MétaCan
Menu
Back to cohort
Record W4411878348 · doi:10.1186/s13756-025-01595-6

Interpreting whole-genome sequencing data during neonatal Klebsiella oxytoca complex outbreak management

2025· article· en· W4411878348 on OpenAlexaff
Chiara Minotti, Elena Robinson, Pascal Schläepfer, Christian Pohl, Daniel Goldenberger, Sven Schulzke, Peter M. Keller, Julia Bielicki

Bibliographic record

VenueAntimicrobial Resistance and Infection Control · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsInstitute of Infection and Immunity
FundersUniversität Basel
KeywordsOutbreakKlebsiella oxytocaMedicineWhole genome sequencingVirulenceNeonatal intensive care unitKlebsiella pneumoniaeBiologyMicrobiologyGenomePediatricsVirologyGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: K. oxytoca generally has a benign susceptibility profile and low virulence but can cause invasive infections in vulnerable populations, like preterm infants. We aim to describe how whole-genome sequencing (WGS) was used to inform management of a prolonged K. oxytoca outbreak on a neonatal intensive care unit (NICU) and implications for outbreak response involving similar organisms. METHODS: We retrospectively reviewed outbreak-associated clinical and environmental isolates from a Swiss NICU. WGS was used to track evolution of resistance and highlighted multiple concurrent outbreaks. WGS was performed using a MiSeq or NextSeq 500 Illumina sequencer. The resulting genome sequences were analysed using Ridom SeqSphere. The current report conforms to ORION reporting guidelines. RESULTS: Of 152 Klebsiella spp. patient-derived isolates, 83 were genotyped using WGS, along with six environmental isolates. This confirmed two outbreak waves (November 2021-February 2022, ST18 wildtype; July 2022-June 2023, main cluster ST18 KI β-lactamase hyperproducer), with multiple genotypically connected clusters during the second wave. Confirmed sepsis (K. oxytoca ST18 wildtype) occurred in four preterm or low birthweight infants. Twins presented a genotypically identical ST with a different susceptibility phenotype (ST18 wildtype vs. K1 OXY-hyperproducer). WGS combined with epidemiological investigation and environmental sampling identified an environmental source. There was a second outbreak wave after source removal, presumably due to the prolonged presence of colonised infants with typically long NICU stays and insufficient standard infection prevention and control measures to prevent transmission. CONCLUSION: WGS use in NICU outbreaks involving low-virulence bacteria can support identification and removal of potentiating environmental sources. These measures, however, will often be insufficient to contain the outbreak, and ongoing WGS surveillance of ubiquitous species may uncover multiple concurrent outbreaks, presumably driven by continuing transfer-transmission between different sources and infants in the NICU. Maximising standard infection prevention and control (IPC) measures is appropriate in this context.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.907
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.251
Teacher spread0.241 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAntimicrobial Resistance and Infection ControlSame topicAntibiotic Resistance in BacteriaFrench-language works237,207