Clostridium difficile infection in rural Ontario: a retrospective multisite population-based study.
Bibliographic record
Abstract
INTRODUCTION: We conducted a retrospective, population-based study to assess the prevalence of Clostridium difficile infections and the associated risk factors among inpatients and outpatients in our region. METHODS: We used laboratory data over a 2-year period to identify inpatient and outpatient cases of C. difficile infection. Data were collected from 3 local catchment areas for rural hospital laboratories in Sioux Lookout, Mount Forest and the South Huron Hospital Association in Exeter. We gathered demographic data and infection-specific information, including recent antibiotic use and recent or current hospital admission or nursing home stay. RESULTS: During the study period, 34 cases of C. difficile infection occurred in 29 patients, with an estimated crude annual rate of 24.3/100,000 population. Of the cases, 47.1% were diagnosed in outpatients. Most patients (76.5%) had taken antibiotics within the previous 90 days, and antibiotic use and hospital admission accounted for 47.1% of cases. Clindamycin was more commonly associated with C. difficile infections at the northern site and ciprofloxacin at the southern sites. There were 2 deaths from comorbidities. CONCLUSION: The estimated annual incidence of C. difficile infection in our study is similar to urban-based estimates. Almost half of the cases involved outpatients, indicating a need to recognize this illness as a serious outpatient condition. Antibiotic stewardship is an ongoing consideration, as most patients were exposed to antibiotic use before infection.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".