Effect of irrigation technique on the vertebral canal temperature during t<scp>horacolumbar</scp> hemilaminectomy in dogs: An ex vivo study
Bibliographic record
Abstract
OBJECTIVE: To determine the influence of continuous and intermittent bolus irrigation on vertebral canal temperature during thoracolumbar hemilaminectomy. STUDY DESIGN: Ex vivo study. SAMPLE POPULATION: Ten canine cadavers. METHODS: Six consecutive thoracolumbar hemilaminectomies starting at T12-13 with alternating left- or right-side selection, and alternating continuous or intermittent bolus irrigation were performed in each dog resulting in 30 hemilaminectomies per irrigation technique. Drilling was performed for 15 s followed by a 10-s pause and resumed until completion of hemilaminectomy. Continuous irrigation consisted of saline delivered at 15 ml/min during drilling. Bolus irrigation consisted of manual delivery of 10 ml saline during the pause. Temperatures were recorded with two sensors placed within the vertebral canal adjacent to target hemilaminectomy site and compared between techniques with a linear mixed model. RESULTS: Intermittent bolus irrigation was associated with lower peak vertebral canal temperatures (mean 15.7°C; range 9.4-23.3°C) than continuous irrigation (mean 16.7°C; range 9.6-27.6°C, p = .003) (mean difference of 1.1°C, p = .006). Similarly, mean vertebral canal temperatures remained lower when hemilaminectomies were performed under intermittent rather than continuous irrigation (mean difference of 0.48°C, p = .006, linear mixed model). CONCLUSION: Lower vertebral canal temperatures were maintained during hemilaminectomy with intermittent bolus rather than continuous irrigation. CLINICAL SIGNIFICANCE: Both intermittent bolus and continuous irrigation are suitable to prevent elevations in canine vertebral canal temperature during hemilaminectomy.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".