Indirect measurement of blood pressure using a pulse oximeter in isoflurane anesthetized dogs
Bibliographic record
Abstract
Abstract Objective:To determine the accuracy of indirect blood pressure (BP) measurements obtained with a pulse oximeter as compared with direct measurements in dogs under isoflurane anesthesia. The Doppler and oscillometric BP monitors were included for comparison. Design:Prospective, experimental study. Animals:Twenty healthy dogs (23 ± 8 kg) anesthetized for research or teaching. Interventions:Dogs were anesthetized with propofol or thiopental and maintained using positive pressure ventilation with isoflurane in 100% O2. Random adjustment of BP was achieved by inhalant adjustment or dopamine infusion to achieve low (≤85 mmHg), normal (90–120 mmHg), or high systolic BP (≥125 mmHg). Triplicate measurements for BP were taken with direct (dorsal pedal artery), Doppler (forelimb), oscillometric (same forelimb), and plethysmographic (pulse oximeter on tongue) methods. Measurements and main results:Using regression analysis and a modified Bland–Altman's technique, the lowest bias was achieved with the Doppler. Systolic BP readings at low, normal, and high BP were within 10 mmHg of direct recordings 95%, 70%, and 30% of the time for pulse oximetry; 95%, 85%, and 55% of the time for Doppler; 42%, 65%, and 30% of the time for oscillometric determination, respectively. Oscillometric mean BP readings were within 10 mmHg of direct measurements 53%, 60%, and 45% of the time, respectively. Conclusions:The pulse oximeter is an acceptable method for measuring BP in anesthetized dogs if assessment of trends is sufficient. All indirect methods showed greater bias and poorer precision at high BP. The Doppler may be the preferred indirect method.
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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 | 0.002 | 0.007 |
| 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 | 0.000 |
| 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 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".