Evaluation of VITEK 2 system and VITEK MS system for the identification of Haemophilus species: a diagnostic accuracy study

Background: Haemophilus is an important pathogen in community-acquired pneumonia and invasive diseases, such as sepsis and meningitis. We aimed to evaluate the VITEK 2 system and VITEK MS system for the identification of Haemophilus strains isolated from clinical specimens in Korea during 2023. Methods: In total, 118 Haemophilus strains isolated from respiratory specimens (n = 107) and blood samples (n = 11) from 10 sentinel hospitals in Kor-GLASS were included in this study. All Haemophilus strains were evaluated using the VITEK 2 and VITEK MS systems. Real-time PCR and 16S rRNA sequencing were used to identify specific species. Results: Among the 118 Haemophilus isolates, 115 were identified as H. influenzae by realtime PCR using hpd gene, and the remaining three strains were identified as H. parainfluenzae by 16S rRNA sequencing. Eighty-eight of the 115 (76.5%) and two of three (66.7%) isolates were correctly identified as H. influenzae and H. parainfluenzae, respectively, using the VITEK 2 system. The VITEK 2 system showed low discrimination (n = 22), misidentification (n = 4), and unidentified organisms (n = 2) in the 28 Haemophilus strains. The VITEK MS system achieved 100% sensitivity and specificity in identifying all 115 H. influenzae and three H. parainfluenzae isolates. Conclusion: The VITEK MS system showed excellent performance in the identification of H. influenzae and H. parainfluenzae, whereas the VITEK 2 system showed relatively low concordance.

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Publication Details

Journal
Annals of Clinical Microbiology
Published
2025-09-02
DOI
https://doi.org/10.5145/acm.2025.28.3.2
Primary Topic
Microbial infections and disease research
Type
article
Field-Weighted Citation Impact
0.00

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article

Evaluation of VITEK 2 system and VITEK MS system for the identification of Haemophilus species: a diagnostic accuracy study

Eunkyoung You, Young Ree Kim, Young Uh, Jong Hee Shin et al.
Annals of Clinical Microbiology
Microbial infections and disease research
article

Evaluation of VITEK 2 system and VITEK MS system for the identification of Haemophilus species: a diagnostic accuracy study

Eunkyoung You, Young Ree Kim, Young Uh, Jong Hee Shin, Ji‐Hyun Cho, Jeong Hwan Shin, Kyeong Seob Shin, Seok Hoon Jeong, Nam Hee Ryoo, Young Ah Kim, Ja Young Lee, Eun-Young Kim, Soo Hyun Kim, Hyun Soo Kim, Si Hyun Kim, Dokyun Kim, Y. Choi, Hyun Jin Choi
article en

Abstract

Background: Haemophilus is an important pathogen in community-acquired pneumonia and invasive diseases, such as sepsis and meningitis. We aimed to evaluate the VITEK 2 system and VITEK MS system for the identification of Haemophilus strains isolated from clinical specimens in Korea during 2023. Methods: In total, 118 Haemophilus strains isolated from respiratory specimens (n = 107) and blood samples (n = 11) from 10 sentinel hospitals in Kor-GLASS were included in this study. All Haemophilus strains were evaluated using the VITEK 2 and VITEK MS systems. Real-time PCR and 16S rRNA sequencing were used to identify specific species. Results: Among the 118 Haemophilus isolates, 115 were identified as H. influenzae by realtime PCR using hpd gene, and the remaining three strains were identified as H. parainfluenzae by 16S rRNA sequencing. Eighty-eight of the 115 (76.5%) and two of three (66.7%) isolates were correctly identified as H. influenzae and H. parainfluenzae, respectively, using the VITEK 2 system. The VITEK 2 system showed low discrimination (n = 22), misidentification (n = 4), and unidentified organisms (n = 2) in the 28 Haemophilus strains. The VITEK MS system achieved 100% sensitivity and specificity in identifying all 115 H. influenzae and three H. parainfluenzae isolates. Conclusion: The VITEK MS system showed excellent performance in the identification of H. influenzae and H. parainfluenzae, whereas the VITEK 2 system showed relatively low concordance.

Annals of Clinical MicrobiologyVol. 28(3)
Korea Disease Control and Prevention Agency, Korea Health Industry Development Institute
Openalex Percentile: Top 79%
Microbial infections and disease research
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