Impact of practice changes on catheter-related exit-site and bloodstream infection rates in a Canadian hemodialysis center: A retrospective study
Bibliographic record
Abstract
Background: Hemodialysis vascular access predisposes patients to exit-site infections (ESIs) and bloodstream infections (BSIs), resulting in significant morbidity and mortality. The objective was to characterize hemodialysis catheter-related (CR) ESIs and BSIs while considering potential factors associated with infection. Methods: The study period was selected to coincide with new CR-infection prevention measures at the midpoint. These included masking during exit-site care, using chlorhexidine-alcohol versus povidone-iodine antiseptic, administering cefazolin prophylaxis with central venous catheter (CVC) insertions, and reducing temporary CVC use for chronic hemodialysis starts. Data were collected retrospectively, including patient characteristics, hemodialysis history, CVC details, and CR-infections. Quarterly infection rates were calculated per 1000 CVC days, and potential factors associated with infection were investigated. Modeling was used to characterize infection rates and covariates over time. Results: Over 39 months, data for 267 patients, 499 CVCs, and 114,825 CVC days were captured. During the study period, there were 113 ESIs and 64 BSIs, with >80% of infections caused by gram-positive bacteria. ESI and BSI rates were 0.98 and 0.56 per 1000 CVC days, respectively. There were significant reductions in infection rates over time. The ESI rate dropped when new CR-infection prevention measures were introduced ( p < 0.01), from a mean of 1.28 to 0.73 per 1000 CVC days ( p = 0.003). The rate of BSI trended downward to a low of 0.10 per 1000 CVC days in the last quarter of the study. The BSI rates associated with temporary and permanent CVCs were 1.25 and 0.53 per 1000 CVC days, respectively ( p = 0.1). There was a strong correlation between the declining BSI rates and declining temporary CVC use over time (rho = 0.73, p = 0.005). Conclusions: CR-ESI rates dropped significantly when new hemodialysis CR-infection prevention measures were introduced. CR-BSI rates declined over the study period, as did the use of temporary CVCs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".