The assessment of pulsatile tinnitus—a systematic review of underlying pathologies and modern diagnostic approaches
Bibliographic record
Abstract
Background: Pulsatile tinnitus (PT) is an auditory phenomenon that occurs in the absence of an external stimulus and presents as a humming or whooshing sound synchronous with the subject’s heartbeat. PT has many causes, ranging from the benign to the life threatening. In the following report, we focus on defining the most common causes of PT and explore changing approaches to diagnostic radiology used in the assessment of PT patients, with the goal of providing an updated and practical set of guidelines for the assessment of this complicated condition. Methods: A collection of case studies, retrospective reviews and technical reports were sourced from PubMed’s online database. The initial cohort was filtered by language and content, and then sorted according to patient demographics, presenting symptoms, imaging protocols and relative success of radiological investigations. Results: The most common causes of PT include vascular anomalies, benign or idiopathic intracranial hypertension (BIH/IIH), and certain middle ear masses. We recommend using magnetic resonance imaging (MRI) as the primary imaging modality for investigating most cases of PT, due to an increase in sensitivity and decrease in medical risk for the patient compared to computed tomography (CT) and traditional angiography. We detail protocols for both basic and comprehensive MRI studies to be used in the assessment of PT and provide descriptions of common radiological findings with representative images for reference. Finally, we make an argument in favour of foregoing extensive imaging studies in cases of subjective idiopathic PT, where no risk factors can be identified in the patient’s medical history or physical examination. Conclusions: The diagnosis of pulsatile tinnitus should be guided by comprehensive clinical data and dominated by the conservative use of MRI. In subjective PT where no risk factors are present, we recommend foregoing extensive imaging.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.017 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".