OBJECTIVE: Advancements in Artificial Intelligence(AI) have made platforms like ChatGPT increasingly relevant in medicine. This study assesses ChatGPT\'s utility in addressing bacterial infection-related questions and antibiogram-based clinical cases.
METHODS: This study involved a collaborative effort involving infectious disease (ID) specialists and residents. A group of experts formulated six true/false, six open-ended questions, and six clinical cases with antibiograms for four types of infections (endocarditis, pneumonia, intra-abdominal infections, and bloodstream infection) for a total of 96 questions. The questions were submitted to four senior residents and four specialists in ID and inputted into ChatGPT-4 and a trained version of ChatGPT-4. A total of 720 responses were obtained and reviewed by a blinded panel of experts in antibiotic treatments. They evaluated the responses for accuracy and completeness, the ability to identify correct resistance mechanisms from antibiograms, and the appropriateness of antibiotics prescriptions.
RESULTS: No significant difference was noted among the four groups for true/false questions, with approximately 70% correct answers. The trained ChatGPT-4 and ChatGPT-4 offered more accurate and complete answers to the open-ended questions than both the residents and specialists. Regarding the clinical case, we observed a lower accuracy from ChatGPT-4 to recognize the correct resistance mechanism. ChatGPT-4 tended not to prescribe newer antibiotics like cefiderocol or imipenem/cilastatin/relebactam, favoring less recommended options like colistin. Both trained- ChatGPT-4 and ChatGPT-4 recommended longer than necessary treatment periods (p-value = 0.022).
CONCLUSIONS: This study highlights ChatGPT\'s capabilities and limitations in medical decision-making, specifically regarding bacterial infections and antibiogram analysis. While ChatGPT demonstrated proficiency in answering theoretical questions, it did not consistently align with expert decisions in clinical case management. Despite these limitations, the potential of ChatGPT as a supportive tool in ID education and preliminary analysis is evident. However, it should not replace expert consultation, especially in complex clinical decision-making.

Early identification of human pathogens is crucial for the effective treatment of bloodstream infections to prevent sepsis. Since pathogens that are present in small numbers are usually difficult to detect directly, we hypothesize that the behavior of the immune cells that are present in large numbers may provide indirect evidence about the causative pathogen of the infection. We previously applied time-lapse microscopy to observe that neutrophils isolated from human whole-blood samples, which had been infected with the human-pathogenic fungus Candida albicans or C. glabrata, indeed exhibited a characteristic morphodynamic behavior. Tracking the neutrophil movement and shape dynamics over time, combined with machine learning approach, the accuracy for the differentiation between the two Candida species was about 75%. In this study, the focus is on improving the classification accuracy of the Candida species using advanced deep learning methods. We implemented (i) gated recurrent unit (GRU) networks and transformer-based networks for video data, and (ii) convolutional neural networks (CNNs) for individual frames of the time-lapse microscopy data. While the GRU and transformer-based approaches yielded promising results with 96% and 100% accuracy, respectively, the classification based on videos proved to be very time-consuming and required several hours. In contrast, the CNN model for individual microscopy frames yielded results within minutes, and, utilizing a majority-vote technique, achieved 100% accuracy both in identifying the pathogen-free blood samples and in distinguishing between the Candida species. The applied CNN demonstrates the potential for automatically differentiating bloodstream Candida infections with high accuracy and efficiency. We further analysed the results of the CNN using explainable artificial intelligence (XAI) techniques to understand the critical features and patterns, thereby shedding light on potential key morphodynamic characteristics of neutrophils in response to different Candida species. This approach could provide new insights into host-pathogen interactions and may facilitate the development of rapid, automated diagnostic tools for differentiating fungal species in blood samples.

BACKGROUND: Evidence has shown that short courses of antibiotic therapy are at least as effective as long courses with better clinical outcomes. CAZ/AVI has demonstrated its clinical efficacy in treating K. pneumoniae-KPC infections.
METHODS: We conducted an analysis based on the real-life data of our ten years retrospective cohort to assess the cost-effectiveness and cost-utility of a short course of CAZ/AVI plus source control compared to a long course plus source control. A Markov model was structured. Patient transition between health states was modeled, each transition has a probability, and each state has a cost and a utility. Incremental cost-effectiveness ratios (ICERs) were obtained by dividing the difference in costs by the difference in utilities between the two courses. Input parameter uncertainty was investigated through sensitivity analysis. We launched 1000 Monte Carlo simulations by iteratively perturbing variables within estimated variation ranges, obtaining an ICER result for each simulation.
RESULTS: In the first model (old appropriate treatment), a short course of treatment was associated with reduced costs per patient per year of €4818.60 and reduced effects (0.10 QALYs), compared to a long course. In the CAZ/AVI model, the short course was associated with increased costs of €1297.9 and with increased effects (0.04 QALYs), resulting in an ICER of €32,317.82 per QALY gained, below the WTP threshold of €40,000.
CONCLUSIONS: Our findings highlight additional evidence regarding the cost-effectiveness of CAZ/AVI for policy-makers. We outline that CAZ/AVI could be cost-effective compared to old appropriate antibiotic therapies for KPC-Kp BSI.

