Establishment and validation of a prediction model for myocarditis in Chinese children below 14 years old: a protocol for a retrospective cohort study.

INTRODUCTION: Paediatric myocarditis, a rare inflammatory disease, often presents without clear early symptoms. Although cardiac troponin I levels can aid in diagnosing myocarditis, they are not definitive indicators. Troponin I levels frequently fluctuate within and outside the reference range, potentially causing misinterpretations by clinicians. Although a negative troponin I result is valuable for excluding myocarditis, its specificity is low. Moreover, the clinical diagnosis of paediatric myocarditis is exceptionally challenging, and accurate early-stage diagnosis and treatment pose difficulties. Currently, the Dallas criteria, involving cardiac biopsy, serves as the gold standard for myocarditis diagnosis. However, this method has several drawbacks and is unsuitable for children, resulting in its limited use. METHODS AND ANALYSIS: In this study, we will employ multiple logistic regression analysis to develop a predictive model for early childhood myocarditis. This model will assess the patient's condition at onset and provide the probability of a myocarditis diagnosis. Model performance will be evaluated for accuracy and calibration, and the results will be presented through receiver operating characteristic (ROC) curves and calibration plots. Clinical decision curve analysis, in conjunction with ROC curve analysis, will be employed to determine the optimal cut-off value and calculate the net clinical benefit value for assessing clinical effectiveness. Finally, internal model validation will be conducted using bootstrapping. ETHICS AND DISSEMINATION: Approval from the Clinical Research Ethics Committee of The Third Affiliated Hospital of Wenzhou Medical University has been obtained. The research findings will be disseminated through presentations at scientific conferences and publication in peer-reviewed journals.

Acetylcysteine increases sensitivity of ceftazidime-avibactam-resistant enterobacterales with different enzymatic resistance to ceftazidime-avibactam in vitro and in vivo.

BACKGROUND: Ceftazidime-avibactam (CZA) improves treatment outcomes for infections caused by carbapenem-resistant organisms, but has led to serious bacterial resistance. Acetylcysteine (NAC) is an approved medication that protects the respiratory tract through antioxidant and anti-inflammatory effects. RESULTS: This study found that NAC combined with CZA effectively inhibits the growth of CZA-resistant clinical Enterobacterales strains. The CZA/NAC combination inhibits biofilm formation in vitro and decreases bacterial burden in a mouse thigh infection model. The combination is biocompatible and primarily increases cell membrane permeability to cause bacterial death. CONCLUSIONS: These findings prove that the CZA/NAC combination has potential as a treatment for CZA-resistant Enterobacterales infections.

Ceftazidime-Decorated Gold Nanoparticles: a Promising Strategy against Clinical Ceftazidime-Avibactam-Resistant Enterobacteriaceae with Different Resistance Mechanisms.

Nanoparticle-based antibiotic delivery systems are essential in combating antibiotic-resistant bacterial infections arising from acquired resistance and/or biofilm formation. Here, we report that the ceftazidime-decorated gold nanoparticles (CAZ_Au NPs) can effectively kill clinical ceftazidime-avibactam-resistant Enterobacteriaceae with various resistance mechanisms. Further study of underlying antibacterial mechanisms suggests that CAZ_Au NPs can damage the bacterial cell membrane and increase the level of intracellular reactive oxygen species. Moreover, CAZ_Au NPs show great potential in inhibiting biofilm formation and eradicating mature biofilms via crystal violet and scanning electron microscope assays. In addition, CAZ_Au NPs demonstrate excellent performance in improving the survival rate in the mouse model of abdominal infection. In addition, CAZ_Au NPs show no significant toxicity at bactericidal concentrations in the cell viability assay. Thus, this strategy provides a simple way to drastically improve the potency of ceftazidime as an antibiotic and its use in further biomedical applications.

Development and validation of a clinical diagnostic model for pregnant women with renal colic in the emergency department in China: a protocol for a retrospective cohort study.

INTRODUCTION: Urolithiasis affects many people throughout their lives. Among the maternal population, although the morbidity of acute urolithiasis in pregnant women is unremarkable, it is the leading cause of hospitalisation during pregnancy. There is no effective clinical diagnostic tool to help doctors diagnose diseases. Our primary aim was to develop and validate a clinical prediction model based on statistical methods to predict the probability of having disease in pregnant women who visited the emergency department because of urolithiasis-induced colic. METHODS AND ANALYSIS: We will use multivariate logistic regression analysis to build a multivariate regression linear model. A receiver operating characteristic curve plot and calibration plot will be used to measure the discrimination value and calibration value of the model, respectively. We will also use least absolute shrinkage and selection operator regression analysis combined with logistic regression analysis to select predictors and construct the multivariate regression model. The model will be simplified to an application that has been reported before, and users will only need to enter their clinical parameters so that risk probability is automatically derived. ETHICS AND DISSEMINATION: The review and approval documents of the clinical research ethics committee have been received from the ethics committee of our hospital (The Third Affiliated Hospital of Wenzhou Medical University). We will disseminate research findings through presentations at scientific conferences and publication in peer-reviewed journals.