Prospective Surveillance for Primary Bloodstream Infections Occurring in Canadian Hemodialysis Units
Bibliographic record
Abstract
OBJECTIVE: Bloodstream infections are a major cause of morbidity and mortality in patients receiving long-term hemodialysis. We wanted to determine the incidence of hemodialysis-related bloodstream infections in Canadian centers participating in the Canadian Nosocomial Infection Surveillance Program. METHODS: Prospective surveillance for hemodialysis-related bloodstream infections was performed in 11 centers during a 6-month period. Bloodstream infections were defined by published criteria. Hemodialysis denominators included the number of dialysis procedures, the number of patient-days on dialysis, and the frequencies of different types of vascular access. RESULTS: There were 184 bloodstream infections in 133,158 dialysis procedures (1.4 per 1,000) and 316,953 patient-days (0.6 per 1,000). Hemodialysis access through arteriovenous (AV) fistulae was associated with the lowest risk for bloodstream infection (0.2 per 1,000 dialysis procedures). The relative risk for infection was 2.5 with AV graft access, 15.5 with cuffed and tunneled central venous catheter (CVC) access, and 22.5 with uncuffed CVC access (P < .001). There was marked variation among the 11 centers in the means of vascular access used for hemodialysis. Significant variation in infection rates was observed among the centers when controlling for types of access. CONCLUSIONS: There was a hierarchy of risk of hemodialysis-related bloodstream infection according to type of vascular access. There was significant variation in the type of vascular access being used among the Canadian hemodialysis centers, and also variation in access-specific infection rates between centers.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".