Influence of electrode position on cardioversion energy requirements during transvenous electrical cardioversion in horses
Bibliographic record
Abstract
OBJECTIVE: To evaluate influence of electrode position on cardioversion energy (CE; energy delivered in the shock at which cardioversion was achieved) during transvenous electrical cardioversion (TVEC) in horses with atrial fibrillation. ANIMALS: 37 horses with atrial fibrillation (41 cardioversion events). PROCEDURES: Records were reviewed to identify horses that underwent TVEC for treatment of atrial fibrillation. Signalment and CE were recorded. Electrode positions in the right atrium and pulmonary artery were identified on intraoperative radiographs. An orthogonal coordinate space was created, and electrode y- and z-axis coordinates and shadow lengths were determined. Trigonometric modeling was used to estimate x-axis electrode positions that resulted in observed shadows. Postmortem casts of catheterized horses were used to assess electrode paths and anatomic relationships. Model assumptions were tested by use of these and a theoretical data set. Relationships between signalment, electrode position, and CE were assessed via multivariate analysis. RESULTS: Sex and y-axis differences between electrode positions were significant predictors of CE. Population stratification based on examination of residuals improved model strength; populations differed in z-axis variables and in CE. Decreasing distance between electrodes and pulmonary artery electrode positions ventral to the right atrium were associated with increased CE. Agreement between estimated and actual x-axis coordinates was poor. CONCLUSIONS AND CLINICAL RELEVANCE: Optimal electrode positioning can reduce the energy requirement for successful TVEC and may eventually support application of TVEC under short-term IV anesthesia and potentially increase chances of treatment response. Further investigation into these relationships is warranted.
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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 | 0.001 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".