PS-222 Staphylococcus Capitis In Neonatal Late-onset Sepsis: Unexpected Worldwide Dissemination Of An Endemic Multi-resistant Clone
Bibliographic record
Abstract
Background Multi-resistant Staphylococcus capitis NRCS-A is involved in late-onset sepsis (LOS) in French NICUs. Aims To investigate the geographical distribution of NRCS-A, and to precise its susceptibility profile. Methods Twelve S. capitis isolates from distant NICUs (Australia, Belgium, France, United Kingdom, n = 3 each) and 2 S. capitis isolates from adult patients were analysed using PFGE, SCCmec typing, dru-typing, a MLST-like analysis, and antimicrobial susceptibility testing. To explore impact of vancomycin selective pressure, after 15 daily subcultures with vancomycin, we determined vancomycin, daptomycin and linezolid minimal inhibitory concentrations (MICs). Results All NICU S. capitis (i) shared >80% similarity of PFGE profile and were similar to NRCS-A profile, (ii) harboured a type V-related SCCmec element, (iii) exhibited the same dru-type, (iv) formed a monophyletic group, (v) harboured a same antimicrobial susceptibility profile including aminoglycosides and methicillin resistance, and vancomycin heteroresistance. These molecular and antimicrobial susceptibility profiles differed from those of adult isolates. An increase of vancomycin and daptomycin (but not linezolid) MICs was observed, significantly faster (p < 0.05) for NRCS-A isolates than other tested strains. Conclusion Our analysis demonstrates an unexpected worldwide distribution of S. capitis NRCS-A, specifically in NICUs. Recently, we collected complementary NICU isolates belonging to NRCS-A from Norway, Denmark, the Netherlands, USA, Brazil, New Zealand and Canada, confirming the worrisome dissemination of NRCS-A. Its multi-resistant profile and its ability to rapidly adapt to vancomycin selective pressure, constitute a selective advantage to NRCS-A in NICUs, and raise the issue of potential therapeutic failure and the need for alternative antimicrobial regimens.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".