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Record W4386989377 · doi:10.1093/pch/pxad055.061

61 Antibiotic Resistant Patterns of Bacterial Pathogens Causing Invasive Neonatal Infections in Northern Alberta

2023· article· en· W4386989377 on OpenAlexaboutno aff
Joseph Ting, Adrien Lam, Alena Tse‐Chang, Mao-Cheng Lee

Bibliographic record

VenuePaediatrics & Child Health · 2023
Typearticle
Languageen
FieldMedicine
TopicNeonatal and Maternal Infections
Canadian institutionsnot available
Fundersnot available
KeywordsAntibiotic resistanceAntibioticsAntimicrobialMicrobiologyStaphylococcus aureusMedicineEnterococcus faecalisNeonatal intensive care unitAntibiogramDrug resistanceBacteremiaBlood cultureNeonatal sepsisEnterococcusSepsisIntensive care medicineBiologyInternal medicinePediatricsBacteria

Abstract

fetched live from OpenAlex

Abstract Background Antimicrobial resistance is one of the most serious global health threats facing the world today. The neonatal intensive care unit (NICU) is a clinical environment that houses newborn infants who are highly susceptible to overwhelming infection. Early and decisive treatment with powerful anti-microbials tends to be the preferred clinical choice for treating sick infants empirically. Prolonged exposure to antimicrobials can result in multi-drug resistant organisms (MDROs), which can be associated with mortality due to an increase in virulence, delay in appropriate treatment, and a lack of treatment options. An updated antibiogram is important for determining the optimal empirical antimicrobial choice for sepsis evaluations. There is currently a lack of antimicrobial susceptibility data for bacterial pathogens in the Northern Alberta region. Objectives The objective of this study is to understand the antibiotic resistance patterns among isolates responsible for bacteremia and meningitis in the NICUs in Northern Alberta through the standard antibiograms produced by microbiology laboratories. Design/Methods We conducted a retrospective study to analyze antimicrobial resistance patterns found in NICUs during 2013-2021 in Northern Alberta. Bacteria isolated from blood and cerebrospinal fluid according to commonly used antibiotics in NICUs were collated to create a provincial antibiogram. Results A total of 5562 isolates were included in this antibiogram. The most frequently isolated organisms were Escherichia coli (1521), Staphylococcus aureus (1157), members of coagulase-negative staphylococcus (534), Enterococcus faecalis (326), and Klebsiella pneumoniae (357) in neonatal populations. Among the 1157 S. aureus isolates, 24% were resistant to oxacillin (i.e., “methicillin-resistant S. aureus” or MRSA) and 1% were resistant to vancomycin (i.e., “vancomycin-resistant S. aureus” or VRSA). Of the 326 strains of Enterococcus spp., there were no vancomycin-resistant enterococci (VRE) identified. Among gram-negative isolates, 251 out of the 2690 (9.6%) were producing extended-spectrum beta-lactamase (ESBL), in which 52% and 94% were susceptible to gentamicin and amikacin respectively. Among the non-ESBL-producing isolates, E. coli (1521) and K. pneumoniae (357), 7% of the E. coli strains and 1% of the K. pneumoniae strains were resistant to gentamicin. Conclusion The provincial antibiogram is a useful clinical tool that can best inform clinicians on the appropriate choice of empirical antimicrobial agent based on commonly identified invasive pathogens in neonatal infections within Northern Alberta. Our findings on these resistant patterns can aid next steps for developing an antimicrobial stewardship program.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.014
GPT teacher head0.266
Teacher spread0.252 · 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 designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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