High risk of <i>Clostridium difficile</i> infection among spinal cord injured patients after the use of antibiotics commonly used to treat urinary tract infections
Bibliographic record
Abstract
AIM: To characterize the use of common urinary tract infections (UTI)-relevant antibiotics after an SCI and determine the risk of Clostridium difficile infection (CDI) from these antibiotics. METHODS: We used routinely collected data from Ontario (Canada) to conduct a retrospective, cohort study. We identified people >18 years of age with a traumatic SCI between April 2003 and March 2017. The primary exposure was an outpatient UTI-relevant antibiotic prescription during our observation period, and the primary outcome was evidence of a CDI. An adjusted cox proportional hazards model was used, and antibiotic exposure was modeled as a categorical, time-varying variable based on whether the patient likely had a UTI or not. RESULTS: We identified 2528 people with SCI; 1642 (65%) were exposed at least once to an antibiotic of interest. The most commonly prescribed UTI-relevant antibiotic was fluoroquinolone (34%). Most patients did not have investigations for a UTI before the use of any of the different antibiotic classes. A small number of patients (5%) used chronic (>3 months) UTI-relevant antibiotics. The overall proportion of patients diagnosed with CDI was 7.4% (9.3/10 000 patient-days). The adjusted hazard ratio for CDI within 30 days was 3.5 (95% confidence interval, 1.9-6.7, p < .01) if they were exposed to a UTI-relevant antibiotic likely associated with a UTI, which was similar to the risk from UTI-relevant antibiotics which may not have been for a UTI. CONCLUSIONS: The rate of CDI is high in this population and outpatient antibiotics that are commonly used for UTIs are a significant risk factor for CDI.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".