Bibliographic record
Abstract
Purpose: Contamination of catheter hub connectors is known to cause catheter‐related blood stream infections in patients undergoing hemodialysis via central venous catheters (CVC). The effectiveness of cleansing the hub with an antimicrobial agent was assessed by culturing the surface of the hub following sanitation. Methods: The CVC hub connectors of 24 patients were sanitized using the standard hospital protocol of aseptically swabbing the connectors with a solution of bleach or Betadine, and then bathing the hub in sterile gauze soaked with the antimicrobial solution for 5 minutes. The exterior surface of the hub was then cultured for a broad spectrum of microorganisms. Patients were monitored for exit site infection, tunnel infection, and septicemia. In the laboratory, sterile hubs were inoculated with E. coli, staph. aureus neg., and yeast. Hubs were then immersed in Betadine for 5, 10, or 30 min. and cultures were taken. Results: Positive cultures were obtained from the hubs of 17 of the 24 patients. Seven (7) of the patients with positive results developed bacteremia from the cultured organism within 7 weeks. Positive cultures were obtained from 50% of inoculated lab samples after 5 min, 10% after 15 min, and 0% after 30 min. of immersion sanitation. Conclusions: The techniques for cleansing CVC hubs should be revisited.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".