Emerging pathogens <i>Aerococcus urinae</i> and <i>Aerococcus sanguinicola</i> from a Canadian tertiary care hospital
Bibliographic record
Abstract
Background:Aerococcus urinae and Aerococcus sanguinicola are emerging pathogens linked with urinary tract infections. We present a case series of A. urinae and A. sanguinicola isolates characterizing the spectrum of clinical presentation, microbiological characteristics and antimicrobial sensitivities. Methods: Retrospective chart review was performed on patients who grew positive cultures for A. urinae and A. sanguinicola identified on MALDI-TOF in Saskatchewan from January to June 2023. Demographic and clinical variables, antimicrobial susceptibility and prescription were documented. Results: This cohort (n = 115) had a median age 82 years. A. urinae and A. sanguinicola 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%). Conclusion: Untreated A. urinae and A. sanguinicola infections can precipitate into urosepsis. The reported antimicrobial susceptibility for these Aerococcus isolates should be utilized to provide appropriate antimicrobial coverage. Aerococcus urinae and Aerococcus sanguinicola 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 A. urinae and 28 cases of A. sanguinicola 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 Aerococcus urinae and Aerococcus sanguinicola infections remains underscored in clinical practice. In cases of Aerococcus 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 Aerococcus infections. The patient profile of A. urinae or A. sanguinicola 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. A. urinae or A. sanguinicola isolates were susceptible to penicillin, ceftriaxone and vancomycin. Our literature review indicated that 20% of A. sanguinicola and 10% of A. urinae 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 A. urinae or A. sanguinicola systemic infections had an antecedent urinary tract infection within 30 days. Therefore, untreated or recurrent urinary tract infections with A. urinae or A. sanguinicola have the propensity to develop systemic infections.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".