Torrents of torment: turbulence as a mechanism of pulsatile tinnitus secondary to venous stenosis revealed by high-fidelity computational fluid dynamics
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Pulsatile tinnitus (PT) is a debilitating condition that can be caused by a vascular abnormality, such as an arterial or venous lesion. Although treatment of PT-related venous lesions has been shown to successfully cure patients of the associated 'tormenting' rhythmical sound, much controversy still exists regarding their role in the etiology of PT. METHODS: A patient presented with a history of worsening, unilateral PT. A partial venous sinus obstruction related to the large arachnoid granulation was detected on the right side, and subsequently stented at the right transverse sinus. High-fidelity computational fluid dynamics (CFD) was performed on a 3D model digitally segmented from the pre-stent venogram, with assumed pulsatile flow rates. A post-stent CFD model was also constructed from this. Data-driven sonification was performed on the CFD velocity data, blinded to the patient's self-reported sounds. RESULTS: The patient reported that the PT was completely resolved after stenting, and has had no recurrence of the symptoms after more than 2 years. CFD simulation revealed highly disturbed, turbulent-like flow at the sigmoid sinus close to auditory structures, producing a sonified audio signal that reproduced the subjective sonance of the patient's PT. No turbulence or sounds were evident at the stenosis, or anywhere in the post-stent model. CONCLUSIONS: For the first time, turbulence generated distal to a venous stenosis is shown to be a cause of PT. High-fidelity CFD may be useful for identifying patients with such 'torrents' of flow, to help guide treatment decision-making.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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 it