Chlorhexidine (di)gluconate locking device for central line infection prevention in intensive care unit patients: A multi-unit, pilot randomized controlled trial
Bibliographic record
Abstract
Purpose: Intensive care unit (ICU) patients are at risk for central line-associated bloodstream infection (CLABSI) with significant attributable mortality and increased hospital length of stay, readmissions, and costs. Chlorhexidine (di)gluconate (CHG) is used as a disinfectant for central line insertion; however, the feasibility and efficacy of using CHG as a locking solution is unknown. Methods: Patients with a central venous access device (CVAD) in situ were randomized to standard care or a CHG lock solution (CHGLS) within 72 hours of ICU admission. The CHG solution was instilled in the lumen of venous catheters not actively infusing. CVAD blood cultures were taken at baseline and every 48 hours. The primary outcome was feasibility including recruitment rate, consent rate, protocol adherence, and staff uptake. Secondary outcomes included CVAD colonization, bacteraemia, and clinical endpoints. Results: Of 3,848 patients screened, 122 were eligible for the study and consent was obtained from 82.0% of the patients or substitute decision makers approached. Fifty participants were allocated to each group. Tracking logs indicated that the CHGLS was used per protocol 408 times. Most nurses felt comfortable using the CHGLS. The proportion of central line colonization was significantly higher in the standard care group with 40 (29%) versus 26 (18.7%) in the CHGLS group (P = .009). Conclusions: Using a device that delivers CHG into CVADs was feasible in the ICU. Findings from this trial will inform a full-scale randomized controlled trial and provide preliminary data on the effectiveness of CHGLS. Trial Registration: ClinicalTrials.gov Identifier NCT03309137, registered on October 13, 2017
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".