Predictive performance of urinalysis for urine culture results according to causative microorganisms: an integrated analysis with artificial intelligence.

Urinary tract infections (UTIs) are pervasive and prevalent in both community and hospital settings. Recent trends in the changes of the causative microorganisms in these infections could affect the effectiveness of urinalysis (UA). We aimed to evaluate the predictive performance of UA for urinary culture test results according to the causative microorganisms. In addition, UA results were integrated with artificial intelligence (AI) methods to improve the predictive power. A total of 360,376 suspected UTI patients were enrolled from two university hospitals and one commercial laboratory. To ensure broad model applicability, only a limited range of clinical data available from commercial laboratories was used in the analyses. Overall, 53,408 (14.8%) patients were identified as having a positive urine culture. Among the UA tests, the combination of leukocyte esterase and nitrite tests showed the highest area under the curve (AUROC, 0.766; 95% CI, 0.764-0.768) for predicting urine culture positivity but performed poorly for Gram-positive bacteriuria (0.642; 0.637-0.647). The application of an AI model improved the predictive power of the model for urine culture results to an AUROC of 0.872 (0.870-0.875), and the model showed superior performance metrics not only for Gram-negative bacteriuria (0.901; 0.899-0.902) but also for Gram-positive bacteriuria (0.745; 0.740-0.749) and funguria (0.872; 0.865-0.879). As the prevalence of non-Escherichia coli-caused UTIs increases, the performance of UA in predicting UTIs could be compromised. The addition of AI technologies has shown potential for improving the predictive performance of UA for urine culture results.IMPORTANCEUA had good performance in predicting urine culture results caused by Gram-negative bacteria, especially for Escherichia coli and Pseudomonas aeruginosa bacteriuria, but had limitations in predicting urine culture results caused by Gram-positive bacteria, including Streptococcus agalactiae and Enterococcus faecalis. We developed and externally validated an AI model incorporating minimal demographic information of patients (age and sex) and laboratory data for UA, complete blood count, and serum creatinine concentrations. The AI model exhibited improved performance in predicting urine culture results across all the causative microorganisms, including Gram-positive bacteria, Gram-negative bacteria, and fungi.

Emergence and Spread of Cephalosporin-Resistant Neisseria gonorrhoeae with Mosaic penA Alleles, South Korea, 2012-2017.

In South Korea, surveillance of antimicrobial drug resistance in Neisseria gonorrhoeae is extremely limited. We describe the emergence and subsequent national spread of N. gonorrhoeae strains with mosaic penA alleles associated with decreased susceptibility and resistance to extended-spectrum cephalosporins. From 2012 through 2017, the proportion of mosaic penA alleles in gonococcal-positive nucleic acid amplification test (NAAT) specimens across South Korea increased from 1.1% to 23.9%. Gonococcal strains with mosaic penA alleles emerged in the international hubs of Seoul in Gyeonggi Province and Busan in South Gyeongsang Province and subsequently spread across South Korea. Most common was mosaic penA-10.001 (n = 572 isolates; 94.7%), which is associated with cefixime resistance. We also identified mosaic penA-34.001 and penA-60.001, both of which are associated with multidrug-resistant gonococcal strains and spread of cefixime and ceftriaxone resistance. Implementation of molecular resistance prediction from N. gonorrhoeae-positive nucleic acid amplification test specimens is imperative in South Korea and internationally.

Characterization of the novel HLA-DRB1*14:252 allele in a Korean individual by next-generation sequencing.

HLA-DRB1*14:252 differs from HLA-DRB1*14:03:01 by one nucleotide substitution in codon 9 in exon 2.

Comparative Analysis of the Molecular Characteristics of Group B Streptococcus Isolates Collected from Pregnant Korean Women Using Whole-genome Sequencing.

