P-275. Risk Factors for Community Colonization with Extended-Spectrum Cephalosporin-Resistant <i>Enterobacterales</i> (ESCrE) among People with HIV in Botswana
Bibliographic record
Abstract
Abstract Background Extended-spectrum cephalosporin-resistant Enterobacterales (ESCrE) are a major global threat, and there is a significant gap in research on the burden and associated risk factors for ESCrE in low-and middle income countries(LMICs). This is particularly true for people with HIV (PWH), who make up a significant proportion of the population in sub-Saharan Africa. In Botswana, 20% of individuals aged 15-49 are PWH. The risk factors associated with ESCrE colonization, typically a precursor to infection, are important to understand as such infections can result in increased healthcare costs as well as high morbidity and mortality. Methods Within a larger regional surveillance study, 546 adults with HIV were recruited from clinics and communities in 3 districts and underwent interviews and rectal sampling. ESCrE was defined as Enterobacterales demonstrating non-susceptibility to ceftriaxone or ceftazidime. Results 27% of participants screened positive for ESCrE colonization. The mean CD4 count was 635 cells/mm3 (SD± 267). Table 1 describes the demographics of the participants with and without ESCrE colonization. Escherichia coli was the most commonly isolated ESCrE (146/174; 84%). Bivariate and multivariate analysis was used to determine risk factors associated with ESCrE colonization (Table 2). Recent hospitalization and certain geographic locations were independent risk factors for ESCrE colonization. Recent antibiotic use had an elevated OR for ESCrE colonization that did not achieve statistical significance in adjusted analysis. Conclusion These results add to the limited data on risk factors associated with ESCrE colonization in PWH. Hospitalization is an independent risk factor for colonization despite controlling for antibiotic use, which suggests the need for further investigation into hospital-specific factors that contribute to ESCrE colonization. Further research is needed to understand the geographic differences in ESCrE colonization in this setting. As LMICs with high HIV burdens build capacity for antimicrobial stewardship and infection prevention infrastructure in healthcare, research on unique potential mechanisms that result in multi-drug resistant colonization in PWH may impact strategies and priorities to combat antimicrobial resistance. Disclosures Robert Gross, MD, MSCE, Pfizer Inc: DSMB member for drug unrelated to study
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".