Agreement between two oscillometric blood pressure technologies and invasively measured arterial pressure in the dog
Bibliographic record
Abstract
OBJECTIVES: To compare two commonly used oscillometric technologies for obtaining noninvasive blood pressure (NIBP) measurements and to determine if there is a difference in agreement between these systems and invasive blood pressure (IBP) measurements. STUDY DESIGN: Prospective, experimental study. ANIMALS: Twenty adult laboratory dogs. METHODS: Each dog was anesthetized and its median caudal artery catheterized for IBP monitoring. An NIBP cuff was placed in the middle third of the antebrachium and attached to either monitor-1 or monitor-2. Four pairs of concurrent NIBP and IBP measurements were recorded with each monitor. Agreement between IBP and NIBP measurements was explored using Bland-Altman analysis, as well as the American College of Veterinary Internal Medicine (ACVIM) and Association for the Advancement of Medical Instrumentation (AAMI) guidelines for the validation of NIBP devices. RESULTS: Both NIBP technologies produced results that met the ACVIM and AAMI guidelines for the validation of NIBP devices. For monitor-1, analyses of agreement showed biases of 0.2 mmHg [95% limits of agreement (LoA) -11.8 to 12.3 mmHg] in systolic arterial pressure (SAP) values, -2.6 mmHg (95% LoA -14.4 to 9.1 mmHg) in diastolic arterial pressure (DAP) values, and -2.5 mmHg (95% LoA -12.7 to 7.3 mmHg) in mean arterial pressure (MAP) values. For monitor-2, analyses of agreement showed biases of 3.4 mmHg (95% LoA -8.7 to 15.5 mmHg) in SAP values, 2.2 mmHg (95% LoA -6.6 to 10.9 mmHg) in DAP values, and 1.6 mmHg (95% LoA -5.9 to 8.9 mmHg) in MAP values. CONCLUSIONS AND CLINICAL RELEVANCE: Multi-function monitors can contain components from various manufacturers. Clinicians should consider whether these have been validated in the species to be monitored. Both of the technologies studied here seem appropriate for use in dogs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.021 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".