Assessment of lithium dilution cardiac output as a technique for measurement of cardiac output in dogs
Bibliographic record
Abstract
OBJECTIVES: To determine agreement of cardiac output measured by use of lithium dilution cardiac output (LiDCO) and thermodilution cardiac output (TDCO) techniques in dogs and to determine agreement of low- and high-dose LiDCO with TDCO. ANIMALS: 10 dogs (7 males, 3 females). PROCEDURE: Cardiac output was measured in anesthetized dogs by use of LiDCO and TDCO techniques. Four rates of cardiac output were induced by occlusion of the caudal vena cava, changes in depth of anesthesia, or administration of dobutamine. Lithium dilution cardiac output was performed, using 2 doses of lithium chloride (low and high dose). Each rate of cardiac output allowed 4 comparisons between LiDCO and TDCO. RESULTS: 160 comparisons were determined of which 68 were excluded. The remaining 92 comparisons had values ranging from 1.10 to 12.80 L/min. Intraclass correlation coefficient (ICC) between low-dose LiDCO and TDCO was 0.9898 and between high-dose LiDCO and TDCO was 0.9896. When all LiDCO determinations were pooled, ICC was 0.9894. For determinations of cardiac output < 5.0 L/min, ICC was 0.9730. Mean +/- SD of the differences of TDCO minus LiDCO for all measurements was -0.084+/-0.465 L/min, and mean of TDCO minus LiDCO for cardiac outputs < 5.0 L/min was -0.002+/-0.245 L/min. CONCLUSIONS AND CLINICAL RELEVANCE: The LiDCO technique is a suitable substitute for TDCO to measure cardiac output in dogs. Use of LiDCO eliminates the need for catheterization of a pulmonary artery and could increase use of cardiac output monitoring, which may improve management of cardiovascularly unstable animals.
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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 | 0.003 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".