Antimicrobial Resistance and Antimicrobial Use Associated with Laboratory‐Confirmed Cases of <i>Campylobacter</i> Infection in Two Health Units in Ontario
Bibliographic record
Abstract
AIM: A population-based study was conducted over a two-year period in the Perth District (PD) and Wellington-Dufferin-Guelph (WDG) health units in Ontario to document antimicrobial resistance and antimicrobial use associated with clinical cases of laboratory-confirmed campylobacteriosis. METHODS: Etest (bioMérieux SA, France) was used to determine the minimum inhibitory concentration of amoxicillin/clavulanic acid, ampicillin, chloramphenicol, ciprofloxacin (CIP), clindamycin, erythromycin (ERY), gentamicin, nalidixic acid and tetracycline. Data regarding antimicrobial use were collected from 250 cases. RESULTS: Of the 250 cases, 165 (65.7%) reported staying home or being hospitalized due to campylobacteriosis. Fifty-four per cent of cases (135 of 249) reported taking antimicrobials to treat campylobacteriosis. In 115 cases (51.1%), fecal culture results were not used for treatment decisions because they were not available before the initiation of antimicrobial treatment and/or they were not available before the cessation of symptoms. Of the 250 cases, 124 (49.6%) had available Campylobacter isolates, of which 66 (53.2%) were resistant to at least one of the antimicrobials tested. No resistance to ampicillin, chloramphenicol or gentamicin was found in these isolates. Six isolates (4.8%) were resistant to CIP. Two isolates (1.6%) were resistant to ERY; however, no isolates were resistant to both CIP and ERY. CONCLUSION: Prudent use practices should be promoted among physicians to reduce the use of antimicrobials for the treatment of gastroenteritis in general and campylobacteriosis in particular, as well as to minimize the future development of resistance to these antimicrobials in Campylobacter species.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".