Admission screening for extended-spectrum cephalosporin-resistant and carbapenem-resistant Enterobacterales colonization at a referral hospital in Botswana: A one-year period-prevalence survey, 2022–2023
Bibliographic record
Abstract
Extended-spectrum cephalosporin-resistant Enterobacterales (ESCrE) and carbapenem-resistant Enterobacterales (CRE) are significant contributors to infection-related mortality in low- and middle-income countries. Colonization with ESCrE and/or CRE can precede infection and serve as a reservoir for transmission within healthcare facilities and the community.We conducted a 12-month period-prevalence study, screening patients for ESCrE and CRE upon admission to a referral tertiary hospital Emergency Department in Botswana. Rectal swabs were collected within 24 hours of hospital arrival. Colonization was identified using selective culture media and confirmed using automated susceptibility testing. Associations between ESCrE/CRE colonization, and clinical and demographic variables were analysed using univariate and multivariable logistic regression. Among 802 patients, 24.1% (n = 193) were colonized with ESCrE, and 1.5% (n = 12) with CRE. ESCrE colonization was associated with recent hospitalization (within the last six months) (aOR 1.76, 95% CI 1.11-2.79), borehole water use (aOR 3.95, 95% CI 1.12-13.87), indwelling medical devices (aOR 2.19, 95% CI 1.08-4.48), and age < 1 year (aOR 2.09, 95% CI 1.32-3.30). CRE colonization was associated with antiretroviral drug use (cOR 6.60, 95% CI 1.72-25.36). Infants (<1 year) had over three times the odds of ESCr/CR-Klebsiella spp. colonization compared to adults (cOR 3.60, 95% CI 1.82-7.13). Infant age, recent healthcare exposure, indwelling medical devices, and borehole water use were key risk factors for ESCrE colonization, highlighting the need for targeted infection prevention strategies in Botswana. The identified potential association between CRE colonization and antiretroviral drug use warrants further investigation to elucidate any possible links and drivers between HIV care and antimicrobial resistance.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".