Central Venous Catheter‐Associated Bloodstream Infections in Hemodialysis Patients: Another Patient Safety Bundle?
Bibliographic record
Abstract
In a previous issue of The Canadian Journal of Infectious Diseases & Medical Microbiology, we reviewed the ′Safer Healthcare Now!′ campaign′s focus on reducing central venous catheter (CVC)‐associated bloodstream infections (BSIs) as a way of improving patient safety (1). This initiative is focused on preventing CVC‐associated BSIs in intensive care units. However, other patient groups are also at risk for CVC‐related BSIs, suggesting that there are other individuals who would benefit from preventive efforts. A 1996 hospital‐wide survey of nosocomial bacteremia in an Israeli university hospital (2) found that 9% of infected patients were on chronic hemodialysis. Surveillance in 73 hospitals in England between 1997 and 2001 found a CVC BSI rate of 21/1000 nephrology patients at risk who were hospitalized in teaching hospitals (3). This rate was similar to that found in special care neonatal units, although not quite one‐half that of patients in a general intensive care unit. In a population‐based survey performed in the Calgary Health Region from 2000 to 2002 (4), hemodialysis (HD) posed the greatest risk (RR 208.7; 95% CI 142.9 to 296.3) for acquiring severe BSI.
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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 | 0.011 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.014 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".