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Record W2174793086 · doi:10.1097/mao.0000000000000900

Treatment Effectiveness for Symptoms of Patulous Eustachian Tube

2015· review· en· W2174793086 on OpenAlexaff
Kimberly Luu, Andrew Remillard, Marcela Fandiño, Alexander J. Saxby, Brian D. Westerberg

Bibliographic record

VenueOtology & Neurotology · 2015
Typereview
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsMedicineEustachian tubePsychological interventionMEDLINESurgeryMiddle ear

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine the effectiveness of currently available medical and surgical interventions for treating symptoms of Patulous Eustachian Tube (PET). DATA SOURCES: A comprehensive search of MEDLINE (January 1948 to July 8, 2015), EMBASE (January 1974 to July 8, 2015), gray literature, hand searches, and cross-reference checking. STUDY SELECTION: Original published reports evaluating an intervention to treat the symptoms of patulous eustachian tube in patients 18 years and older. DATA EXTRACTION: Quality-of-case reviews were assessed with the National Institute of Health (NIH) Quality Assessment Tool for Case Series Studies. DATA SYNTHESIS: The search strategy identified 1,104 unique titles; 39 articles with 533 patients are included. The available evidence consists of small case series and case reports. The most common medical treatment was nasal instillation of normal saline. Surgical treatments were categorized as mass loading of the tympanic membrane, eustachian tube plugging, and manipulation of eustachian tube musculature. CONCLUSIONS: The available evidence for management of patients with PET is poor in quality and consists predominantly of small case series. Further research is needed to determine the comparative efficacy of the current treatments.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.382
Teacher spread0.317 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations34
Published2015
Admission routes1
Has abstractyes

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