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Emerging pathogens <i>Aerococcus urinae</i> and <i>Aerococcus sanguinicola</i> from a Canadian tertiary care hospital

2024· article· en· W6976823981 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsnot available
Fundersnot available
KeywordsAntimicrobialAntibioticsUrinary systemPenicillinCohortUrineCohort studyAntibiotic resistance

Abstract

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<b>Background:</b><i>Aerococcus urinae</i> and <i>Aerococcus sanguinicola</i> are emerging pathogens linked with urinary tract infections. We present a case series of <i>A. urinae</i> and <i>A. sanguinicola</i> isolates characterizing the spectrum of clinical presentation, microbiological characteristics and antimicrobial sensitivities. <b>Methods:</b> Retrospective chart review was performed on patients who grew positive cultures for <i>A. urinae</i> and <i>A. sanguinicola</i> identified on MALDI-TOF in Saskatchewan from January to June 2023. Demographic and clinical variables, antimicrobial susceptibility and prescription were documented. <b>Results:</b> This cohort (n = 115) had a median age 82 years. <i>A. urinae</i> and <i>A. sanguinicola</i> infections spanned from urinary tract infection (n = 96) to urosepsis (n = 6). These infections were predominantly monomicrobial (73.9%) and were susceptible to ceftriaxone, penicillin G and vancomycin. Antimicrobials were seldom prescribed within the urinary tract infection cohort (31.2%). <b>Conclusion:</b> Untreated <i>A. urinae</i> and <i>A. sanguinicola</i> infections can precipitate into urosepsis. The reported antimicrobial susceptibility for these <i>Aerococcus</i> isolates should be utilized to provide appropriate antimicrobial coverage. <i>Aerococcus urinae</i> and <i>Aerococcus sanguinicola</i> are bacteria that can cause urine infections. They are often overlooked and thought to be unable to cause serious blood infections, such as sepsis. We collected data on 87 cases of <i>A. urinae</i> and 28 cases of <i>A. sanguinicola</i> to show that these bacteria can cause urine and blood infections in elderly patients. We also looked at other studies and summarized that patients with serious blood infections from these bacteria often had a previous urine infection from these same bacteria. These bacteria can be resistant to a common antibiotic used to treat urine infections. It is important to test and report if these bacteria are resistant to this common antibiotic and doctors must be aware that they can cause serious blood infections if not treated with the correct antibiotics. The clinical importance of <i>Aerococcus urinae</i> and <i>Aerococcus sanguinicola</i> infections remains underscored in clinical practice. In cases of <i>Aerococcus</i> with polymicrobial growth, clinicians often target their antimicrobial choice against the other organisms. We present a single center case series highlighting the clinical presentation, microbiological findings and antibiotic management in patients with these <i>Aerococcus</i> infections. The patient profile of <i>A. urinae</i> or <i>A. sanguinicola</i> infections at our institution was an elderly patient from long-term care facilities, background medical history notable for hypothyroidism and hypertension and clinical presentation ranging from asymptomatic bacteriuria to sepsis. <i>A. urinae</i> or <i>A. sanguinicola</i> isolates were susceptible to penicillin, ceftriaxone and vancomycin. Our literature review indicated that 20% of <i>A. sanguinicola</i> and 10% of <i>A. urinae</i> isolates show fluoroquinolone resistance. Therefore, microbiology labs must report fluoroquinolone susceptibilities in these isolates. Our literature review also showed that 84% (n = 165 out of 197) of <i>A. urinae</i> or <i>A. sanguinicola</i> systemic infections had an antecedent urinary tract infection within 30 days. Therefore, untreated or recurrent urinary tract infections with <i>A. urinae</i> or <i>A. sanguinicola</i> have the propensity to develop systemic infections.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.806
Threshold uncertainty score0.998

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1270.003

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 head0.016
GPT teacher head0.237
Teacher spread0.220 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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