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Record W2107277189 · doi:10.1093/jac/dkt008

Ability of the VITEK(R) 2 system to detect group B streptococci with reduced penicillin susceptibility (PRGBS)

2013· letter· en· W2107277189 on OpenAlexaboutno aff
Kouji Kimura, Noriyuki Nagano, Yoshiko Nagano, Jun-ichi Wachino, Keigo Shibayama, Y. Arakawa

Bibliographic record

VenueJournal of Antimicrobial Chemotherapy · 2013
Typeletter
Languageen
FieldMedicine
TopicNeonatal and Maternal Infections
Canadian institutionsnot available
FundersTakeda Science Foundation
KeywordsStreptococcus agalactiaePenicillinGroup BStreptococcusMedicineAntibioticsMicrobiologyBreakpointSepsisMeningitisInternal medicineBiologyPediatricsBacteriaGene

Abstract

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Sir, Group B Streptococcus (Streptococcus agalactiae, GBS) is the leading cause of neonatal sepsis and meningitis and an important pathogen among elderly people and those suffering from underlying medical disorders.1,2 The highest GBS mortality and morbidity result from invasive infections in neonates.1,2 Approximately 5% of GBS-infected infants die and survivors often suffer from severe neurological sequelae.2 Intrapartum antibiotic prophylaxis has been recommended by the CDC2 and is prescribed for pregnant women who have GBS isolated from vaginal specimens. Since the introduction of prophylaxis, the rate of GBS infection during the first post-natal week has decreased. Penicillins are the first-line agents in the prophylaxis and treatment of GBS infections because all clinical GBS isolates have been considered to be uniformly susceptible to β-lactams, including penicillins.2,3 However, we identified and characterized several GBS isolates demonstrating reduced penicillin susceptibility (PRGBS) through acquisition of multiple mutations in the penicillin-binding protein 2X (pbp2x) gene,4 and similar isolates were reported in the USA,5 Canada6,7 and Japan.8 After our research was published, EUCAST (http://www.eucast.org/clinical_breakpoints/) defined a clinical penicillin MIC breakpoint for Streptococcus groups A, B, C and G, together with the penicillin MIC resistance breakpoint (>0.25 mg/L). The EUCAST breakpoint is higher than the breakpoint for penicillin susceptibility set by the CLSI (≤0.12 mg/L). Until recently, PRGBS were isolated from respiratory specimens, blood, decubitus ulcers and adult hip-joint fluid,4–8 with no report of PRGBS isolated from neonates or vaginal specimens of pregnant women. The isolation rate of PRGBS from various sources is approximately 2.3% in Japan.8 The MICs of penicillin G for PRGBS (0.25–1 mg/L) are near the breakpoint set by the CLSI (≤0.12 mg/L). Therefore it is unclear whether automated susceptibility testing machines such as VITEK® 2 can detect PRGBS accurately. Because the VITEK® 2 system is widely used in clinical laboratories in Japan, we used this system as an example in order to evaluate the ability of automated susceptibility testing machines to detect PRGBS. The MICs of penicillin G were determined for 28 PRGBS using the agar dilution method as per CLSI recommendations.3Streptococcus pneumoniae ATCC 49619 was used as a quality control for MIC measurements. It was confirmed that these PRGBS harboured the amino acid substitutions in pbp2x genes, as described previously.4,8 We performed the determination of the MICs of penicillin G for 28 PRGBS three times using the VITEK® 2 compact system with AST-P546 cards (bioMérieux Clinical Diagnostics, Marcy l'Étoile, France) in accordance with the manufacturer's instructions. The results of the comparison between the MICs of penicillin G for 28 PRGBS, as determined by agar dilution and the VITEK® 2 system, are shown in Table 1. Although the MICs determined by the agar dilution method were 0.25–1 mg/L [above the breakpoint (≤0.12 mg/L) set by the CLSI], the MICs determined by the VITEK® 2 system were ≤0.12–1 mg/L. The MICs determined by the VITEK® 2 system were ≤0.12 mg/L in 38 instances (38/84, 45.2%; 84 instances = 28 strains × 3 times). The number of strains for which the MICs determined by the VITEK® 2 system were ≤0.12 mg/L at least two of three times was 13 (13/28, 46.4%). Comparison between MICs of penicillin G for 28 PRGBS determined by agar dilution and by VITEK® 2 ND, not determined. Comparison between MICs of penicillin G for 28 PRGBS determined by agar dilution and by VITEK® 2 ND, not determined. In this study, we investigated the ability of the VITEK® 2 system to detect PRGBS. It detected only half of the PRGBS in this study. Automated susceptibility testing machines such as VITEK® 2 are used in clinical settings worldwide, and these results suggest that many PRGBS may be misclassified as ‘susceptible’ to penicillin G. We recently revealed that PRGBS tends to be resistant to fluoroquinolones and macrolides, in addition to having reduced penicillin susceptibility,9 indicating that the classification of susceptibility to penicillin G is very important. The worldwide misclassification of PRGBS as ‘susceptible’ to penicillin G is undesirable and hinders attempts to clarify the clinical significance of reduced susceptibility to penicillin G. The MICs of penicillin G for PRGBS (0.25–1 mg/L) are near the ‘susceptible’ breakpoint (≤0.12 mg/L) set by the CLSI, while the MICs of oxacillin (2–8 mg/L) and ceftizoxime (4–128 mg/L) for PRGBS are higher than those of penicillin-susceptible GBS.4 However, the VITEK® 2 system AST-P546 cards for S. agalactiae do not include MIC determinations of oxacillin or ceftizoxime. We believe that inclusion of these MICs would enable more accurate detection of PRGBS by automated susceptibility testing machines. Moreover, it would be better for these machines to contain systems to alert operators to PRGBS-suspicious isolates when the MICs of penicillin G indicate a range near the susceptibility breakpoint, e.g. at 0.12 mg/L. Previously we reported that disc diffusion methods using oxacillin, ceftizoxime and ceftibuten were useful for detecting PRGBS.10 The disc diffusion method for detecting PRGBS does not require expensive or specialized equipment. Therefore, prior to any improvements in automated susceptibility testing machines, the disc diffusion method for detecting PRGBS will be useful for clinical microbiological laboratories worldwide. This study was supported by grants H21-Shinkou-Ippan-008 and H24-Shinkou-Ippan-010, from the Ministry of Health, Labor and Welfare, Japan, and, in part, by a research grant for medical science from the Takeda Science Foundation (2012). The third grant covered the cost of editing by Editage, as mentioned in the Transparency declarations section. The authors have no conflicts of interest to declare. The manuscript was edited by Editage, a language editing company. We thank Kumiko Kai, Yoshie Taki and Yumiko Yoshimura for technical assistance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.235
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations16
Published2013
Admission routes1
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