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Record W2791657414 · doi:10.14639/0392-100x-1641

Anterior palatoplasty in the treatment of obstructive sleep apnoea - a systemic review

2018· review· en· W2791657414 on OpenAlexaff
Kenny P. Pang, Edward B. Pang, Kathleen A. Pang, Brian Rotenberg

Bibliographic record

VenueActa Otorhinolaryngologica Italica · 2018
Typereview
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicinePalatoplastySleep (system call)OtologyIntensive care medicineDentistrySurgery

Abstract

fetched live from OpenAlex

This study seeks to determine the objective and subjective success rates of anterior palatoplasty and its variants for the treatment of obstructive sleep apnoea (OSA). A systematic review with two independent searches of Medline, PubMed, Cochrane Library and Evidence Based Medicine Reviews was performed to identify publications relevant to OSA and anterior palatoplasty. All relevant studies published before 30 June 2015 were included. Six studies were included in the systematic review. The numbers of patients in each paper ranged from 13 to 77 (total = 240), and mean age ranged from 21 to 51 years. Substantial and consistent improvement in polysomnography (PSG) outcomes were observed in patients after the anterior palatoplasty, with or without multilevel surgery. The results showed that the anterior palatoplasty technique provides significantly improvement in the post-operative Apnoea-Hypopnea Index. The mean pre-operative AHI (in the 6 papers) improved from 16.3 to 7.1, the snore visual analogue scale improved from 7.5 to 3.1 and the Epworth score reduced from 11.3 to 7.3 post-operatively. The overall pro-rated pooled success rate for all the patients was 72.5%, with a mean follow-up of 17.3 months. Anterior palatoplasty is an effective option in the management of patients with mild to moderate OSA.

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)0.001
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 score0.917
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.053
GPT teacher head0.351
Teacher spread0.298 · 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

Citations18
Published2018
Admission routes1
Has abstractyes

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