Relationship between intracranial pressure as measured by an epidural intracranial pressure monitoring system and optic nerve sheath diameter in healthy dogs
Bibliographic record
Abstract
OBJECTIVE: To evaluate the association between ultrasonographically measured optic nerve sheath diameter (ONSD) and acute increases in intracranial pressure (ICP) as measured by an epidural intracranial pressure monitoring system (EICPMS) in healthy dogs. ANIMALS: 6 young healthy dogs. PROCEDURES: An EICPMS connected to a pressure monitor was used to generate a continuous pressure waveform in each anesthetized dog. A 22-gauge IV catheter was inserted into the brain parenchyma through the contralateral parietal bone, and 0.5 to 2.0 mL of anticoagulated autologous blood was injected at predetermined intervals. At baseline (immediately after EICPMS placement) and following each injection, the ICP as indicated by EICPMS was recorded, and 3 ultrasonographic images of the optic nerve sheath of each eye were obtained. The ONSD was measured at maximum diameter and at 5 mm caudal to the optic disk. RESULTS: In linear models, the maximum ONSD was positively associated with increasing ICP. Specifically, the rate of maximum ONSD increase was greater for pressures ≤ 20 mm Hg above baseline (0.0534 mm/1 mm Hg ICP increase) than for pressures > 40 mm Hg above baseline (0.0087 mm/1 mm Hg ICP increase). The relationship of ICP to maximum ONSD was slightly nonlinear and best explained by comparison of fractional polynomial regression models. CONCLUSIONS AND CLINICAL RELEVANCE: ICP was positively and nonlinearly associated with increasing maximum ONSD, especially when ICP was ≤ 20 mm Hg above baseline, supporting the conclusion that ultrasonographic measurement of maximum ONSD may provide a noninvasive monitoring tool for evaluation of ICP in dogs. Further research is needed to assess the utility of these measurements in clinical patients.
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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 | 0.003 |
| 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 | 0.000 | 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".