Our antimicrobial pharmacist-led intervention included: (a) a structured review of antibiotic prescriptions; (b) educating prescribers on antimicrobial therapy; (c) monthly reporting of department-level rates of blood sampling for culture. Daily review began in May 2018 and was discontinued after 10 months; however, the other interventions were conducted throughout the study period. This study aimed to evaluate the sustained impact of pharmacist’s interventions on antimicrobial therapy and clinical outcomes between the baseline (May–December 2017), intervention (May–December 2018), and post-intervention (May–December 2019) periods. The rate of blood culture collections before starting antipseudomonal agent therapy was significantly increased from the baseline to post-intervention periods (71% vs. 85%, p < 0.001). Antipseudomonal agent therapy was more frequently de-escalated in the post-intervention period than in the baseline period (73% vs. 54%, p = 0.038). Total use of antipseudomonal agents was reduced from the baseline to intervention periods and persisted during the post-intervention period (50.5 vs. 41.8 and 42.6 DDD per 1000 patient-days, p = 0.016 and p = 0.022, respectively). During the study period, there were significant reductions in the incidence of hospital-acquired Clostridioides difficile infection (1.12, 0.54, and 0.51 per 10,000 patient-days, respectively, p = 0.031) and 30-day mortality with bacteremia (19%, 18%, and 12%, respectively, p = 0.005). Our pharmacist-led interventions sustainably achieved appropriate antimicrobial therapy and improved clinical outcomes.

Since 2014, several global and national guidelines have been introduced to address the problem of antimicrobial resistance. We conducted a campaign in a tertiary hospital to promote appropriate quinolone use through educational lectures in 2018. The aim of this retrospective study was to evaluate the changes in the following: prescription characteristics, trend of oral quinolone use, and antibiotic susceptibility of bacteria from 2013 to 2020. Antimicrobial use was assessed as days of therapy per 1000 patient-days. We found a significant reduction in unnecessary antibiotic prescriptions between December 2013 and December 2020. Significant negative trends were detected in the use of quinolones over 8 years (outpatients, coefficient = −0.15655, p < 0.001; inpatients, coefficient = −0.004825, p = 0.0016). In particular, the monthly mean use of quinolones among outpatients significantly decreased by 11% from 2013 to 2014 (p < 0.05) and reduced further by 31% from 2017 to 2020 (p < 0.001). A significant positive trend was observed in the susceptibility of Pseudomonas aeruginosa to levofloxacin (p < 0.001). These results demonstrate that the use of oral quinolones was further reduced following educational intervention and the bacterial susceptibility improved with optimal quinolone usage compared to that in 2013.

Introduction. Timely and accurate diagnosis of bacterial infections enables early administration of appropriate antimicrobial treatment and improved outcomes. Hypothesis/Gap Statement. The accuracy of computer-aided diagnosis (CAD) for identifying organisms on urine Gram stains has not been compared with that of microbiology specialists (MS). Aim. To compare the interpretation of urine Gram-stain results by MS and a CAD app designed using artificial intelligence. Methodology. Urine specimens from patients with urinary tract infections were used and collected at two tertiary hospitals between 1 April and 31 December 2022. Using non-inferiority analysis to assess whether CAD was non-inferior to expert interpretation, CAD-predicted microscopic findings of the Gram-stained slide generated from iPhone camera images from two hospitals were compared with those from ten MS. A total of 153 images were taken from each hospital, and CAD interpreted a total of 306. The primary endpoint was the prediction accuracy based on the morphology of the Gram-stained bacteria. Results. The accuracy (95% confidence interval) of MS and CAD predictions was 83.0% (81.6%–84.3%) and 87.9% (83.7%–91.3%), respectively, with a difference of –4.93% (–8.43% to –0.62%) indicating non-inferiority of CAD. Conclusion. CAD was non-inferior to MS predictions for identifying Gram-stained pathogens; therefore, CAD was suggested to have the potential for guiding empirical antibiotic selection in patients with urinary tract infections.

