Analysis of costs and benefits of transparent, gauze, or no dressing for a tunnelled central venous catheter in Canadian stem cell transplant recipients
Bibliographic record
Abstract
Catheter-related bloodstream infection (CRBSI), an avoidable risk in cancer nursing, contributes to patient morbidity, and increases health care spending. The objectives of the study were to evaluate the impact of three different nursing care strategies for tunnelled central venous catheter (CVC) exit sites on infection outcomes and compare costs of each strategy. The study hypothesis proposed that CRBSI and charges for nursing care differ in adult Canadian blood and marrow cell transplant recipients with a tunnelled CVC that use a transparent dressing, no dressing, or a gauze dressing. A sample of 432 records at a single centre compared CRBSI across dressing groups. A micro-costing approach was used to estimate dressing supply charges for an evaluation of the costs and benefits of each exit care strategy. Results of the study indicated no significant differences in CRBSI, number of organisms, gram stain of organisms, or days until the onset of an infection between the three dressing groups. The gauze dressing was considerably more expensive than both the transparent dressing and the no dressing strategy. In terms of supplies and nursing labour fees, transparent dressings were most economical, closely followed by no dressing. The no-dressing strategy was arguably the best option overall, as removing the dressing presents several other non-monetary and monetary benefits too broad for measurement by this study.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".