Variables Influencing Intravenous Catheterization Success by Final-Year Veterinary Students in the Emergency Room
Bibliographic record
Abstract
Abstract Successful placement of intravenous catheters (IVC) is a basic and essential clinical skill for veterinary students. The purposes of this study were to determine the overall success rate for IVC placement in cats and dogs when final-year veterinary students are performing the procedure in a clinical setting, to determine if self-assessed experience level affects IVC placement success rates, and to identify factors affecting student success with this procedure. Final-year students were asked to complete an anonymous survey following each catheter placement attempt during their 3-week core emergency medicine rotation. The survey included self-assessed level of experience, patient species, indication for IVC placement, restrainer, catheter type, insertion site, use of sedation, and perceived degree of coaching. Success or failure in catheter placement was recorded and two attempts were allowed. A Chi-square test was used to evaluate differences between insertion outcomes in dogs and cats. A univariate logistic regression analysis was used to assess the relationship between success and all other variables. A total of 256 catheters were attempted by students, with an overall success rate of 61%. The cephalic vein was associated with successful placement compared with the saphenous vein ( p = .005). There was no relationship between successful catheter placement and self-assessed experience, species, indication for IVC placement, insertion site, use of sedation, catheter type, or restrainer. Final-year veterinary students do not master intravenous catheterization in the emergency room setting, and additional studies are required to improve clinical instruction in this area.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".