Prevention of Central Line-Associated Bloodstream Infections Through Educational Interventions in Adult Intensive Care Units: A Systematic Review
Bibliographic record
Abstract
Central line-associated bloodstream infections (CLABSIs) represent a severe systemic threat to patients admitted in ICUs and contribute to increased mortality, prolonged length of stay in ICUs, and increased costs. The majority of CLABSIs are preventable. The current systematic review aimed to investigate the effectiveness of educational methods on CLABSI rates in adult ICUs. A systematic literature search was conducted using the electronic databases of Medline, Cumulative Index to Nursing and Allied Health Literature (CINAHL) Plus, and Cochrane Database of Systematic Reviews for studies published from the beginning of 1995 to March 2020. The terms used for the search were as follows: central venous catheters, infection, central line-associated bloodstream infections, intensive care unit, and education intervention in all possible combinations and using the word 'and' between them. Data were extracted independently and crosschecked by two authors using a standard data collection form. The quality of the studies included in the review was assessed using the Methodological Index for Non-randomized Studies (MINORS). The current systematic review included 27 interventional studies of central line insertion or maintenance or both in adult ICU settings with documentation of the CLABSI incidence expressed per 1,000 catheter days. A large deviation between the length of time and type of educational interventions was found. Statistical significance was found in all studies (except one) in terms of CLABSI reduction despite the large variation of the length or the type of the educational intervention. Continuing education on infection prevention may be necessary to maintain the post-intervention results and improve clinical outcomes.
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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".