ACVIM consensus statement on diagnosis and management of acute canine thoracolumbar intervertebral disc extrusion
Bibliographic record
Abstract
BACKGROUND: Thoracolumbar intervertebral disc extrusion (TL-IVDE) is the most common cause of acute paraparesis and paraplegia in dogs; however, guidelines on management of the condition are lacking. OBJECTIVES: To summarize the current literature as it relates to diagnosis and management of acute TL-IVDE in dogs, and to formulate clinically relevant evidence-based recommendations. ANIMALS: None. METHODS: A panel of 8 experts was convened to assess and summarize evidence from the peer-reviewed literature in order to develop consensus clinical recommendations. Level of evidence available to support each recommendation was assessed and reported. RESULTS: The majority of available literature described observational studies. Most recommendations made by the panel were supported by a low or moderate level of evidence, and several areas of high need for further study were identified. These include better understanding of the ideal timing for surgical decompression, expected surgical vs medical outcomes for more mildly affected dogs, impact of durotomy on locomotor outcome and development of progressive myelomalacia, and refining of postoperative care, and genetic and preventative care studies. CONCLUSIONS AND CLINICAL IMPORTANCE: Future efforts should build on current recommendations by conducting prospective studies and randomized controlled trials, where possible, to address identified gaps in knowledge and to develop cost effectiveness and number needed to treat studies supporting various aspects of diagnosis and treatment of TL-IVDE.
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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 | 0.053 | 0.102 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.010 | 0.006 |
| Research integrity | 0.017 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".