Comparison of 2 Transillumination Technologies to Improve First-Attempt Success at Peripheral Intravenous Catheter Insertion
Bibliographic record
Abstract
This randomized controlled crossover study, conducted in a university hospital, aimed to compare the success of the first attempt at peripheral intravenous catheter (PIVC) insertion using 2 technologies of the visualization of veins in children at risk of difficult intravenous access (DIVA) guided by light-emitting diodes (LEDs) or infrared radiation (IR). The allocation of the type of technology initially used was determined by randomization. The primary outcome was successful insertion of the PIVC on first attempt. Data were analyzed using the McNemar test, paired t-test, and multiple logistic regression models. This crossover study included 143 children: 69 in Group A and 74 in Group B. The first-attempt PIVC insertion success rate with IR and LED was 65.2% and 44.9% in Group A and 55.4% and 50.0% in Group B, respectively, without statistical significance (P = .720). The results also showed that 51.5% of patients with difficult-to-see vessels (P = .022) and 49.8% with previous complications related to intravenous therapy (P = .008) had first-attempt PIVC insertion success using either transillumination device. The first-attempt PIVC insertion success was statistically similar between the groups. The device also assists in visualizing the veins in children at risk of DIVA.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".