Bibliographic record
Abstract
The purpose of this retrospective study was to review cases of spinal fractures or luxations (SFL) treated with various modalities in order to describe fracture location, neurological status, treatment, outcome and complications in a patient population at a single centre. The medical records of dogs and cats that had been diagnosed with a SFL between C1 and L7 between January 1995 and June 2005 were reviewed in order to collect pertinent data. Ninety-five cases were included in this study. The severity of spinal cord injury was graded on a scale from 0 to 5. Vehicular trauma was the most common cause of SFL. Spinal fractures were localized between C1-C5 in 10 cases, C6-T2 in one case, T3-L3 in 54 cases, L4-L7 in 36 cases. Thirty patients that were euthanatized without treatment had a median neurological score of 5. Twenty-eight patients, all of which had motor function, were treated conservatively and there was not any change in their median neurological grade at the time of discharge. Thirty-seven patients had surgery, 27 of which were non ambulatory. Thirty-five of 37 were stabilized using pins and/or screws and PMMA or various other techniques. The median neurological grade of surgically treated patients improved by one point between the time of initial diagnosis and discharge. Implant removal was performed in five cases. The patients that were treated with pins and/or screws and PMMA were significantly more improved than conservatively managed patients at the time of discharge, although the surgically treated patients were hospitalized significantly longer than the conservatively managed patients. Our results suggest that dogs that retain pain sensation prior to surgery have a good prognosis for functional recovery. In this study, the dogs that were treated conservatively retained purposeful movement and had a good prognosis for recovery.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".