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Record W1985472205 · doi:10.2310/7070.2003.37144

Oral Appliance Therapy for Snoring and Sleep Apnea: Preliminary Report on 86 Patients Fitted with an Anterior Mandibular Positioning Device, The Silencer

2003· article· en· W1985472205 on OpenAlexaffvenue
Phillip S. Wade

Bibliographic record

VenueThe Journal of Otolaryngology · 2003
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsMarkham Stouffville Hospital
Fundersnot available
KeywordsMedicineOral applianceObstructive sleep apneaContinuous positive airway pressurePolysomnogramSleep apneaSleep studyOtorhinolaryngologyOral and maxillofacial surgeryDentistryApneaSurgeryAnesthesiaPolysomnography

Abstract

fetched live from OpenAlex

There has been a great deal of interest recently in snoring and obstructive sleep apnea (OSA) by both dental and medical professions, as well as the media. Oral appliance therapy has been recognized by many sleep disorder specialists as the primary treatment of choice for snoring and mild to moderate OSA. Continuous positive airway pressure (CPAP) is the gold standard treatment for severe OSA, with oral appliance therapy reserved for CPAP failures. CPAP therapy has a compliance rate of 50 to 70%. The author has had experience with anterior mandibular positioning devices, in particular, Dr. Wayne Halstrom's Silencer for approximately 2 years. All patients are thoroughly investigated to include a polysomnogram (PSG) to assess the degree of snoring and OSA. Patients who are suitable candidates for oral appliance therapy are offered a temporary appliance with a follow-up PSG prior to fitting with the permanent appliance or initially with a more comfortable, custom-fitted permanent appliance. In either case, attempts are made to convince the patients of the necessity for a follow-up PSG to evaluate the efficacy of the device. The results, as well as potential harmful side effects and complications, are presented and are compared with the results of other recent studies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.303
Teacher spread0.283 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations25
Published2003
Admission routes2
Has abstractyes

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