Heteroresistant Vancomycin Intermediate Coagulase Negative Staphylococcus in the NICU: A Systematic Review
Bibliographic record
Abstract
CONTEXT: NICUs in the province of Québec have seen an increase in hVICoNS, detected in the clinical laboratory. OBJECTIVE: To investigate the clinical relevance of hVICoNS on the course of infection, and to determine the prevalence of hVICoNS sepsis in the NICU. METHODS: We searched MEDLINE, EMBASE, and PubMed from 1 January 1980 to 1 July 2016. Both observational and interventional studies were considered eligible if they provided data on hVICoNS in the NICU population. Two investigators independently reviewed studies for data extraction. Data extracted included: number of CoNS cultures, prevalence of hVICoNS, and clonality of strains. RESULTS: Of the 613 studies identified, 19 studies were reviewed, and 5 studies included in the final review. No studies addressed the clinical significance of hVICoNS in the NICU. The prevalence of hVICoNS in the NICU varied greatly, ranging from 2.3% to 100%. LIMITATIONS: Publication bias could not be assessed, and risk of bias in some of the included studies due to small sample size and poor methods reporting. The quality of all included studies was low according to GRADE criteria, and the inclusion criteria restricted to either English or French studies. CONCLUSIONS: Our review suggests that heteroresistance to vancomycin is much more common than previously believed. Our search however did not identify any studies that explicitly assessed any clinical implications of hVICoNS infections, thereby highlighting the need for research to assess the true impact of hVICoNS infection and to determine its significance on patient mortality and morbidity in the NICU.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".