Objective: This study analyzed the urine cultures of emergency department patients diagnosed with acute uncomplicated cystitis and determined the antimicrobial resistance and appropriate treatment for our region. Methods: Results of urine analysis and urine culture of acute uncomplicated cystitis patients diagnosed in our emergency department between January 2019 and December 2020 were examined and analyzed. Results: In our study, 256 out of 340 urine culture samples (75.3%) were positive for cystitis. The most common microorganism was reported to be Escherichia coli (93.0%). The resistance rates of E. coli to the following antimicrobial agents were as follows: amikacin (0.0%), ampicillin (63.5%), amoxicillin/clavulanate (15.6%), aztreonam (7.1%), ceftazidime (3.4%), cefotaxime (16.4%), cefoxitin (5.5%), cefazolin (19.9%), ciprofloxacin (29.4%), cefepime (1.7%), ertapenem (0.0%), gentamicin (18.1%), piperacillin/tazobactam (2.1%), trimethoprim/sulfamethoxazole (36.1%), and tigecycline (0.4%). The prevalence of extended-spectrum beta-lactamase producing E. coli strains was 17.8%. Conclusion To determine the proper empirical antimicrobial treatment for acute uncomplicated cystitis, it is essential to examine the antimicrobial resistance. For our region, fosfomycin, nitrofurantoin, and 2nd and 3rd generation cephalosporin should be considered the first-line empirical treatment for acute uncomplicated cystitis.

Objective: The purpose of this study was to develop a machine learning-based model (eXtreme Gradient boost [XGBoost]) that can accurately predict the severity of acute cholangitis in patients. The model was designed to simplify the classification process compared to conventional methods. Methods: We retrospectively collected data from patients with cholangitis who visited the emergency department of a secondary medical institution in Seongnam, Korea from January 1, 2015 to December 31, 2019. The patients were divided into three groups (Grade I, II, III) based on severity according to the Tokyo Guidelines 2018/2013 (TG18/13) severity assessment criteria for cholangitis. We used algorithms to select variables of high relevance associated with the grade of severity. For the XGBoost models, data were divided into a train set and a validation set by the random split method. The train set was trained in XGBoost models using only the top seven variables. The area under the receiver operating characteristic (AUROC) and the area under the precision-recall curve (AUPRC) were obtained from the validation set. Results: 796 patients were enrolled. The top 7 variables associated with the grade of severity were albumin, white blood cells, blood urea nitrogen, troponin T, platelets, creatinine, prothrombin time, and international normalized ratio. The AUROC values were 0.881 (Grade I), 0.836 (Grade II), and 0.932 (Grade III). The AUPRC values were 0.457 (Grade I), 0.820 (Grade II), and 0.880 (Grade III). Conclusion We believe that the developed XGBoost model is a useful tool for predicting the severity of acute cholangitis with high accuracy and fewer variables than the conventional severity classification method.

Objective: This study examined the predictive factors to decide the surgical treatment for clinically suspected pediatric acute appendicitis with equivocal imaging findings. Methods: This study was conducted retrospectively on children who visited local emergency medical centers and outpatients from January 2018 to February 2021. The electronic medical records were reviewed from 811 pediatric patients younger than 16 years of age with the chief complaint of abdominal pain and who underwent an imaging test for the clinical suspicion of appendicitis. Ninety-two patients who showed ambiguous findings on imaging tests but were still suspected of having appendicitis were analyzed. Recursive partitioning analysis and multivariable logistic regression were used to identify the variables associated with appendicitis. Results: Of the 92 enrolled patients, 23 patients were confirmed to have appendicitis, and 69 did not. Patients with the clinical suspicion who had an elevated white blood cell (WBC) count, polymorphonuclear leukocyte differential count (PMN), absolute neutrophil count (ANC), and leukocytosis were more likely to have appendicitis. The PMN (odds ratio=1.175; 95% confidence interval, 1.092-1.265) and ANC (odds ratio=1.00050; 95% confidence interval, 1.00025-1.00075) remained significant after multivariable logistic analysis. Conclusion Elevated PMN and ANC are clinical predictors of pediatric appendicitis when the imaging findings are nondiagnostic, and the clinical suspicion is continuous.