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Record W4411715044 · doi:10.4103/jiaomr.jiaomr_16_25

Relationship between Nasal Septum Deviation and Size of Inferior Turbinate in Obstructive Sleep Apnea: A Systematic Review

2025· review· en· W4411715044 on OpenAlexaboutno aff
K M Veena, A. M Mohamed Sharuff, Prashanth Shenoy, Laxmikanth Chatra, Rachana V. Prabhu, Prathima Shetty

Bibliographic record

VenueJournal of Indian Academy of Oral Medicine and Radiology · 2025
Typereview
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineObstructive sleep apneaNasal septumApneaSleep apneaSleep (system call)AnesthesiaNoseSurgery

Abstract

fetched live from OpenAlex

Abstract Background: Obstructive sleep apnea is increasing in prevalence, with multiple risk factors, but the relationship between nasal septum deviations and inferior turbinate size remains controversial. Objective: This systematic review examines the link between obstructive sleep apnea (OSA) and upper airway abnormalities, specifically nasal septum deviation and inferior turbinate hypertrophy. Methods: Registered in PROSPERO [CRD42024523975], the review used a two-phase search in six databases, including eligible studies while excluding small samples, animal studies, case reports, reviews, and non-full-text articles. Two reviewers extracted data, with findings summarized narratively and analyzed using risk ratios and standardized mean differences. Study quality was assessed via the Newcastle-Ottawa Scale. Results: This review of nine studies [five case-control, four cohort] found a strong association between nasal septum deviation (NSD), inferior turbinate hypertrophy (ITH), and OSA in 34,742 participants, with low bias risk and reliable diagnostic methods. Conclusion: The systematic review suggests assessing obstructive sleep apnea patients for nasal septum deviations and inferior turbinate hypertrophy, and recommending specialized training for healthcare and dental professionals for improved diagnosis and treatment outcomes. Further research is needed.

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)0.003
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.095
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.063
GPT teacher head0.400
Teacher spread0.337 · 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 designSystematic review
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

Citations1
Published2025
Admission routes1
Has abstractyes

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