Bacteremia caused by extended-spectrum β-lactamases-producing Enterobacterales has increased rapidly and is mainly attributed to CTX-M enzymes. This study aimed to evaluate the NG-Test® CTX-M MULTI lateral flow assay (CTX-M LFA) for rapid detection of CTX-M producers in blood cultures (BCs) positive for Gram-negative bacilli in spiked and clinical BCs. Retrospective testing was performed on BC bottles spiked with a collection of well-characterized Enterobacterales isolates producing CTX-M (n = 15) and CTX-M-like (n = 27) β-lactamases. Prospective testing of clinical, non-duplicate BCs (n = 350) was performed in two hospital microbiology laboratories from April 2021 to March 2022 following detection of Gram-negative bacilli by microscopic examination. Results were compared against molecular testing as the reference. In the spiked BCs, the CTX-M LFA correctly detected all CTX-M producers including 5 isolates with hybrid CTX-M variants. However, false-positive results were observed for several CTX-M-like β-lactamases, including OXY-1-3, OXY-2-8, OXY-5-3, FONA-8, -9, -10, 11, 13 and SFO-1. In clinical BCs, the CTX-M LFA showed 100% (95% CI, 96.0-100%) sensitivity and 99.6% (97.9-100%) specificity. In conclusion, this study showed that rapid detection of CTX-M producers in BC broths can be reliably achieved using the CTX-M LFA, thus providing an opportunity for early optimization of antibiotics.

We narratively reviewed the physiopathology, epidemiology, and management of co-infections in Clostridioides difficile colitis (CDI) by searching the following keywords in Embase, MedLine, and PubMed: \"Clostridium/Clostridioides difficile\", \"co-infection\", \"blood-stream infection\" (BSI), \"fungemia\", \"Candida\", \"Cytomegalovirus\", \"probiotics\", \"microbial translocation\" (MT). Bacterial BSIs (mainly by Enterobacteriaceae and Enterococcus) and fungemia (mainly by Candida albicans) may occur in up to 20% and 9% of CDI, increasing mortality and length of hospitalization. Up to 68% of the isolates are multi-drug-resistant bacteria. A pivotal role is played by gut dysbiosis, intestinal barrier leakage, and MT. Specific risk factors are represented by CDI-inducing broad-spectrum antibiotics, oral vancomycin use, and CDI severity. Probiotics administration (mainly Saccharomyces and Lactobacillus) during moderate/severe CDI may favor probiotics superinfection. Other co-infections (such as Cytomegalovirus or protozoa) can complicate limited and specific cases. There is mounting evidence that fidaxomicin, bezlotoxumab, and fecal microbiota transplantation can significantly reduce the rate of co-infections compared to historical therapies by interrupting the vicious circle between CDI, treatments, and MT. Bacterial BSIs and candidemia represent the most common co-infections in CDI. Physicians should be aware of this complication to promptly diagnose and treat it and enforce preventive strategies that include a more comprehensive consideration of newer treatment options.

Early and accurate detection of pathogens is important to improve clinical outcomes of bloodstream infections (BSI), especially in the case of drug-resistant pathogens. In this study, we aimed to develop a culture-independent digital PCR (dPCR) system for multiplex detection of major sepsiscausing gram-negative pathogens and antimicrobial resistance genes using plasma DNA from BSI patients. Our duplex dPCR system successfully detected nine targets (five bacteria-specific targets and four antimicrobial resistance genes) through five reactions within 3 hours. The minimum detection limit was 50 ag of bacterial DNA, suggesting that 1 CFU/ml of bacteria in the blood can be detected. To validate the clinical applicability, cell-free DNA samples from febrile patients were tested with our system and confirmed high consistency with conventional blood culture. This system can support early identification of some drug-resistant gram-negative pathogens, which can help improving treatment outcomes of BSI.

