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Record W2890477051

Approach to tinnitus management.

2018· article· en· W2890477051 on OpenAlexaff
Vincent Wu, Bonnie Cooke, Susan T. Eitutis, Matthew T W Simpson, Jason A. Beyea

Bibliographic record

VenuePubMed · 2018
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsHotel Dieu HospitalCollege of Family Physicians of CanadaQueen's University
Fundersnot available
KeywordsTinnitusMedicineOtorhinolaryngologyAudiologyHearing lossReferralMEDLINEQuality of life (healthcare)PerceptionIntensive care medicinePsychologyFamily medicinePsychiatryNursing
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.876
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.073
GPT teacher head0.255
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations46
Published2018
Admission routes1
Has abstractyes

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