Characterizing the bioburden of ESBL-producing organisms in a neonatal unit using chromogenic culture media: a feasible and efficient environmental sampling method
Bibliographic record
Abstract
INTRODUCTION: Infections due to extended spectrum beta-lactamase producing organisms (ESBL) have emerged as the leading cause of sepsis among hospitalized neonates in Botswana and much of sub-Saharan Africa and south Asia. Yet, ESBL reservoirs and transmission dynamics within the neonatal intensive care unit (NICU) environment are not well-understood. This study aimed to assess the efficiency and feasibility of a chromogenic-culture-media-based environmental sampling approach to characterize the ESBL bioburden within a NICU. METHODS: A series of four point-prevalence surveys were conducted at a 36-bed NICU at a public tertiary referral hospital in Botswana from January-June 2021. Samples were collected on 4 occasions under semi-sterile technique using 1) flocked swabs & templates (flat surfaces); 2) sterile syringe & tubing (water aspiration); and 3) structured swabbing techniques (hands & equipment). Swabs were transported in physiological saline-containing tubes, vortexed, and 10 µL was inoculated onto chromogenic-agar that was selective and differential for ESBL (CHROMagar™ ESBL, Paris, France), and streaking plates to isolate individual colonies. Bacterial colonies were quantified and phenotypically characterized using biochemical identification tests. RESULTS: In total, 567 samples were collected, 248 (44%) of which grew ESBL. Dense and consistent ESBL contamination was detected in and around sinks and certain high-touch surfaces, while transient contamination was demonstrated on medical equipment, caregivers/healthcare worker hands, insects, and feeding stations (including formula powder). Results were available within 24-72 h of collection. To collect, plate, and analyse 50 samples, we estimated a total expenditure of $269.40 USD for materials and 13.5 cumulative work hours among all personnel. CONCLUSIONS: Using basic environmental sampling and laboratory techniques aided by chromogenic culture media, we identified ESBL reservoirs (sinks) and plausible transmission vehicles (medical equipment, infant formula, hands of caregivers/healthcare workers, & insects) in this NICU environment. This strategy was a simple and cost-efficient method to assess ESBL bioburden and may be feasible for use in other settings to support ongoing infection control assessments and outbreak investigations.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".