Repetitive Transcranial Magnetic Stimulation For The Treatment of Chronic Tinnitus: A Preliminary Study of The Influence of Traumatic Brain Injury on Treatment Response
Bibliographic record
Abstract
This study aims to test whether the efficacy of repetitive Transcranial Magnetic Stimulation (rTMS) differs between patients who developed tinnitus following a traumatic brain injury (TBI), and those without a history of TBI. This was a parallel pilot, open-label, non-randomized, clinical trial to compare the efficacy of low frequency rTMS on tinnitus symptoms in patients with and without a TBI history. Patients with moderate to severe tinnitus symptoms based on the Tinnitus Handicap Inventory (THI) and the Tinnitus Functional Index (TFI) were enrolled in the study. Validated questionnaires (THI and TFI) were used to quantify the severity of tinnitus symptoms and hearing impairment (Hearing Handicap Index - HHI) before and after ten sessions of rTMS of the left primary auditory cortex. Hearing threshold levels as well as speech reception and speech discrimination thresholds were also compared. The number of patients who experienced a reduction in their subjective tinnitus symptoms was greater and sustained longer in patients without a history of TBI. The same was seen with subjective symptoms of hearing impairment. In conclusion, our preliminary results suggest tinnitus patients without a history of TBI respond better to low frequency rTMS than those with a history of TBI, suggesting that treatments could be more effective if tailored to tinnitus etiology.
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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 | 0.003 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".