The use of laboratory-identified event surveillance to classify adverse outcomes due to<i>Clostridioides difficile</i>infection in Canadian long-term care facilities
Bibliographic record
Abstract
OBJECTIVE: Adverse outcomes following Clostridioides difficile infection (CDI) are not often reported for long-term care facility (LTCF) residents. We focused on the adverse outcomes due to CDI identified in Alberta LTCFs. METHODS: All positive Clostridioides difficile stool specimens identified by laboratory-identified (LabID) event surveillance in Alberta from 2011 to 2018, along with Alberta Continuing Care Information System, were used to define CDI in Alberta LTCFs. CDI cases were classified as long-term care onset, hospital onset, and community onset. Laboratory records were linked to provincial databases to analyze acute-care admissions and mortality within 30-day post CDI. Age, sex, case classification, episode, and operator type, were investigated using logistic regression. RESULTS: Overall, 902 CDI cases were identified in 762 LTCF residents. Of all CDI events, 860 (95.3%) were long-term care onset, 38 (4.2%) were hospital onset, and 4 (0.4%) were community onset. The CDI rate was 2.0 of 100,000 resident days. In total, 157 residents (20.6%) had 30-day all-cause mortality, 126 CDI cases (14.0%) had 30-day all-cause acute-care admissions. The 30-day all-cause mortality rate was significantly higher in residents aged >80 versus ≤80 years (24.9 vs 12.3 per 100 residents; P < .05). Residents aged >80 years, with hospital-onset CDI, and those staying in private or voluntary LTCFs were more likely to have 30-day all-cause acute-care admissions. CONCLUSIONS: The prevalence of CDI adverse outcomes is in LTCFs was found to be high using LabID event surveillance. Annual review of CDI adverse outcomes using LabID event can minimize the burden of surveillance and standardize the process across all Alberta LTCFs.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".