Approach to tinnitus management.
Bibliographic record
Abstract
OBJECTIVE: To provide family physicians with an evidence-based and practical approach to managing patients with tinnitus. SOURCES OF INFORMATION: MEDLINE was searched for English-language tinnitus guidelines and reviews. All such articles published between 1980 and 2016 were reviewed, with most providing level II and III evidence. MAIN MESSAGE: Tinnitus affects more than 40% of Canadians at least once in their lifetimes, most commonly older adults. Tinnitus is the perception of sound without external stimulation. It can greatly affect a patient's physical and psychological quality of life. Clinical history taking is directed at eliciting whether symptoms have a pulsatile or nonpulsatile quality, whether symptoms are unilateral or bilateral, and whether there is associated hearing loss. For tinnitus that is pulsatile or unilateral, referral to an otolaryngologist is recommended, as these qualities might be associated with more serious underlying conditions. Most patients with tinnitus can be managed with reassurance, conservative measures, and hearing aids if substantial hearing loss exists. CONCLUSION: Family physicians play the primary role in managing patients with tinnitus and are well situated to address both the physiologic and the psychological manifestations. As tinnitus is very common, helping patients cope with the symptoms through conservative measures and reassurance can prove to have the best outcomes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".