Antibiotic susceptibility of urine culture specimens in Ontario: a population-based cohort study
Bibliographic record
Abstract
<h3>Background:</h3> Surveillance of antimicrobial resistance is essential to mitigate its impact on population health and inform local empiric treatment practices. Our aims were to evaluate urine culture specimen susceptibility from a range of diverse settings and describe antibiotic susceptibility across all organisms and compare susceptibilities to that of <i>Escherichia coli</i> alone. <h3>Methods:</h3> In this descriptive cohort study, we measured the prevalence of organisms in urine culture specimens using linked province-wide administrative databases. Using positive urine cultures collected in Ontario between Jan. 1, 2016, and Dec. 31, 2017, we measured susceptibility to 6 classes of antibiotics using a weighted antibiogram for all organisms compared with <i>E. coli</i> alone. <h3>Results:</h3> We included 689 497 cultures derived from 569 399 patients and 879 778 test orders for specimens. For all organisms, the rates of susceptibility in the outpatient, inpatient and long-term care settings were 49.3%, 42.8% and 39.2%, respectively, for ampicillin; 83.1%, 72.7% and 69.7%, respectively, for nitrofurantoin; 80.3%, 64.8% and 73.1%, respectively, for trimethoprim–sulfamethoxazole; 87.2%, 74.1% and 66.2%, respectively, for ciprofloxacin; 90.6%, 73.6% and 85.1%, respectively, for aminoglycosides; and 82.6%, 57.5% and 73.5%, respectively, for cefazolin. We found resistance to 3 or more antibiotic classes in 20.6% of episodes for all organisms compared with 14.0% for <i>E. coli</i> alone. The average absolute difference in antibiotic susceptibility between all organisms and <i>E. coli</i> across all drugs was lowest in the outpatient setting (6.2%) and highest in the inpatient setting (14.6%). <h3>Interpretation:</h3> In this study, urinary organism prevalence and antimicrobial susceptibility varied across health care settings and patient populations, with implications for both antimicrobial resistance surveillance and clinical decision-making. Weighted antibiograms may be most useful for guiding empiric treatment of urinary infections in inpatient settings where the diversity of infectious organisms is higher than in the community.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".