Nurses' knowledge on routine care and maintenance of adult vascular access devices: A scoping review
Bibliographic record
Abstract
BACKGROUND: Vascular access devices (VAD), centrally (CVAD) or peripherally (PIV) located, are common in the nursing profession. A high proportion of admitted patients require a VAD to enable administration of intravenous treatments or diagnostic modalities. As the primary caregivers for these patients, nurses are responsible for ongoing care and maintenance of these devices. OBJECTIVE: This scoping review examines the current state of practicing nurses knowledge around routine care and maintenance of adult VADs. METHODS: In the fall of 2018, the following databases were searched: Medline-Ovid 1946 to current, Embase-Ovid 1947 to current, Ebsco CINAHL Plus with full text and ProQuest Nursing & Allied Health database, and articles were selected according to the PRISMA-ScR checklist. INCLUSION CRITERIA: original research published in peer-reviewed journals; in English or French; and focused on practising nurses' knowledge about the routine care and maintenance of adult VADs. RESULTS: Of the 4,099 abstracts identified, 36 full-text articles were included. Study characteristics are reportedin addition to themes found in the literature: the relationship between demographic data and CVAD/PIV knowledge, the state of nurses' CVAD/PIV knowledge and nurses' CVAD/PIV knowledge scores. Overall, significant gaps in nurses' knowledge on the care and maintenance of VADs are noted. CONCLUSION: The variability in nurses' knowledge around both CVAD and PIV led the authors to conclude that there is room for improvement in the educational preparation of nurses and a need for workplace training. RELEVANCE TO CLINICAL PRACTICE: This scoping review intends to highlight the knowledge gap of nurses with regard to best practices for VAD routine care and maintenance and demonstrate the need for education, both in educational and healthcare institutions, to ensure high-quality care and improved patient outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".