Evaluating Veterinarians’ and Veterinary Students’ Knowledge and Clinical Use of Pulse Oximetry
Bibliographic record
Abstract
RATIONALE FOR THE STUDY: We hypothesized that veterinarians and veterinary students may lack key knowledge about pulse oximetry, which may result in this type of patient monitor not being used on appropriate patient populations or to its full capabilities. METHODOLOGY: A questionnaire was developed to assess an individual's knowledge and understanding of pulse oximetry. Residents and specialists in anesthesiology and critical care at several academic institutions were surveyed first to assess the questionnaire for clarity and to serve as a control group. General veterinary practitioners (GPs) attending continuing education courses at the University of Georgia were surveyed over a 24-month period. Students entering their senior-year anesthesiology rotation at the University of Georgia were also surveyed. RESULTS: Residents and specialists (69% correct responses) scored significantly higher than senior students (46%), who scored significantly higher than GPs (34%). Only 15% of GPs and 21% of senior students reported that they had received training in pulse oximetry in school. Those who had received training scored significantly higher than those who had not. Many GPs did not report using a pulse oximeter on their critical patients under anesthesia, a group that would be expected to benefit from its use. CONCLUSIONS: Veterinarians have a poor understanding of how pulse oximetry works, the information it provides, and how best to apply it to their patients. Furthermore, the respondents did not use pulse oximeters in a manner that would yield the most information and result in the greatest benefit to the patient relative to the cost of the instrument. Didactic training in veterinary curricula and during continuing education opportunities continues to be necessary in order to produce veterinarians who have an understanding of the technologies available to improve patient care.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".