Controlling exit site infections: Does it decrease the incidence of catheter‐related bacteremia in children on chronic hemodialysis?
Bibliographic record
Abstract
The aim of this retrospective study was to investigate whether the application of a chlorhexidine-impregnated dressing (Biopatch) at the exit site of tunneled-cuffed hemodialysis catheters has any effect on the incidence and etiology of catheter-related bacteremia (CRB). This study was carried out over a 5-year period in a single center, where, in the first 2(1/2) years, the exit sites were cleansed with betadine at every hemodialysis session and then covered with a transparent dressing (pre-Biopatch Era). During the next 2(1/2) years, Biopatch was applied to the exit site once a week after cleansing with betadine, and then covered with a transparent dressing (Biopatch Era). The application of Biopatch significantly decreased the incidence of exit site infections (ESI) (P<0.05). However, there was no difference in the incidence of CRBs or their microbiological distribution. The improved ESI rate had no effect on the overall catheter survival time. The antimicrobial sensitivities of the Gram-positive microorganisms were statistically different for the 2 different types of infections (P<0.05). In conclusion, even though Biopatch is effective in decreasing the incidence of ESI, it has no effect on the incidence of CRB, the etiology of CRB, or the overall catheter survival time. The distinct difference between the antimicrobial sensitivities of the ESI and CRB suggests that they are not a spectrum of the same pathogenesis. These preliminary data support the intraluminal pathogenesis of CRB, rather than the exit site as a possible entry point for the extraluminal route.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".