Molecular surveillance reveals widespread colonisation by carbapenemase and extended spectrum beta-lactamase producing organisms in neonatal units in Kenya and Nigeria
Bibliographic record
Abstract
Abstract Objectives Neonatal sepsis, a major cause of death amongst infants in sub-Saharan Africa, is often gut derived. Gut colonisation by Enterobacteriaceae producing extended spectrum beta-lactamase (ESBL) or carbapenemase enzymes can lead to antimicrobial-resistant (AMR) or untreatable infections. We sought to explore the rates of colonisation by ESBL or carbapenemase producers in two neonatal units (NNUs) in West and East Africa. Methods Stool and rectal swab samples were taken at multiple timepoints from newborns admitted to the NNUs at the University College Hospital, Ibadan, Nigeria and the Jaramogi Oginga Odinga Teaching and Referral Hospital, Kisumu, western Kenya. Samples were tested for ESBL and carbapenemase genes using a previously validated qPCR assay. Kaplan–Meier survival analysis was used to examine colonisation rates at both sites. Results In total 119 stool and rectal swab samples were taken from 42 infants admitted to the two NNUs. Colonisation with ESBL (37 infants, 89%) was more common than with carbapenemase producers (26, 62.4%; P = 0.093). Median survival time before colonisation with ESBL organisms was 7 days and with carbapenemase producers 16 days (P = 0.035). The majority of ESBL genes detected belonged to the CTX-M-1 (36/38; 95%), and CTX-M-9 (2/36; 5%) groups, and the most prevalent carbapenemase was blaNDM (27/29, 93%). Conclusions Gut colonisation of neonates by AMR organisms was common and occurred rapidly in NNUs in Kenya and Nigeria. Active surveillance of colonisation will improve the understanding of AMR in these settings and guide infection control and antibiotic prescribing practice to improve clinical outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".