Healthcare-Associated Bloodstream Infections Secondary to a Urinary Focus The Québec Provincial Surveillance Results
Bibliographic record
Abstract
OBJECTIVE: Urinary tract infections (UTIs) are an important source of secondary healthcare-associated bloodstream infections (BSIs), where a potential for prevention exists. This study describes the epidemiology of BSIs secondary to a urinary source (U-BSIs) in the province of Québec and predictors of mortality. DESIGN: Dynamic cohort of 9,377,830 patient-days followed through a provincial voluntary surveillance program targeting all episodes of healthcare-associated BSIs occurring in acute care hospitals. SETTING: Sixty-one hospitals in Québec, followed between April 1, 2007, and March 31, 2010. PARTICIPANTS: Patients admitted to participating hospitals for 48 hours or longer. METHODS: Descriptive statistics were used to summarize characteristics of U-BSIs and microorganisms involved. Wilcoxon and χ(2) tests were used to compare U-BSI episodes with other BSIs. Negative binomial regression was used to identify hospital characteristics associated with higher rates. We explored determinants of mortality using logistic regression. RESULTS: Of the 7,217 reported BSIs, 1,510 were U-BSIs (21%), with an annual rate of 1.4 U-BSIs per 10,000 patient-days. A urinary device was used in 71% of U-BSI episodes. Identified institutional risk factors were average length of stay, teaching status, and hospital size. Increasing hospital size was influential only in nonteaching hospitals. Age, nonhematogenous neoplasia, Staphylococcus aureus, and Foley catheters were associated with mortality at 30 days. CONCLUSION: U-BSI characteristics suggest that urinary catheters may remain in patients for ease of care or because practitioners forget to remove them. Ongoing surveillance will enable hospitals to monitor trends in U-BSIs and impacts of process surveillance that will be implemented shortly.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".