Background/Objectives: Gram staining is an essential diagnostic technique used for the rapid identification of bacterial and fungal infections, playing a pivotal role in clinical decision-making, especially in point-of-care (POC) settings. Manual staining, while effective, is labor-intensive and prone to variability, relying heavily on the skill of laboratory personnel. Current automated Gram-staining systems are primarily designed for high-throughput laboratory environments, limiting their feasibility in decentralized healthcare settings such as emergency departments and rural clinics. This study aims to introduce and evaluate the Point-of-Care Gram Stainer (PoCGS^®), a compact, automated device engineered for single-slide processing, addressing challenges related to portability, standardization, and efficiency in POC applications. Methods: The PoCGS^® device was developed to emulate expert manual staining techniques through features such as methanol fixation and programmable reagent application. A comparative evaluation was performed using 40 urine samples, which included both clinical and artificial specimens. These samples were processed using PoCGS^®, manual staining by skilled experts, and manual staining by unskilled personnel. The outcomes were assessed based on microbial identification concordance, the staining uniformity, presence of artifacts, and agreement with the culture results. Statistical analyses, including agreement rates and quality scoring, were conducted to compare the performance of PoCGS^® against manual staining methods. Results: PoCGS^® achieved a 100% concordance rate with expert manual staining in terms of microbial identification, confirming its diagnostic accuracy. However, staining quality parameters such as the uniformity and presence of artifacts showed statistically significant differences when compared to skilled and unskilled personnel. Despite these limitations, PoCGS^® demonstrated a comparable performance regarding artifact reduction and agreement with the culture results, indicating its potential utility in POC environments. Challenges such as fixed processing times and limited adaptability to varying specimen characteristics were identified as areas for further improvement. Conclusions: The study findings suggest that PoCGS^® is a reliable and valuable tool for microbial identification in POC settings, with a performance comparable to skilled manual staining. Its compact design, automation, and ease of use make it particularly beneficial for resource-limited environments. Although improvements in staining uniformity and background clarity are required, PoCGS^® has the potential to standardize Gram staining protocols and improve diagnostic turnaround times. Future developments will focus on optimizing staining parameters and expanding its application to other clinical sample types, ensuring robustness and broader usability in diverse healthcare settings.

Rapid and reliable diagnostic methods are essential to ensure appropriate management of acute gastroenteritis. The BioFire FilmArray® Gastrointestinal Panel (FGP) rapidly and accurately identifies various pathogens. However, previous studies on FGP lacked detailed descriptions of its utility in clinical practice. Additionally, pediatric data from Japan are limited. Therefore, we aimed to evaluate the clinical utility of the FGP and identify the characteristics of patients with positive FGP results. We retrospectively reviewed the records of pediatric patients (aged ≤18 years) who underwent FGP testing at Kobe University Hospital in 2024. The pathogens detected and clinical characteristics of FGP-positive and FGP-negative patients were compared. Subgroup analyses were conducted by bacterial- and viral-positive status. The median time from FGP testing to the confirmation of results was 82 min. Of the 67 patients who underwent FGP testing, 28 (42 %) were FGP-positive. The most frequently detected pathogen was norovirus (18 %), followed by Clostridioides difficile toxin A/B (12 %), Campylobacter spp. (4.5 %), Yersinia enterocolitica (4.5 %), Enteroaggregative Escherichia coli (4.5 %), Enteropathogenic Escherichia coli (3 %), astrovirus (3 %), sapovirus (1.5 %), Shiga -like toxin producing Escherichia coli (1.5 %), and Salmonella spp. (1.5 %). No significant differences in clinical findings were observed between FGP-positive and FGP-negative cases. Subgroup analysis revealed frequent vomiting, and significantly shorter fever in patients with viral-positive FGP results than in those with bacterial-positive FGP results. FGP aids clinical decision-making by enabling the early detection of pathogens, such as Campylobacter spp. and Yersinia enterocolitica, which typically require several days for stool culture results.

In our hospital, a full-time pharmacist specializing in antimicrobial therapy joined the newly launched antimicrobial stewardship team in May 2018, and started daily monitoring to optimize the use of broad-spectrum antimicrobials. For the medical staff to better understand antimicrobial therapy, the educational lectures were conducted four times after intervention. This study aimed to evaluate the impact of a full-time pharmacist’s intervention on antimicrobial stewardship. The effects before (May–December 2017) and after the intervention period (May–December 2018) on antibiotic therapy and clinical outcomes were compared. The rate of blood culture collections before starting broad-spectrum antibiotics significantly increased after intervention (71% vs. 82%, p < 0.001), and initially prescribed broad-spectrum antibiotics were significantly de-escalated (55% vs. 78%, p = 0.004). A significant reduction in the monthly use of antipseudomonal antibiotics was observed (50.5 vs. 41.8 defined daily doses per 1000 patient-days, p = 0.01). The incidence of hospital-acquired Clostridioides difficile infection (HA-CDI) significantly decreased after intervention (1.12 vs. 0.54 cases per 10,000 patient-days, p = 0.033). The 30-day mortality rate did not change between the two periods (19.4% vs. 17.7%, p = 0.61). Our intervention ensured appropriate antimicrobial therapy and reduced the incidence of HA-CDI without worsening the clinical outcomes.