Background: The incidence of early- and late-onset sepsis and meningitis in neonates due to maternal rectovaginal group B Streptococcus (GBS) colonization may differ with serotype distribution and clonal complex (CC). CC17 strains are associated with hypervirulence and poor disease outcomes. GBS serotypes are distinguished based on the polysaccharide capsule, the most important virulence factor. We determined the sequence type distribution of GBS isolates from pregnant women in Korea and validated whole-genome sequencing (WGS)-based prediction of antimicrobial susceptibility and capsular serotypes in GBS isolates. Methods: Seventy-five GBS isolates collected from pregnant Korean women visiting Wonju Severance Christian Hospital, Wonju, Korea between 2017 and 2019 were subjected to WGS using the NovaSeq 6000 system (Illumina, San Diego, CA, USA). Multilocus sequence types, serotypes, antimicrobial resistance genes, and hemolysin operon mutations were determined by WGS, and the latter three were compared with the results of conventional phenotypic methods. Results: The predominant lineage was CC1 (37.3%), followed by CC19 (32.0%), CC12 (17.3%), and CC17 (4.0%). All isolates were cps typeable (100%, (75/75), and 89.3% of cps genotypes (67/75) were concordant with serotypes obtained using latex agglutination. The cps genotypes of the 75 isolates were serotypes III (24.0%), V (22.7%), and VIII (17.3%). All isolates harboring intact ermB and tet were non-susceptible to erythromycin and tetracycline, respectively. Three non-hemolytic strains had 1-bp frameshift insertions in cylE. Conclusions: The low prevalence of CC17 GBS colonization may explain the low frequency of neonatal GBS infections. WGS is a useful tool for simultaneous genotyping and antimicrobial resistance determination.

A Retrospective National Study on Colonization Rate and Antimicrobial Susceptibility of Streptococcus agalactiae in Pregnant Korean Women, 2018-2020.

PURPOSE: The prevalence of Group B Streptococcus (GBS) colonization in pregnant Korean women is increasing; however, nationwide studies are lacking. Therefore, we aimed to analyze regional colonization rates and antimicrobial susceptibility for GBS in pregnant Korean women through a nationwide survey. MATERIALS AND METHODS: From January 2018 to December 2020, data from the Seoul Clinical Laboratories on vaginal swab cultures were retrospectively analyzed to detect maternal GBS carriers. Each swab specimen was inoculated onto a 5% blood agar plate and incubated at 35℃-37℃ in a 5% CO2 incubator for 24 h. GBS isolates were identified using a Microflex MALDI Biotyper. Antimicrobial susceptibility tests were performed using the Vitek 2 automated system. RESULTS: The overall nationwide GBS colonization rate in pregnant Korean women was found to be 10.6% (3578/33721). The maternal GBS colonization rates ranged from 10.5%-10.8% over the 3-year study period. The GBS colonization rates by province, in descending order, were as follows: Jeolla-do, 13.2%; Gangwon-do, 12.0%; Chungcheong-do, 11.8%; Gyeonggi-do, 11.3%; Seoul, 10.2%; and Gyeongsang-do, 9.6%. During the study period, the resistance rates against chloramphenicol, levofloxacin, clindamycin, erythromycin, and tetracycline were 2.6%-2.7%, 18.2%-19.6%, 33.4%-35.7%, 35.6%-36.8%, and 50.5%-53.3%, respectively. CONCLUSION: In pregnant Korean women, GBS colonization rates were in the range of 9.6%-13.2%, with Gyeongsang-do being the lowest and Jeolla-do the highest. The resistance rate against clindamycin was high (33.4%-35.7%). GBS colonization rates during pregnancy should be studied nationwide according to the Centers for Disease Control and Prevention-recommended guidelines with periodic antimicrobial resistance monitoring.

[Evaluation of the OC-SENSOR neo system for testing fecal occult blood].

BACKGROUND: Fecal occult blood tests (FOBTs) have been widely used as a means of colorectal cancer screening. Automated FOBTs using immunologic principles have the advantages such as quantitation, high specificity, and high throughput. We evaluated a newly-introduced automated FOBT analyzer, OC-SENSOR neo (OC neo) (Eiken Chemical Co., Japan). METHODS: The precision, linearity, and carry-over rate of OC neo were assessed with specimens prepared in accordance with the guidelines of CLSI. We performed a parallel test between OC neo and OC-SENSOR I (OC I) (Eiken Chemical Co.) using 300 consecutive stool specimens and 60 OC I-positive specimens. The results were analyzed with SPSS version 13.0 (SPSS Inc., USA). RESULTS: The coefficients of variation (CV) of within-run, between-run, and between-day using OCControl L (Eiken Chemical Co.) of ca. 150 ng/mL were 3.5-7.8%, 4.5-8.8% and 4.9-5.0%, respectively. The linear regression coefficient and carry-over rate with the range of 67.8-939.4 ng/mL were 0.9998 (P<0.001), and 0.1%, respectively. Correlation coefficient between OC neo and OC I was R2=0.954 (P<0.001) for 60 OC I-positive specimens. The positive and negative interpretations of 300 consecutive specimens by OC neo were completely consistent with those of OC I. CONCLUSIONS: Because OC neo showed an excellent performance and a good correlation with OC I, OC neo warrants to be a reliable quantitative FOBT system for high volume laboratories.