Multidrug resistance among Escherichia coli and Klebsiella pneumoniae carried in the gut of out-patients from pastoralist communities of Kasese district, Uganda
Bibliographic record
Abstract
BACKGROUND: Antimicrobial resistance is a worldwide public health emergency that requires urgent attention. Most of the effort to prevent this coming catastrophe is occurring in high income countries and we do not know the extent of the problem in low and middle-income countries, largely because of low laboratory capacity coupled with lack of effective surveillance systems. We aimed at establishing the magnitude of antimicrobial resistance among Escherichia coli and Klebsiella pneumoniae carried in the gut of out-patients from pastoralist communities of rural Western Uganda. METHODS: A cross-sectional study was carried out among pastoralists living in and around the Queen Elizabeth Protected Area (QEPA). Stool samples were collected from individuals from pastoralist communities who presented to the health facilities with fever and/or diarrhea without malaria and delivered to the microbiology laboratory of College of Health Sciences-Makerere University for processing, culture and drug susceptibility testing. RESULTS: A total of 300 participants fulfilling the inclusion criteria were recruited into the study. Three hundred stool samples were collected, with 209 yielding organisms of interest. Out of 209 stool samples that were positive, 181 (89%) grew E. coli, 23 (11%) grew K. pneumoniae and five grew Shigella. Generally, high antibiotic resistance patterns were detected among E. coli and K. pneumoniae isolated. High resistance against cotrimoxazole 74%, ampicillin 67%, amoxicillin/clavulanate 37%, and ciprofloxacin 31% was observed among the E. coli. In K. pneumoniae, cotrimoxazole 68% and amoxicillin/clavulanate 46%, were the most resisted antimicrobials. Additionally, 57% and 82% of the E. coli and K. pneumoniae respectively were resistant to at least three classes of the antimicrobials tested. Resistance to carbapenems was not detected among K. pneumoniae and only 0.6% of the E. coli were resistant to carbapenems. Isolates producing ESBLs comprised 12% and 23% of E. coli and K. pneumoniae respectively. CONCLUSION: We demonstrated high antimicrobial resistance, including multidrug resistance, among E. coli and K. pneumoniae isolates from pastoralist out-patients. We recommend a One Health approach to establish the sources and drivers of this problem to inform public health.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".