Long-term trends in bacterial keratitis in Toronto: a 21-year retrospective review
Bibliographic record
Abstract
OBJECTIVE: To examine the incidence, distribution, emerging trends, and resistance patterns of bacterial keratitis isolates in Toronto over the past 21 years. DESIGN: A retrospective observational study conducted at a tertiary care centre in Toronto. METHODS: A retrospective review was conducted on the microbiology records of suspected bacterial keratitis cases that underwent diagnostic corneal scraping and cultures between January 1, 2000, and December 31, 2021. The distribution of primary isolated pathogens and the results of in vitro susceptibility were assessed. RESULTS: A total of 3 554 corneal scrapings were collected over 21 years. A pathogen was identified in 1 842 samples (51.8%), with bacterial keratitis comprising 84.9% of all isolates. Of these, 75.4% were Gram-positive, and 24.0% were Gram-negative. Coagulase-negative Staphylococcus (CoNS) and Pseudomonas aeruginosa were the most frequently isolated Gram-positive and Gram-negative bacteria, respectively. A decreasing trend in the detection of Staphylococcus aureus (E = -0.004; p = 0.015) and Streptococcus pneumoniae (E = -0.002; p = 0.03) was observed over the 21-year study period. Methicillin/oxacillin-resistant CoNS (MRCoNS) was found in 37.5% of the CoNS isolates. The susceptibility of Gram-positive organisms, including methicillin/oxacillin-resistant species, to vancomycin was highest at 100%. Gram-negative organisms showed 99.5% susceptibility to ciprofloxacin and 99.4% susceptibility to tobramycin. CONCLUSIONS: This study represents the largest and longest case series of bacterial keratitis in Canada. CoNS was the most common pathogen, while Pseudomonas aeruginosa was the leading Gram-negative isolate. The findings support the empirical use of fortified tobramycin and vancomycin for the initial management of severe bacterial keratitis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".