UNASSIGNED: To elucidate the in-hospital and long-term outcomes of infective endocarditis (IE) in end-stage kidney disease (ESKD) patients on chronic dialysis and to analyze the risk factors of mortality.
UNASSIGNED: The case files of 1,817 patients who were hospitalized for IE over a 14-year period were retrospectively reviewed. Of these, 116 ESKD patients on chronic dialysis were enrolled in this study. Cox\'s proportional hazard model was used to evaluate the risk factors of mortality and long-term outcomes.
UNASSIGNED: The in-hospital mortality rate of the 116 enrolled patients was as high as 43.1%. Patients who survived the index admission had a three-year mortality rate of 33%. Univariate analysis was used to compare survivors and non-survivors; poor in-hospital outcomes were associated with the use of a tunneled cuffed catheter for dialysis access, a shorter duration hospitalization, shock or respiratory failure during hospitalization, a higher white blood count, a higher percentage of polymorphonuclear leukocytes, a higher C-reactive protein level, a lower serum albumin level, and a higher total bilirubin level. Following multivariate adjustment, shock (odds ratio, 9.29, with a 95% confidence interval [CI] of 2.78 to 34.24; p<0.001) or respiratory failure (odds ratio, 25.16, with a 95% CI of 5.63 to 153.54; p<0.001) during hospitalization was strongly associated with increased in-hospital mortality. Patients who underwent cardiac operations (odds ratio, 0.22, with a 95% CI of 0.052 to 0.86; p=0.031) had better in-hospital outcomes. Heart failure reduced ejection fraction (HFrEF) at the time of initial hospitalization was an independent risk factor for 3-year mortality (hazard ratio, 3.48, with a 95% CI of 1.09 to 11.09; p=0.035).
UNASSIGNED: The outcomes of IE for ESKD patients on chronic dialysis were poor. Only 56.9% of these patients survived the index admission and their mortality rate over three years was 33%. Shock or respiratory failure during hospitalization was associated with increased in-hospital mortality. Patients who underwent cardiac operations had better in-hospital outcomes. HFrEF at the time of initial hospitalization was an independent risk factor for three-year mortality.

There has been scarce evidence about deaths due to blood stream infection (BSI) in Japan so far. The main objective of this study is to understand the epidemiological trend of deaths caused by BSIs due to Staphylococcus aureus and Escherichia coli including Methicillin-resistant S. aureus (MRSA) and fluoroquinolone-resistant E. coli (FQREC) at national level. We annually estimated the number of BSI caused by S. aureus and E. coli between 2011 and 2017 across Japan using comprehensive data of bacterial culturing and drug susceptibilities collected in Japan Nosocomial Infection Surveillance (JANIS). The number of death was estimated by using BSI mortality obtained from previous studies in Japan. The number of BSI death attributable to S. aureus was estimated to 17,412 in 2011 and 17,157 in 2017, respectively, out of the whole population (126.8 million) in Japan. Among them, cases attributed to MRSA accounted for 5924 (34.0%) in 2011, and decreased to 4224 (24.6%) cases in 2017. On the other hand, the number of BSI death attributable to E. coli was estimated to 9044 in 2011 and increased to 14,016 in 2017. Among them, cases attributed to FQREC accounted for 2045 (22.6%) in 2011 and increased to 3915 (27.9%) cases in 2017. The number of BSI death attributable to MRSA has been decreasing and that attributable to FQREC has been increasing. This study provides the first annual estimate of disease burden of BSI caused by antimicrobial resistant (AMR) bacteria in Japan, and basis for formulating health policy to deal with AMR.

Candida pararugosa is a yeast that has been previously isolated in various human specimens. The first reported isolation was from human feces in 1998, with subsequent reports of positive cultures from the oral cavity where it was thought to represent colonization rather than true infection. Though it has been isolated from other human sites, its clinical significance and manifestations are poorly characterized. We report the case of a 39-year-old woman on parenteral hyperalimentation who developed post abdominal surgery sepsis and surgical wound necrotizing fasciitis. Candida pararugosa was isolated from two different blood cultures and the patient\'s clinical status improved after initiation of therapy with micafungin. Though it was not clear whether sepsis was driven by the candidemia or the necrotizing fasciitis or both, this report appears to be the first case of Candida pararugosa bloodstream infection described in an adult.

BACKGROUND: Bloodstream infection following a transrectal prostate biopsy is a well-known and feared complication. Previous studies have shown an increase in multi-resistant bacterial infections as a consequence of higher usage of antibiotics in investigated populations. Our aim was to analyze bacterial resistance patterns in positive blood cultures, after prostate biopsies in Stockholm, Sweden, where the use of antibiotics has been low and decreasing during the last 10 years.
METHODS: From the three pathology laboratories in Stockholm, reports of prostate examinations were retrieved (n = 56,076) from 2003 to 2012. By linking men to the National Patient Register all but prostate core biopsies were excluded (n = 12,024). Prostate biopsies in men younger than 30 years of age were excluded (n = 5) leaving 44,047 biopsies for analysis. From laboratory information systems data regarding blood cultures were retrieved. Proportions of blood cultures within 30 days by year were calculated. Crude and adjusted logistic regression models were used to estimate ORs.
RESULTS: In total, 44,047 prostate biopsies were performed in 32,916 men over 10 years. On 620 occasions a blood culture was drawn within 30 days of the biopsy; 266 of these were positive. The proportions with positive blood cultures in 2003 and 2012 were 0.38 and 1.14%, respectively. The proportion of multidrug-resistant bacteria increased significantly during the study. In the crude and the adjusted analysis, the year of biopsy and Charlson Comorbidity Index were associated with the risk of having a positive blood culture.
CONCLUSIONS: Multidrug-resistant enteric bacilli are becoming a problem in Sweden, despite low antimicrobial use. Men need to be informed about the increasing risks of infectious complications of transrectal prostate biopsy. One out of 50 men undergoing a prostate biopsy will develop symptoms suggestive of a bloodstream infection after the biopsy and one in 100 men will have a positive blood culture.