new strategies seeking.

Carbapenem-resistant gram-negative bacterial infection in intensive care unit patients: Antibiotic resistance analysis and predictive model development

In this study, we analyzed the antibiotic resistance of carbapenem-resistant gram-negative bacteria (CR-GNB) in intensive care unit (ICU) patients and developed a predictive model. We retrospectively collected the data of patients with GNB infection admitted to the ICU of the First Affiliated Hospital of Fujian Medical University, who were then divided into a CR and a carbapenem-susceptible (CS) group for CR-GNB infection analysis. Patients admitted between December 1, 2017, and July 31, 2019, were assigned to the experimental cohort (n = 205), and their data were subjected to multivariate logistic regression analysis to identify independent risk factors for constructing the nomogram-based predictive model. Patients admitted between August 1, 2019, and September 1, 2020, were assigned to the validation cohort for validating the predictive model (n = 104). The Hosmer-Lemeshow test and receiver operating characteristic (ROC) curve analysis were used to validate the model's performance. Overall, 309 patients with GNB infection were recruited. Of them, 97 and 212 were infected with CS-GNB and CR-GNB, respectively. Carbapenem-resistant Klebsiella pneumoniae (CRKP), carbapenem-resistant Acinetobacter baumannii (CRAB) and carbapenem-resistant Pseudomonas aeruginosa (CRPA) were the most prevalent CR-GNB. The multivariate logistic regression analysis results of the experimental cohort revealed that a history of combination antibiotic treatments (OR: 3.197, 95% CI: 1.561-6.549), hospital-acquired infection (OR: 3.563, 95% CI: 1.062-11.959) and mechanical ventilation ≥ 7 days (OR: 5.096, 95% CI: 1.865-13.923) were independent risk factors for CR-GNB infection, which were then used for nomogram construction. The model demonstrated a good fit of observed data (p = 0.999), with an area under the ROC curve (AUC) of 0.753 (95% CI: 0.685-0.820) and 0.718 (95% CI: 0.619-0.816) for the experimental and validation cohort, respectively. The decision curve analysis results suggested that the model has a high practical value for clinical practice. The Hosmer-Lemeshow test indicated a good fit of the model in the validation cohort (p-value, 0.278). Overall, our proposed predictive model exhibited a good predictive value in identifying patients at high risk of developing CR-GNB infection in the ICU and could be used to guide preventive and treatment measures.