Background/Objectives: Rare diseases often present challenges in obtaining reliable and accurate information than common diseases owing to their low prevalence. Patients and families often rely on self-directed learning, but understanding complex medical information can be difficult, increasing the risk of misinformation. This study aimed to evaluate whether generative artificial intelligence (AI) provides accurate and non-harmful answers to rare disease-related questions and assesses its utility in supporting patients and families requiring genetic counseling. Methods: We evaluated four generative AI models available between 22 September and 4 October 2024: ChatGPT o1-Preview, Gemini advanced, Claude 3.5 sonnet, and Perplexity sonar huge. A total of 102 questions targeting four rare diseases, covering general information, diagnosis, treatment, prognosis, and counseling, were prepared. Four evaluators scored the responses for professionalism and accuracy using the Likert scale (1: poor, 5: excellent). Results: The average scores ranked the AI models as: ChatGPT (4.24 ± 0.73), Gemini (4.15 ± 0.74), Claude (4.13 ± 0.82), and Perplexity (3.35 ± 0.80; p < 0.001). Perplexity had the highest proportion of scores of 1 (very poor) and 2 (poor) (7.6%, 31/408), followed by Gemini (2.0%, 8/408), Claude (1.5%, 6/408), and ChatGPT (1.5%, 6/408). The accuracy of responses in the counseling part across all four diseases was significantly different (p < 0.001). Conclusions: The four generative AI models generally provided reliable information. However, occasional inaccuracies and ambiguous references may lead to confusion and anxiety among patients and their families. To ensure its effective use, recognizing the limitations of generative AI and providing guidance from experts regarding its proper utilization is essential.

We evaluated the impact of the FilmArray blood culture identification (BCID) panel on the time taken to administer effective antibiotics and the clinical outcomes of bloodstream infections. We retrospectively screened patients with bloodstream infections who underwent BCID testing and compared them to a historical control group that received conventional culture testing. A total of 144 and 214 patients who underwent BCID and conventional cultures, respectively, were compared. The 30-day mortality (BCID: 9.7% vs. conventional method: 10.7%, p = 0.755), time to effective antibiotic administration (3 h for both BCID and conventional method, p = 0.789), and time to appropriate antibiotic administration did not differ significantly between the groups. BCID was not significantly associated with 30-day mortality after adjusting for the Pitt bacteremia score and the Charlson comorbidity index (adjusted OR = 0.833, CI; 0.398–1.743). Compared with conventional methods, BCID reduced the time to administration of effective antibiotics in cases of carbapenem-resistant Enterobacterales (CRE) (39 h vs. 93 h, p = 0.012) and vancomycin-resistant enterococci (VRE) (50 h vs. 92 h, p < 0.001) bacteremia. BCID did not affect the clinical outcomes of overall bloodstream infections; however, it contributed to the early administration of effective antibiotics in cases of CRE and VRE bacteremia.

The spread of delta variants (B.1.671.2) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a severe global threat. Multiplex real-time PCR is a common method for confirming SARS-CoV-2 infection, however, additional tests, such as whole genomic sequencing, are required to reveal the presence or type of viral mutation. Moreover, applying whole genomic sequencing to all SARS-CoV-2 positive samples is challenging due to time and cost constraints. Here, we report that the double or low amplification curve observed during RNA-dependent RNA polymerase (RdRp) gene/S gene amplification in the Allplex SARS-CoV-2 Assay is related to delta/alpha variants. We analyzed the RdRp/S gene amplification curve using 94 samples confirmed as SARS-CoV-2 infection by the Allplex SARS-CoV-2 Assay from January to August, 2021. These positive samples identified variant types using the Novaplex SARS-CoV-2 Variants I and IV Assays. Overall, 17 samples showing a double curve and 11 samples showing a low amplification pattern were associated with alpha-/delta-type strains with variants in the P681 region. The double or low curve shown in the RdRp gene amplification curve had 100% sensitivity and 100% specificity for diagnosing delta/alpha variants. During the SARS-CoV-2 virus diagnostic RT-PCR test using the Allplex SARS-CoV-2 Assay, we could consider the presence of delta/alpha variants in the samples with double or low amplification curve of the RdRp/S gene channel. This PCR amplification curve abnormality enables rapid and cost-effective variant type prediction during SARS-CoV-2 diagnostic testing in clinical laboratories.

Fast antimicrobial susceptibility testing (AST) is essential for appropriate antimicrobial therapeutic guidance in patients with bloodstream infections, reducing the time required for optimal treatment. We aimed to evaluate the clinical performance of the VITEK REVEAL (REVEAL), a volatile organic compound-based fast AST system, compared with our already established AST workflow for bloodstream infections. We prospectively collected a total of 107 gram-negative isolates from positive blood cultures and performed rapid species identification using the BIOFIRE BCID2 panel, followed by AST using the REVEAL system. We conducted parallel comparative tests (QMAC-dRAST, VITEK 2, and ETEST for selected antimicrobials) and analyzed the results for categorical agreement (CA), essential agreement (EA), and categorical discrepancies. Moreover, we compared the time to results between the REVEAL vs QMAC-dRAST and VITEK2. Compared with QMAC-dRAST, REVEAL demonstrated 94.1% CA and 98.4% EA across 1,200 pairwise comparisons, with very major discrepancy (VMD) and major discrepancy (MD) rates of 1.4% and 0.7%, respectively. Compared to VITEK2 (872 comparisons), REVEAL yielded 94.5% CA and 97.9% EA, with VMD and MD of 0.5% and 0.6%, respectively. For ceftazidime/avibactam and ceftolozane/tazobactam, REVEAL showed 100% and 98.6% CA, respectively, compared to ETEST. The median final and per-antibiotic time to results for REVEAL were 8.00 h (range: 6.50–8.15 h) and 5.97 h (range: 3.17–8.15 h), respectively. The REVEAL system demonstrated high concordance with existing fast and conventional AST methods and enabled reliable susceptibility testing. These results support the potential integration of the REVEAL system into routine microbiological workflows for time-sensitive clinical decision-making in bloodstream infections. IMPORTANCE: Fast antimicrobial susceptibility testing is critical for initiating appropriate therapy in patients with gram-negative bacteria-induced bloodstream infections. Conventional antimicrobial susceptibility testing methods often require extended turnaround times, thereby delaying optimal treatment. In this study, we prospectively evaluated the VITEK REVEAL system, which detects bacterial growth-associated volatile organic compounds to directly determine antimicrobial susceptibility in positive blood cultures. We assessed the system against our already established identification and antimicrobial susceptibility testing methods, including both fast and conventional platforms currently implemented in routine clinical practice. The volatile organic compounds-based system demonstrated high concordance, shorter time-to-results, and reliable performance for newer antimicrobial agents. By directly comparing its performance with established clinical diagnostic tools, this study provides relevant support for the potential integration of this approach into real-world laboratory workflows, with implications for improved patient management and antimicrobial stewardship.

Boeun Yoo, M.S., Arang Kim, M.S., Hye Sung Moon, M.S., Min-Kyung So, M.D., Ph.D., Tae-Dong Jeong, M.D., Ph.D., Kyoung Eun Lee, M.D., Ph.D., Byung-In Moon, M.D., Ph.D., and Jungwon Huh, M.D., Ph.D.. Ann Lab Med 2024;44:82-91. https://doi.org/10.3343/alm.2024.44.1.82

Min-Kyung So, M.D., Jungwon Huh, M.D., Seunghwan Kim, M.D., and Sholhui Park, M.D.. Ann Lab Med -0001;0:. https://doi.org/10.3343/alm.2023.0460