Accuracy and precision of venous pressure measurements of endovascular microcatheters in the setting of dural venous sinus stenosis
Bibliographic record
Abstract
INTRODUCTION: Dural venous sinus stenosis (DVSS) may lead to increased intracranial pressure, sometimes requiring a stent if a high pressure gradient exists. Many neuroendovascular physicians use microcatheters to measure gradients, yet there are no studies comparing the accuracies and precisions of modern day microcatheters. We examined pressure recordings from five commonly used microcatheters in an experimental DVSS model. METHODS: Using a programmable pump, dynamic flow was established in a closed circuit mimicking the venous sinus waveform. Microcatheters with 150 cm effective lengths were connected proximally to pressure transducers. Mean recording pressures were compared with a high fidelity microcatheter (HFM) in several configurations including no stenosis, proximal to a focal stenosis, and distal to a focal stenosis in opposing orientations. RESULTS: All microcatheters recorded lower pressures than the HFM. Three of the five microcatheters successfully met intracranial pressure monitoring device standards in all conditions, while one did not meet standards in any configuration. The performance of the final microcatheter was variable, with inaccuracies occurring in unrestricted flow. All microcatheters demonstrated relatively high precision, but with variable accuracies. The larger diameter microcatheters displayed the least damping and therefore the greatest accuracies. Of the three smaller microcatheters, dimensions did not predict performance, suggesting that microcatheter construction may also play a role in pressure accuracy. CONCLUSION: The use of microcatheters to record dural venous sinus pressures must be done with an understanding of the inherent limitations and inaccuracies, especially if clinical decisions are made from the results.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".