BACKGROUND: Artificial intelligence (AI)-based tools can reshape healthcare practice. This includes ChatGPT which is considered among the most popular AI-based conversational models. Nevertheless, the performance of different versions of ChatGPT needs further evaluation in different settings to assess its reliability and credibility in various healthcare-related tasks. Therefore, the current study aimed to assess the performance of the freely available ChatGPT-3.5 and the paid version ChatGPT-4 in 10 different diagnostic clinical microbiology case scenarios.
METHODS: The current study followed the METRICS (Model, Evaluation, Timing/Transparency, Range/Randomization, Individual factors, Count, Specificity of the prompts/language) checklist for standardization of the design and reporting of AI-based studies in healthcare. The models tested on December 3, 2023 included ChatGPT-3.5 and ChatGPT-4 and the evaluation of the ChatGPT-generated content was based on the CLEAR tool (Completeness, Lack of false information, Evidence support, Appropriateness, and Relevance) assessed on a 5-point Likert scale with a range of the CLEAR scores of 1-5. ChatGPT output was evaluated by two raters independently and the inter-rater agreement was based on the Cohen\'s κ statistic. Ten diagnostic clinical microbiology laboratory case scenarios were created in the English language by three microbiologists at diverse levels of expertise following an internal discussion of common cases observed in Jordan. The range of topics included bacteriology, mycology, parasitology, and virology cases. Specific prompts were tailored based on the CLEAR tool and a new session was selected following prompting each case scenario.
RESULTS: The Cohen\'s κ values for the five CLEAR items were 0.351-0.737 for ChatGPT-3.5 and 0.294-0.701 for ChatGPT-4 indicating fair to good agreement and suitability for analysis. Based on the average CLEAR scores, ChatGPT-4 outperformed ChatGPT-3.5 (mean: 2.64±1.06 vs. 3.21±1.05, P=.012, t-test). The performance of each model varied based on the CLEAR items, with the lowest performance for the \"Relevance\" item (2.15±0.71 for ChatGPT-3.5 and 2.65±1.16 for ChatGPT-4). A statistically significant difference upon assessing the performance per each CLEAR item was only seen in ChatGPT-4 with the best performance in \"Completeness\", \"Lack of false information\", and \"Evidence support\" (P=0.043). The lowest level of performance for both models was observed with antimicrobial susceptibility testing (AST) queries while the highest level of performance was seen in bacterial and mycologic identification.
CONCLUSIONS: Assessment of ChatGPT performance across different diagnostic clinical microbiology case scenarios showed that ChatGPT-4 outperformed ChatGPT-3.5. The performance of ChatGPT demonstrated noticeable variability depending on the specific topic evaluated. A primary shortcoming of both ChatGPT models was the tendency to generate irrelevant content lacking the needed focus. Although the overall ChatGPT performance in these diagnostic microbiology case scenarios might be described as \"above average\" at best, there remains a significant potential for improvement, considering the identified limitations and unsatisfactory results in a few cases.

This case report presents a difficult-to-diagnose case of American tegumentary leishmaniasis (ATL) caused by Leishmania (Viannia) guyanensis in a 24-year-old Hispanic male with a travel history to the Panama jungle, an endemic region for tropical infectious diseases. The patient initially presented with persistent skin lesions that progressed to abscesses with ulceration. Despite negative initial diagnostic tests, including microbiological investigations and histopathological examination, a comprehensive diagnostic workup and subsequent polymerase chain reaction (PCR) confirmed the presence of Leishmania parasites. This case underscores the need to consider tropical infectious diseases despite initial negative tests. Accurate species identification is vital for proper drug treatment, with miltefosine as an emerging option. Early, precise diagnosis and tailored management are essential for successful treatment. This report emphasizes the significance of conducting a comprehensive diagnostic workup, including PCR, in individuals with a history of travel to endemic regions, to accurately diagnose and effectively manage complex infectious diseases.

Background Accurate interpretation of antibiotic susceptibility testing (AST) is one of the most crucial functions of the microbiology laboratory. However, its performance depends on a number of critical factors. We conducted a status survey to understand the existing practices in Indian laboratories that have a potential to influence performance of AST. Method We developed a 22-point online survey questionnaire on information about respondent\'s specifications, use of AST consumables, existing quality control protocols, and matters of contention in AST practices, and sent it by Google forms to 362 clinical microbiologists (holding MD or DNB certification). Participation was voluntary. Results were analyzed using descriptive statistics. Results Among 362, a total of 103 returned the questionnaire. The first 100 responses that were complete (all 22 questions answered) were analyzed. Respondents were from medical colleges (61%), private hospitals (26%), and stand-alone laboratories (13%). Analysis revealed that the Clinical & Laboratory Standards Institute (CLSI) guidelines were followed by all. Overall, 54% used disc diffusion as the primary method for performing AST. For the internal quality control testing of media and AST, 24% and 16% had adequate testing components and frequency, respectively. For performing AST of colistin, broth microdilution was used by 19%. Also, 86% participated in external quality control programs, and 54% respondents were dissatisfied or unsure about the development of competencies in AST methodology during their postgraduate training. Conclusion This survey reveals that potential gaps exist in the performance parameters and internal quality control of AST. There is an urgent need for harmonization in AST performance and postgraduate training in clinical microbiology in India.