Comparison of cardiac output determined by arterial pulse pressure waveform analysis method (FloTrac/Vigileo) versus lithium dilution method in anesthetized dogs
Bibliographic record
Abstract
OBJECTIVE: To compare the determination of cardiac output (CO) via arterial pulse pressure waveform analysis (FloTrac/Vigileo) versus lithium dilution method. DESIGN: Prospective study. SETTING: University teaching hospital. ANIMALS: Six adult dogs. INTERVENTIONS: Dogs were instrumented for CO determinations using lithium dilution (LiDCO) and FloTrac/Vigileo methods. Direct blood pressure, heart rate, arterial blood gases, and end-tidal isoflurane (ETIso) and CO(2) concentrations were measured throughout the study while CO was manipulated with different depth of anesthesia and rapid administration of isotonic crystalloids at 60 mL/kg/h. MEASUREMENTS AND MAIN RESULTS: Baseline CO measurements were obtained at 1.3% ETIso and were lowered by 3% ETIso. Measurements were obtained in duplicate or triplicate with LiDCO and averaged for comparison with corresponding values measured continuously with the FloTrac/Vigileo method. For 30 comparisons between methods, a mean bias of -100 mL/kg/min and 95% limits of agreement between -311 and +112 mL/kg/min (212 mL/kg/min) was determined. The mean (mL/kg/min) of the differences of LiDCO-Vigileo=62.0402+-0.8383 × Vigileo, and the correlation coefficient (r) between the 2 methods 0.70 for all CO determinations. The repeatability coefficients for the individual LiDCO and FloTrac/Vigileo methods were 187 and 400 mL/kg/min, respectively. Mean LiDCO and FloTrac/Vigileo values from all measurements were 145 ± 68 mL/kg/min (range, 64-354) and 244 ± 144 mL/kg/min (range, 89-624), respectively. The overall mean relative error was 48 ± 14%. CONCLUSION: The FloTrac/Vigileo overestimated CO values compared with LiDCO and the relative error was high, which makes this method unreliable 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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".