Use of a <scp>gentamicin‐citrate</scp> lock leads to lower <scp>catheter‐related</scp> bloodstream infection rates and reduced cost of care in hemodialysis patients
Bibliographic record
Abstract
INTRODUCTION: Central venous catheters (CVC) are a major contributor to infections in hemodialysis (HD) patients, leading to high morbidity and mortality. Gentamicin-citrate (GC) lock is used as standard of care at centers belonging to a mid-size dialysis organization. Four outpatient HD centers acquired by the organization continued to use heparin for catheter locks for a period of time before converting to the provider's standard of using GC lock. METHODS: In this retrospective observational study, we included patients receiving HD by CVC at these four centers. We report rates of CVC-related bloodstream infections (CVC-BSI) during the heparin lock and the GC lock periods; crude rate ratios and adjusted rate ratios using Cox survival analyses adjusting for potential confounders; microbiology patterns; safety signals (gentamicin resistance, hospitalizations and deaths); and financial impact on payer. FINDINGS: A total of 220 and 281 patients used tunneled CVCs, accounting for 25,245 and 44,550 catheter days in the heparin and the GC lock periods, respectively. CVC-BSI event rates were 66% lower in the GC lock period (CVC-BSI event rate: 0.20 per 1000 catheter-days) than the heparin lock period (rate: 0.59 per 1000 catheter days); rate ratio 0.34 (95% confidence interval (CI) 0.15-0.78, P = 0.01). In the fully adjusted multivariable Cox model, use of GC lock was associated with 70% reduction in CVC-BSI events (HR 0.30, 95% CI 0.12-0.72, P = 0.01). No increased risk of gentamicin resistance, hospitalizations, or death associated with use of GC lock were observed. Use of GC lock was associated with an estimated saving of $1533 (95% CI: $259-$4882) per patient per year. DISCUSSION: Use of GC lock led to significant reductions in CVC-BSIs with no signal for harm, and is associated with significant cost savings in dialysis care.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".