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Record W2902055387 · doi:10.1177/0194599818815106

Impact of Septal Deviation on Recurrent Chronic Rhinosinusitis after Primary Surgery: A Matched Case‐Control Study

2018· article· en· W2902055387 on OpenAlexaff
Terence Fu, Daniel J. Lee, Jonathan Yip, Alisha Jamal, John M. Lee

Bibliographic record

VenueOtolaryngology · 2018
Typearticle
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSeptoplastyMedicineChronic rhinosinusitisSurgeryEndoscopic sinus surgeryRetrospective cohort studyInternal medicineNose

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the impact of untreated deviated nasal septum (DNS) on recalcitrant chronic rhinosinusitis (CRS) among patients undergoing revision endoscopic sinus surgery (ESS). STUDY DESIGN: Case-control study. SETTING: Tertiary academic center. SUBJECTS AND METHODS: We performed a retrospective review of 489 patients undergoing revision ESS for CRS at a tertiary academic center. Patients undergoing septoplasty were matched to nonseptoplasty controls based on age and sex. Preoperative Lund-Mackay score (LMS) was compared between cohorts. Linear regression was used to identify predictors of LMS and ostiomeatal complex (OMC) obstruction. RESULTS: Thirty-six matched pairs (72 patients) were selected for analysis: 36 undergoing septoplasty and revision ESS and 36 undergoing revision ESS alone. Compared with nonseptoplasty controls, the septoplasty group had a significantly higher average LMS (17.8 vs 14.6, P = .02) and a greater rate of OMC obstruction (89% vs 61%, P < .01). The septoplasty group also had significantly higher opacification scores in the maxillary (1.5 vs 1.2, P = .03) and posterior ethmoid (1.8 vs 1.4, P = .02) sinuses. On multivariable analysis, DNS was an independent predictor of LMS ( P = .02) and OMC obstruction ( P < .01). CONCLUSION: Untreated DNS is associated with radiographic markers of CRS severity among patients undergoing revision ESS and may contribute to the multifactorial pathogenesis of persistent CRS.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.016
GPT teacher head0.304
Teacher spread0.288 · 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 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

Citations12
Published2018
Admission routes1
Has abstractyes

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