Preliminary insights into the occurrence of similar clones of extended‐spectrum beta‐lactamase‐producing bacteria in humans, animals and the environment in Tanzania: A systematic review and meta‐analysis between 2005 and 2016
Bibliographic record
Abstract
Summary The emergence and spread of extended‐spectrum beta‐lactamase producing Enterobacteriaceae (ESBL‐PE) are complex and of the public health concern across the globe. This review aimed at assessing the ESBL‐PE clones circulating in humans, animals and the environment to provide evidence‐based insights for combating ESBL‐PE using One Health approach. Systematic search from Medline/PubMed, Google Scholar and African Journals Online was carried out and retrieved nine eligible articles (of 131) based on phenotypic and genotypic detection of ESBL‐PE between 2005 and 2016 in Tanzania. Analysis was performed using STATA 11.0 software to delineate the prevalence of ESBL‐PE, phenotypic resistance profiles and clones circulating in the three interfaces. The overall prevalence of ESBL‐PE in the three interfaces was 22.6% (95% CI: 21.1–24.2) with the predominance of Escherichia coli (E. coli) strains (51.6%). The majority of ESBL‐PE were resistant to the commonly used antimicrobials such as trimethoprim–sulfamethoxazole and tetracycline/doxycycline, 38%–55% were resistant to ciprofloxacin and all were sensitive to meropenem/imipenem. ESBL‐PE infections were more associated with deaths compared to non‐ESBL‐PE infections. Strikingly, E. coli ST38, ST131 and ST2852 were found to intersect variably across the three interfaces. The predominant allele, blaCTX‐M‐15, was found mostly in the conjugative IncF plasmids connoting transmission potential. The high prevalence of ESBL‐PE and shared clones across the three interfaces, including the global E. coli ST131 clone, indicates wide and inter‐compartmental spread that calls for One Health genomic‐driven studies to track the resistome flow.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.021 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".